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PMC10000452 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050703 healthcare-11-00703 Article Cretan Aging Cohort-Phase III: Methodology and Descriptive Characteristics of a Long-Term Longitudinal Study on Predictors of Cognitive Decline in Non-Demented Elderly from Crete, Greece Basta Maria Conceptualization Methodology Formal analysis Writing - review & editing Supervision Funding acquisition 12*+ Skourti Eleni Formal analysis Investigation Data curation Writing - original draft Writing - review & editing 1+ Alexopoulou Christina Conceptualization Methodology Data curation Writing - review & editing Supervision 3 Zampetakis Alexandros Investigation Data curation 1 Ganiaris Andronikos Investigation Data curation 1 Aligizaki Marina Investigation 1 Simos Panagiotis Conceptualization Methodology Formal analysis Data curation Writing - review & editing Supervision 14 Vgontzas Alexandros N. Conceptualization Methodology Writing - review & editing Supervision Funding acquisition 12 Steiger Axel Academic Editor 1 Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, 71003 Heraklion, Greece 2 Sleep Research and Treatment Center, Department of Psychiatry, Penn State University, State College, PA 16802, USA 3 Department of Intensive Care Unit, University Hospital of Heraklion, 71500 Heraklion, Greece 4 Computational Biomedicine Lab, Institute of Computer Science, Foundation for Research and Technology-Hellas, 70013 Heraklion, Greece * Correspondence: [email protected]; Tel.: +30-2810-392-402; Fax: +30-2810-392-859 + These authors contributed equally to this work. 27 2 2023 3 2023 11 5 70329 1 2023 23 2 2023 25 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Identifying modifiable factors that may predict long-term cognitive decline in the elderly with adequate daily functionality is critical. Such factors may include poor sleep quality and quantity, sleep-related breathing disorders, inflammatory cytokines and stress hormones, as well as mental health problems. This work reports the methodology and descriptive characteristics of a long-term, multidisciplinary study on modifiable risk factors for cognitive status progression, focusing on the 7-year follow-up. Participants were recruited from a large community-dwelling cohort residing in Crete, Greece (CAC; Cretan Aging Cohort). Baseline assessments were conducted in 2013-2014 (Phase I and II, circa 6-month time interval) and follow-up in 2020-2022 (Phase III). In total, 151 individuals completed the Phase III evaluation. Of those, 71 were cognitively non-impaired (CNI group) in Phase II and 80 had been diagnosed with mild cognitive impairment (MCI). In addition to sociodemographic, lifestyle, medical, neuropsychological, and neuropsychiatric data, objective sleep was assessed based on actigraphy (Phase II and III) and home polysomnography (Phase III), while inflammation markers and stress hormones were measured in both phases. Despite the homogeneity of the sample in most sociodemographic indices, MCI persons were significantly older (mean age = 75.03 years, SD = 6.34) and genetically predisposed for cognitive deterioration (APOE e4 allele carriership). Also, at follow-up, we detected a significant increase in self-reported anxiety symptoms along with a substantial rise in psychotropic medication use and incidence of major medical morbidities. The longitudinal design of the CAC study may provide significant data on possible modifiable factors in the course of cognitive progression in the community-dwelling elderly. elderly cognitive decline mild cognitive impairment RISK factors mental health indices longitudinal cohort study Hellenic Foundation for Research and Innovation (HFRI)HFRI-FM17-4397 the National Strategic Reference Framework (NSRF)MIS 377299 Current research was funded by the Hellenic Foundation for Research and Innovation (HFRI) 2020-2022-Research Funding Program: ELIDEK entitled "Sleep Apnea (OSA) and poor sleep as Risk Factors for decreased cognitive performance in patients with Mild Cognitive Impairment: the Cretan Aging Cohort (CAC)", [Grant code: HFRI-FM17-4397] (P.I: M. Basta). Phase I and II were supported by the National Strategic Reference Framework (NSRF) 2007-2013--Research Funding Program: THALES entitled: "UOC-A multi-disciplinary network for the study of Alzheimer's Disease" [Grant code: MIS 377299] (P.I: A.N. Vgontzas). pmc1. Introduction As life expectancy increases, cognitive impairment becomes an inextricable facet of aging. Worldwide, it is estimated that over 55 million people live with dementia, a number that is about to rise to 139 million people by 2050, while a substantial percentage of dementia patients has yet to receive a formal diagnosis . In contrast, normal cognitive aging comprises predictable age-related cognitive changes, as indicated by age and education-adjusted domain-specific scores that fall within 1.5 standard deviations from the population mean . Persons who display domain-specific (i.e., not global) cognitive impairment, which is not considered serious mental disorder and does not interfere with daily functioning, are likely to be diagnosed with mild cognitive impairment (MCI) . Individuals with MCI are considered at high risk of progression to dementia , with conversion rates ranging from 6 to 44.8%, according to a recent meta-analysis . MCI incidence rates increase from 22.5% for ages 75-79 to 60.1% for individuals beyond 85 years old . In Greece specifically, MCI prevalence ranges from 13.11% to 32.4% (Cretan Aging Cohort) . As a prodromal stage of dementia pathology, MCI constitutes a critical "window" for early intervention, and consequently, several studies have focused on identifying modifiable risk factors for cognitive deterioration. Sleep disturbances are a frequent, yet potentially modifiable, comorbid condition in the elderly, which appears to contribute significantly to cognitive impairment and disease prognosis . According to a recent meta-analysis, sleep quality, measured by dysregulation in sleep architecture, was found to differentiate cognitively intact and MCI persons, with the latter group exhibiting increased sleep latency and less Cyclic Alternating Pattern expression compared to healthy individuals . Findings regarding the association between sleep duration and cognitive impairment are rather controversial , with some studies indicating greater risk for cognitive decline among short (<6 h) and long sleepers (>8 h), or both , whilst other studies fail to report such an association. Cross-sectional analyses from the Cretan Aging Cohort (CAC) revealed significant associations between objective long sleep duration and executive deficits among persons diagnosed with MCI and cognitively non-impaired individuals , whereas long sleep duration in MCI and Alzheimer's Disease (AD) patients may be driven by the presence of APOE (Apolipoprotein E) e4 allele . Other biomarkers (including genetic factors, pro-inflammatory cytokines and stress hormones) contribute to disease progression and differentiate between clinical categories (MCI, dementia). The APOE e4 allele is an established risk factor for dementia, incident MCI, and rate of conversion from MCI to dementia . Dysregulation of inflammatory response (a condition also known as "inflamm-aging") seems to play a critical role in the pathogenesis of neurodegenerative diseases, although the underlying mechanisms are not clearly understood . Elevated cerebrospinal fluid and plasma levels of Tumor Necrosis Factor-alpha (TNFa) and Interleukin-6 (IL-6) in AD patients predict further cognitive decline and have been linked to worse cognitive performance in both MCI and AD patients . Impaired regulation of pro-inflammatory cytokine secretion has been found in sleep-related disorders and acute sleep deprivation . Moreover, increased IL-6 plasma levels predict poor sleep quality and relate to excessive daytime sleepiness in the cognitively intact elderly . Elevated cerebrospinal fluid and plasma cortisol levels have been detected in both MCI and dementia patients, whereas increased cortisol may exert deleterious effects on memory recall via biphasic activation of specific receptors in the hippocampus, leading to downregulation of Long-Term Potentiation . Additionally, overexpression of cortisol receptors in prefrontal areas may be associated with executive deficits emerging from irregular activity patterns in the prefrontal cortex . The two processes may be interrelated, as impaired executive function mediates the relationship between basal cortisol levels and impaired memory recall . Neuropsychiatric symptoms and mental morbidities are particularly common among elderly with and without neurocognitive disorders or MCI . Depression prevalence among MCI patients may be as high as 32% and is considered a risk factor for dementia progression and accelerated rate of cognitive deterioration (possibly moderated by APOE e4 carriership) . Patients with persistent depressive symptomatology are more likely to present hippocampal atrophy , whereas depression diagnosis is often accompanied by pronounced amyloid abnormalities . Anxiety is another frequent comorbid condition (although not as extensively studied as depression), with prevalence rates reaching 21% among MCI patients . Significant anxiety symptoms can compromise daily functioning in MCI patients and increase the risk for dementia progression . A trend towards reduced cognitive performance is present in patients with concurrent anxiety and depressive manifestations, although the contribution of anxiety symptoms on the observed cognitive deficits remains unclear . Anxiety symptoms are also linked to elevated pro-inflammatory cytokines and hypercortisolemia, a condition that leads to dementia-associated brain atrophy due to long-term glucocorticoid exposure . Last but not least, sleep dysregulation is a core depression symptom, and sleep-associated disturbances (insomnia symptoms, poor sleep quality) are overexpressed among MCI patients . The CAC was established in 2013 to investigate sociodemographic, medical, lifestyle, inflammation and neuroendocrine, sleep-related, genetic, cognitive and neuropsychiatric characteristics of the elderly residing in mostly rural areas of the Heraklion prefecture in the island of Crete, Greece. The present report describes the protocol of a 7-year follow-up study on a subset of CAC participants, aimed to identify potentially modifiable predictors of cognitive deterioration among persons who were either cognitively non-impaired or were diagnosed with MCI. Similar large-scale prospective studies are being conducted in Greece and focus on sociodemographic information, medical and mental health indices, lifestyle factors and biomarkers (SHARE; Survey of Health, Ageing and Retirement in Europe ), as well as nutrition and neuropsychological markers of cognitive progression (HELIAD study; Hellenic Longitudinal Investigation of Aging & Diet ). However, to our knowledge, up to now, this is the first longitudinal cohort study conducted in Greece and among few worldwide with a relatively large, well-defined sample--including MCI patients--with a special focus on objective sleep, inflammation, stress and neuropsychiatric symptoms as possible modifiable factors for dementia. 2. Materials and Methods 2.1. Study Design 2.1.1. Phase I-Phase II During Phase I, 3140 community-dwelling participants (mean age 73.7 +- 7.8 years) from rural areas of Heraklion, Crete (Cretan Aging Cohort) were examined. Eligible participants were those aged >=60 years old who visited Primary Health Care Centers (staffed by physicians participating in the Primary Health Care research network of the CAC study) in both rural and urban areas of Heraklion and consented to participate in the study. Patients with acute symptomatology (terminal illnesses, severe movement impairment) were excluded from the study. Data from the 2011 national census were utilized in order to compare CAC participants to the whole Greek and Cretan population of similar age (for a more thorough analysis, see ). Demographic information and medical data were collected, and all participants were administered the Mini Mental State Examination (MMSE) test. Participants who had scored <24 points on MMSE (n = 636) were invited to a comprehensive neuropsychological and neuropsychiatric examination (Phase II), and a total of 344 consenting persons (comparable in terms of demographic and anthropometric measurements to the 636 participants) completed the evaluation. A control group (n = 181) of persons scoring >=24 points on MMSE during Phase I was also formed using a proportional stratification process to match the low MMSE group on gender and place of residence. Of those, 161 persons consented and took part in Phase II examination . During Phase II (2013-2014), all participants underwent full neuropsychological/neuropsychiatric/neurological evaluation, 3-day, 24-h actigraphy recording, and blood sampling (to measure baseline morning cortisol, pro-inflammatory cytokines and genetic biomarkers); medical history, sleep complaints and general functionality information were also recorded. Consensus clinical diagnoses for dementia and MCI were based upon the Diagnostic & Statistical Manual of Mental Disorders (DSM, 4th Edition) and the International Working Group (IWG) criteria, accordingly . In total, 146 persons were found cognitively intact, whilst 231 participants were diagnosed with MCI of any type . 2.1.2. Phase III The participant pool for the 7-year follow up study (Phase III) comprised all CNI persons (n = 146) and individuals who met the formal criteria for MCI (n = 231) during Phase II. Patients diagnosed with dementia were excluded from Phase III testing, which took place between October 2020 and August 2022 . In total, 103 participants (27.3%) had passed away in the intervening years, 56 persons (14.9%) could not be located, and 63 persons (16.7%) refused to participate, raising the total attrition rate (inability to participate for any reason) to 58.9%. In total, 149 MCI and 73 CNI individuals could not be retested. From the 274 survivors, 155 individuals completed the evaluation, although data from four participants were not included in the analyses due to severe medical comorbidities or sensory loss. Thus, the final response rate reached 55.1%. All participants were contacted by telephone and came from 11 different districts in the prefecture of Heraklion. Testing procedures were similar to those followed in Phase II, permitting direct quantitative comparisons between the two time points on the majority of measures. Examination was conducted at participants' homes and included medical history and physical examination, neuropsychological testing, a night of polysomnography recording and a 7-day, 24-h actigraphy, as well as a morning blood draw to assess stress and inflammatory biomarkers. The study was approved by the Ethics Committee of the University of Crete (number of approval: 61/9-3-2020). A detailed description of the study protocol is provided below. Figure 1 presents a flow chart of the entire study. 2.2. Measurements 2.2.1. Sleep Measurements (i) Polysomnography (PSG) We collected data from 144 participants. Each participant underwent one night home sleep study ad libitum using a portable Type II7 16 channel polysomnography device (Alice, PDx, Philips, Respironics, Murrysville, PA, USA). The sleep study registered the following parameters: oral-nasal airflow via pressure cannula and thermistor, respiratory effort via the abdominal and chest belts, arterial oxygen saturation level via the pulse oximeter (oxygen saturation and pulse rate), body position detection (supine or non-supine), cardiac electrical activity, C3M2 and C4M1 electroencephalogram, electrooculogram and chin and leg electromyogram. Scoring was performed manually from a sleep expert physician according to the American Association Sleep Medicine scoring manual version 2.6.2020. Apnea/Hypopnea episodes followed the standard procedures (AASM, 2007) and Obstructive Sleep Apnea was defined as an Apnea/Hypopnea Index >= 15. Additional sleep variables, such as Sleep Latency, Total Sleep Time, Total Time in Bed, Sleep Efficiency and Wake Time after Sleep Onset were also scored according to the standard AASM 2007 criteria. (ii) Actigraphy The majority of participants (n = 110) completed a 7-day, 24-h wrist actigraphy recording (Actigraph, GT3XP model, Pensacola, FL, USA) as a complementary means to estimate sleep duration and quality, using the same procedures followed in Phase II . Sleep-wake cycle estimation was based on epochs of movement (peaks of activity) or movement absence (relatively quiet periods of activity) using the ActLife 6 software (ActLife v6.9.5 LLC, Pensacola, FL, USA) and complemented by sleep diaries. Data were collected and averaged for the 7-day and 3-day period separately, and specific variables of interest were calculated: night and 24-h total sleep time, night and 24-h total time in bed, sleep latency and efficiency, wake time after sleep onset, and number and mean duration of night awakenings. For 104 participants, actigraphy took place simultaneously or within 24 h from PSG recording. Six participants underwent actigraphy recording within 1-4 months from PSG recording due to technical issues. 2.2.2. Inflammatory Biomarkers Single morning blood samples were collected (between 10:00 am and 12:00 pm) to assess inflammatory markers (IL-6, TNFa and C-Reactive Protein, n = 119) and plasma cortisol levels (available for116 participants). Blood samples were transferred to EDTA-containing tubes, refrigerated, centrifuged for plasma isolation and kept in deep freeze (-80 degC). Plasma TNFa and IL-6 were measured using the ELISA technique (Human TNF-alpha Quantikine HS ELISA and Human IL-6 Quantikine HS ELISA kits, R&D Systems Europe, Abington, UK). Plasma cortisol levels were measured using the ELISA technique (Cusabio Technology LLC, Texas, USA). The same procedure was followed at Phase II, rendering results comparable between the two phases . 2.2.3. Diagnosis of Neurocognitive Impairment (i) Neuropsychological assessment All participants underwent a thorough neuropsychological examination (mean duration <= 2.5 h). Domains evaluated included memory , language (naming ability: Boston Naming Test-short version and verbal fluency: the Semantic Verbal Fluency test) and attention/executive function (processing speed: Symbol Digits Modality test and visuomotor speed, task shifting and selective attention: Trails A & B). Raw scores were transformed into age and education-standardized values (based on normative values), and average z-scores on each cognitive domain were computed. Impaired performance on a given domain was considered if the average z-score was at least 1.5 SD below normative values. For the diagnosis of MCI, impaired performance in two or more tests within a given cognitive domain and intact functionality level (based on an Independent Activities of Daily Living (IADL) score > 0.78) were required. In cases of severe cognitive impairment, the MMSE test was administered instead. A Clinical Dementia Rating score was also calculated to aid cognitive status classification, especially in cases of severe cognitive impairment and significant sensory limitation. (ii) Informant scales Close relatives or caregivers were asked to complete scales measuring daily functioning (the 13-item Greek Independent Activities of Daily Living scale), current cognitive and neuropsychiatric symptoms (Cambridge Behavioral Inventory) and symptoms indicative of Lewy-body dementia (4-item Mayo Fluctuations Scale). An average IADL score < 0.78 points (range 0 to 1.00) was considered as indicative of significant functional impairment, a core criterion of severe cognitive impairment diagnosis (Dementia of any type). According to the IWG criteria, MCI diagnosis requires intact basic daily activities and relatively preserved instrumental daily functioning. Therefore, an IADL score > 0.78 points serves as a marker of adequate/preserved daily functionality in persons with mild cognitive impairment and CNI individuals. 2.2.4. Semi-Structured Interview A comprehensive medical history was taken, including the following domains that were initially assessed at baseline:- Current and past medical conditions, with emphasis on illnesses and operations occurring during the follow-up period, including Traumatic Brain Injury (TBI), stroke and pharmacotherapy (any type of treatment with a special focus on psychotropic substances). We then calculated total number of major medical morbidities (hypertension, diabetes, heart/pulmonary/hematological/liver diseases, gastrointestinal conditions, hyper/hypothyroidism, cancer, arthritis). - Mental morbidities (i.e., depression and anxiety diagnosis) were assessed according to the DSM-5 criteria, based on a clinical interview, neuropsychological evaluation, and existing diagnosis following the same procedures described previously . - Anthropometric measurements: weight, height, and Body Mass Index were assessed as previously described . - A frailty composite index was calculated based on level of physical activity, self-reported symptoms of exhaustion and decreased appetite, and objectively assessed upper limb weakness (using a dynamometer measurement). Frailty level was then recorded into 3 classes (absence of frailty, pre-frailty, frailty). - Overall subjective memory difficulties were assessed via a single question ("Do you have any memory problems?"), requiring a yes/no response, whereas domain-specific memory complaints (difficulty recalling recent information, words and names) were assessed using single questions requiring a binary response (WHICAP medical package: Medical Conditions and WHICAP survey). - Sleep problems: we used a shortened version of the Penn State Sleep Questionnaire comprising 12 items (answered on a 4-point Likert scale ranging from 0 = absence of symptoms to 3 = serious symptomatology) in order to assess presence and severity of self-reported sleep complaints, sleep duration and napping throughout the day (apnea, snoring, excessive movements during sleep, difficulty falling/staying asleep, early awakening, overall quality of sleep and, lastly, average night sleep duration and time required for falling asleep, as well as napping frequency and duration, if applicable) . - Lifestyle habits: we recorded current smoking and drinking habits (number of cigarettes if a current smoker, smoking cessation and year of quitting, as well as frequency of alcohol consumption on a daily basis). We also estimated level of physical activity during the previous week (including frequency of participation in particular activities such as gardening, housework, handiwork, shopping), as well as based on participants' responses to the question "How many days did you walk for more than 10 min in a row in a brisk manner during the last week?", as previously described in detail . - Social support and frequency of social contacts: we calculated the total number of social contacts (close relatives and friends) reported by participants during the last month, the availability of emotional and practical support, using two questions adapted from the Social Support Questionnaire-Short Form : "Is there anyone you can really count on when you need help? Is there anyone you can really count on to help you feel more relaxed when you are under pressure/stress?" and the quality of perceived support ("How satisfied are you with the level of support you receive?"), answered on a 5-point Likert scale ranging from 0 (not at all) to 4 (completely satisfied). 2.2.5. Neuropsychiatric Evaluation Self-reported symptoms of anxiety and depression were assessed using the 7-item Hamilton Depression and Anxiety Scale-Anxiety subscale (HADS-A) and the 15-item Geriatric Depression Scale (GDS), respectively. Diagnosis of depression and anxiety during Phase III followed the same procedure as in Phase II, according to the DSM-5 criteria established through a clinical interview conducted by a specially trained physician and psychologist, scores on the aforementioned scales (using 7 and 4 points as cutoffs, respectively) and prescription of psychotropic medication(antidepressants/anxiolytics or antipsychotics) . Furthermore, in Phase III, we recorded retrospectively major stressful events that occurred within the 7-year interval and calculated a new binary variable to indicate the presence of at least one major stressor in the period preceding the examination process. Major stressors included significant medical conditions (severe eyesight/hearing loss, cancer), death or illness of close relatives and finally, survival from natural disasters (there was consecutive severe and frequent earthquake activity in Crete in the time preceding Phase III assessment). Following the same procedures as in Phase II, all relevant information (cognitive performance by domain, IADL score, neuropsychiatric symptoms) was evaluated by a certified psychiatrist (M.B), neurologist (C.C.) and neuropsychologist (P.S) to reach a consensus diagnosis according to theDSM-4 and DSM-5 criteria (for Phase II and III accordingly) for the diagnosis of Major Neurocognitive Disorder and the IWG criteria for the MCI diagnosis . Dementia differential diagnosis was made on the basis of the following criteria: for the diagnosis of probable AD, vascular Dementia, Lewy Body Dementia, behavioral variant FTD and other types of Frontotemporal Dementia, the NINCDS-ADRDA, the NINDS-AIREN, the DLB Consortium, the International Consortium on behavioral variant Frontotemporal Dementia and the Neary criteria were utilized, accordingly . Diagnosis of mixed dementia was made in cases of co-occurrence of signs suggestive of both probable AD and vascular dementia . 2.3. Statistical Analysis SPSS 28.0 (IBM; 2022) was used for statistical analyses. In view of significant deviation from normality for a number of variables (as indicated by p < 0.05 on the Kolmogorov-Smirnov test), non-parametric tests (Wilcoxon signed-rank test and Mann-Whitney U test) were used to assess change over time and group differences at each Phase, respectively. The Chi square test was used to assess differences in proportions. The final sample size was sufficient to ensure 85% power for detecting small-to-medium effect size group differences at p < 0.05 and also sufficient to ensure 95% power for detecting small effect sizes of change over time at p < 0.05. 3. Results Seventy-one CNI and 80 participants previously diagnosed with MCI in Phase II were re-evaluated in Phase III at an average interval of 7.12 years (SD = 0.92). Compared to the total participant pool (all persons in the CNI and MCI groups in Phase II, n = 377), those who were followed up were younger (72.8 vs. 77.2 years, p < 0.001), more likely to be women (77.5% vs. 63.3%, p = 0.004) and less likely to live alone (p = 0.03). There was a non significant tendency for followed-up persons to have achieved more years of education (p = 0.059). The total group and followed-up subgroup were comparable in terms of geographic origin (p = 0.4), major medical morbidities (p = 0.9) and previous occupation (p = 0.1). As evident in Table 1, the majority of participants in the current cohort were rural residents (84.1%), previously occupied in domestic/agricultural work (63.6%) and having attained 6 or fewer years of formal education (92.1%). In Phase II, the two diagnostic groups (i.e., CNI, MCI) were comparable in Body Mass Index, gender ratio, lifestyle habits, previous occupation, frequency of persons living alone, overall health (as indexed by the number of current major medical morbidities), and family history of dementia (see Table 1), with the exception of age (CNI < MCI, p < 0.001) and frequency of APOE e4 carriers (CNI < MCI, p = 0.04). Moreover, the two diagnostic groups did not differ in psychiatric manifestations (severity of self-reported anxiety and depression symptoms, depression and anxiety diagnosis) or frequency of psychotropic medication use (see Table 2). In Phase III, the two groups were comparablein all variables. Occurrence of major stressors during the follow-up period was also very similar between the two groups, as was the frequency of persistent depression diagnosis (21.1 vs. 17.5% for CNI and MCI, respectively, p = 0.6). Over the follow-up period, participants in both groups reported increased anxiety symptoms (p < 0.001), although the frequency of anxiety diagnosis did not vary significantly (p = 0.6 and p = 0.2 within the CNI and MCI groups, respectively). This trend was paralleled by a concurrent increase in the use of at least one psychotropic medication, which reached significance in both groups (p < 0.001 and p = 0.005 in the CNI and MCI group, respectively). Whereas self-reported depression symptoms did not vary significantly across the two time points between CNI and MCI groups, the frequency of depression diagnosis changed significantly over time within diagnostic groups (increasing trend, statistically significant among CNI persons, p < 0.001). Alcohol use was reduced (p = 0.028 and p = 0.023 in CNI and MCI group, respectively). Finally, there was an increase in those living alone within the CNI group (p = 0.003) and in the average number of major medical morbidities in both groups (p = 0.001 and p < 0.001 in CNI and MCI groups, respectively), possibly as a result of aging. 4. Discussion In this paper, we outline the study protocol and the sociodemographic, medical and mental health characteristics of the sample of a 7-year longitudinal study on aging, aiming to identify predictors of cognitive decline in community-dwelling elderly participants. The sample derived from the CAC included persons averaging 72.9 (range: 60-89) years old at baseline who either met criteria for MCI or were cognitively intact upon initial examination. Considering the age range of participants, we achieved satisfactory response rate (55.1%) in this well-characterized, culturally homogeneous, mainly rural (84.1%), low-literacy sample (92.1% had completed <=6 years of formal education). This longitudinal study is rather unique as it involves multimodal measurements of a wide range of factors, which could act as either direct predictors of cognitive decline or as moderators of the impact of other variables on long-term cognitive status progression in this well-defined community-dwelling elderly sample. Few studies have investigated the interplay between sleep abnormalities, mental and physical comorbid disorders, inflammatory biomarkers, stress-related hormones, behavioral/psychological symptoms and domain-specific cognitive performance among persons diagnosed with different levels of cognitive and functional impairment longitudinally. Until recently, the majority of actigraphy and polysomnography studies recruited small groups of cognitively intact and MCI participants . To our knowledge, this is the first longitudinal study conducted in Greece and among few studies worldwide that uses several qualitative and quantitative measures, providing an objective, integrative assessment of sleep patterns, sleep-related disorders (Obstructive Sleep Apnea) and sleep macrostructure, as well as their interplay with cognitive performance and possible confounding factors (inflammatory and genetic biomarkers, mental and physical comorbidities, sociodemographic and lifestyle conditions)in a relatively large sample. The two diagnostic groups (CNI and MCI) were relatively similar in sociodemographic, medical and emotional conditions at baseline, including family history of dementia, except that MCI persons were older and more likely to be APOE e4 allele carriers. At follow-up, we noted a significant increase in the number of major medical morbidities, which is expected with advancing age. In terms of mental health, both groups reported increased severity of anxiety symptoms and use of psychotropic medications (anti-depressants and anxiolytics), possibly as a consequence of aging as well as the long-term and ongoing effects of two consecutive crises, namely the Greek financial crisis of 2009-2019, which resulted in further income reductions and increased unemployment, and the global pandemic crisis, which caused insecurity and exacerbated feelings of distress among Greeks . Furthermore, depression diagnosis (based on the clinical interview and antidepressant prescription criteria) was notably increased at re-evaluation, especially among cognitively non-impaired persons. It should be stressed, though, that subjectively assessed depressive symptomatology remained relatively stable between the two measurement points (as opposed to increased frequency of depression diagnosis), assumingly due to increased anti-depressant use, which led to symptom alleviation at follow-up. Depression and anxiety are frequent comorbid conditions among the elderly, and their co-occurrence increases the chance of somatic symptoms and cognitive deterioration . Development of depression and anxiety symptomatology is closely related to multimorbidity , presence of chronic illnesses, and stressful life events . The number of medical morbidities increased in Phase III, and at the same time, one out of three participants reported at least one type of major stressful event. Major stressors that trigger feelings of threat or undermine functional independence (as in the case of severe sensory loss) predict both depressive and anxiety symptoms . Given the demographic characteristics of the current population (low educational level and rural residence), lack of familiarity with the utilized techniques (actigraphy and polysomnography), the time-consuming nature of the study procedures and the lack of personal incentives (i.e., remuneration), the response rate can be considered satisfactory. Our project was delayed for 7 months due to COVID-19 pandemic restrictions, whereas excessive worrying about COVID infection during examination and/or inconsistent information about the effectiveness of protective measures against coronavirus expansion may have negatively affected the response rate. However, despite the adverse conditions and the insurmountable challenges posited by the pandemic, the Phase III response rate (51.1%) was among the highest compared to similar studies conducted in Greece and Southern Europe . Lastly, some limitations of the current protocol should be discussed. Despite the fact that all testing procedures took place in participants' homes to reduce the inconvenience of a hospital visit and to increase ecological validity, we could not control for the presence of environmental distractors during neuropsychological testing (although we opted for a distraction-free environment), fatigue or reduced compliance with the instructions pertaining to the polysomnographic process. In addition, although home PSG is a well-validated process for sleep assessment, it is associated with artifacts and data loss due to lack of continuous monitoring by overnight technical staff. 5. Conclusions The current study aimed to identify modifiable risk factors for cognitive deterioration by embracing a comprehensive, multidisciplinary approach, utilizing user-friendly techniques. This is important given the high progression rates from MCI to dementia, the urgent need for timely interventions, as well as the complex interplay between risk factors for cognitive decline. Strengths of this study include the longitudinal design, the relatively large number of MCI patients recruited, the particular socio-economic and cultural characteristics of the current sample, the long follow-up interval and methodological advantages (presence of a control group), which we expect to result in scientifically valid and clinically useful findings in terms of modifiable factors predisposing to cognitive progression among the elderly. Acknowledgments We thank study coordinator Cynthia Manassaki for her continuing support. Furthermore, we would like to thank the neurologists Ioannis Zaganas and Chrysanthi Chlapoutaki for their significant contribution to the final diagnoses in Phases II and III, respectively, the staff from the Day Center for Alzheimer's Disease "NEFELI" (Eirini Spyridaki, Maria Konsolaki, Evangelia Chnaraki, Andreas Fotopoulos), and all Primary Health Care Physicians (Fotini Anastasiou, Eirini Kalogridaki, Eleni Klouva, Evangelia Ladoukaki, Kornilia Makri, Polyvios Papadokostakis, Emmanouil Papamastorakis, Eleni Pateli, Dimitra Prokopiadou, Ioanna Stefanaki, Emmanouil Symvoulakis, Nikolaos Tsakountakis, Ioanna Tsiligianni, Theodoros Vasilopoulos, Angeliki Vassilaki) for the excellent co-operation. Last but not least, we are grateful to all individuals and their families for their participation in the study. Author Contributions Conceptualization, M.B., C.A., P.S. and A.N.V.; Data curation, E.S., C.A., A.Z., A.G. and P.S.; Formal analysis, M.B., E.S. and P.S.; Funding acquisition, M.B. and A.N.V.; Investigation, E.S., A.Z., A.G. and M.A.; Methodology, M.B., C.A., P.S. and A.N.V.; Supervision, M.B., C.A., P.S. and A.N.V.; Writing--original draft, E.S.; Writing--review & editing, M.B., E.S., C.A., P.S. and A.N.V. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The HFRI and the NSRF studies were approved by the Ethics Committee of the University of Crete (number of approval: 61/9-3-2020) and by the Bioethics Committee of the University Hospital of Heraklion, Crete (number of approval: 13541/20-11-2010), respectively. All procedures performed in the current studies involving human participants were in accordance with the 1975 Helsinki Declaration and its later amendments or comparable ethical standards. Informed Consent Statement Written informed consent was obtained from all subjects involved in the current study (also applied for Phase II of the program). Data Availability Statement Data available on request due to restrictions (privacy). The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow diagram of Phases I, II & III of the Cretan Aging Cohort study. Phases I & II were conducted within approximately six months in 2013, whereas Phase III assessments were conducted between 2020-2022. Participant diagnostic status during Phase II is also shown. Abbreviations; MMSE: Mini Mental State Examination, MCI: mild cognitive impairment, CNI: cognitively non-impaired, PSG: polysomnography. healthcare-11-00703-t001_Table 1 Table 1 Sociodemographic and medical characteristics assessed in Phase II and III for the cognitively non-impaired (CNI) and MCI participants (according to Phase II diagnosis). KERRYPNX CNI (n = 71) MCI (n = 80) MCI vs. CNI MCI vs. CNI Phase II Phase III Phase II Phase III (Phase II) (Phase III) Age (years) 70.48 (6.31) 78.32 (6.16) * 75.03 (6.34) 83.30 (6.27) + <0.001 <0.001 1 Gender (Female, (%)) 55 (77.5) 62 (77.5) 0.9 2 RuralResidence (%) 59 (83.1) 68 (85.0) 0.7 Body Mass Index 31.22 (4.22) 31.10 (5.89) 30.12 (4.55) 30.05 (5.95) 0.07 0.3 Living alone (%) 17 (23.2) 23 (32.4) * 16 (20.0) 18 (22.5) 0.6 0.2 No of Illnesses 2.55 (1.62) 3.28 (1.62) * 2.49 (1.37) 3.18 (1.50) + 0.8 0.5 Education (years) 5.49 (3.23) 4.70 (2.55) 0.06 Previous occupation (%) 0.6 Housekeeping 13 (18.3) 22 (27.5) Farmer 28 (39.4) 33 (41.2) Worker 7 (9.9) 9 (11.2) Technician 1 (1.4) 1 (1.3) Employee 11 (15.5) 6 (7.5) Self-employed 9 (12.7) 8 (10.0) Teacher 2 (2.8) 1 (1.3) Dementia Family history (%) 20 (28.2) 24 (30.0) 0.8 APOE e4 allele (%) 6 (8.5) 19 (24.4) 0.04 Smoking (%) 7 (9.9) 6 (8.6) * 3 (3.8) 2 (2.5) + 0.1 0.1 Alcohol use (%) 21 (29.6) 13 (18.8) * 35 (43.6) 16 (20.0) + 0.08 0.8 1 Mann-Whitney U test, 2 Chi square test of independence. Notes: Significant differences (p < 0.05) between the two time points within the same diagnostic group are indicated by * (CNI group) or + (MCI group). Abbreviations; CNI: cognitively non-impaired, MCI: mild cognitive impairment, APOE: Apolipoprotein E. Unless otherwise specified, values are mean (SD). healthcare-11-00703-t002_Table 2 Table 2 Mental health characteristics assessed in Phase II and III for cognitively non-impaired (CNI) and MCI participants (according to Phase II diagnosis). CNI (n = 71) MCI (n = 80) MCI vs. CNI MCI vs. CNI PhaseII Phase III PhaseII Phase III (Phase II) (Phase III) HADS-A subscale score 3.57 (3.71) 5.83 (4.28) * 2.81 (3.09) 4.79 (3.63) + 0.5 0.2 1 GDS score 3.84 (3.62) 3.59 (2.88) 3.93 (3.07) 3.58 (3.05) 0.8 0.9 Depression Diagnosis (%) 20 (28.2) 26 (36.6) * 27 (33.8) 30 (37.5) 0.5 0.9 2 Anxiety Diagnosis (%) 19 (26.8) 26 (36.6) 26 (32.5) 20 (25.0) 0.4 0.1 Psychotropic medication use (%) 3 26 (36.6) 32 (45.1) * 21 (26.3) 36 (45.6) + 0.2 0.9 Persistent Depression (%) 4 15 (21.1) 14 (17.5) 0.6 Major stressful events (%) 4 21 (29.6) 30 (37.5) 0.3 1 Mann-Whitney U test, 2 Chi square test of independence, 3 Antidepressants, anxiolytics, antipsychotics, 4 7-year interval. Notes: Significant differences (p < 0.05) between the two time points within the same diagnostic group are indicated by * (CNI group) or + (MCI group). Abbreviations; CNI: cognitively , MCI: mild cognitive impairment, HADS-A: Hamilton Anxiety & Depression Scale-Anxiety subscale, GDS: Geriatric Depression Scale. Unless otherwise specified, values are mean (SD). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Alzheimer's Disease International World Alzheimer Report Available online: (accessed on 21 September 2022) 2. Daffner K.R. Promoting Successful Cognitive Aging: A Comprehensive Review Alzheimer's Dis. 2010 19 1101 1122 10.3233/JAD-2010-1306 20308777 3. Lu Y. Liu C. Yu D. Fawkes S. Ma J. Zhang M. Li C. 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PMC10000453 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050895 diagnostics-13-00895 Case Report A Mutation in CACNA1S Is Associated with Multiple Supernumerary Cusps and Root Maldevelopment Kantaputra Piranit 12* Leelaadisorn Niramol 3 Hatsadaloi Athiwat 4 Quarto Natalina 5 Intachai Worrachet 1 Tongsima Sissades 6 Kawasaki Katsushige 7 Ohazama Atsushi 7 Ngamphiw Chumpol 6 Wiriyakijja Paswach 89 Han Dong Academic Editor 1 Center of Excellence in Medical Genetics Research, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand 2 Division of Pediatric Dentistry, Department of Orthodontics and Pediatric Dentistry, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand 3 Dental Department, Rot-et Hospital, Roi-et 45000, Thailand 4 Dental Home Clinic, Khon Kaen 40000, Thailand 5 Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA 94305, USA 6 National Biobank of Thailand, National Science and Technology Development Agency (NSTDA), Thailand Science Park, Pathum Thani 12120, Thailand 7 Division of Oral Anatomy, Faculty of Dentistry & Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8514, Japan 8 Department of Oral Medicine, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand 9 Avatar Biotechnologies for Oral Health and Healthy Longevity Research Unit, Chulalongkorn University, Bangkok 10330, Thailand * Correspondence: [email protected]; Tel.: +66-(81)-9524529 27 2 2023 3 2023 13 5 89528 1 2023 21 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Background: Enamel knots and Hertwig epithelial root sheath (HERS) regulate the growth and folding of the dental epithelium, which subsequently determines the final form of tooth crown and roots. We would like to investigate the genetic etiology of seven patients affected with unique clinical manifestations, including multiple supernumerary cusps, single prominent premolars, and single-rooted molars. Methods: Oral and radiographic examination and whole-exome or Sanger sequencing were performed in seven patients. Immunohistochemical study during early tooth development in mice was performed. Results: A heterozygous variant (c. 865A>G; p.Ile289Val) in CACNA1S was identified in all the patients, but not in an unaffected family member and control. Immunohistochemical study showed high expression of Cacna1s in the secondary enamel knot. Conclusions: This CACNA1S variant seemed to cause impaired dental epithelial folding; too much folding in the molars and less folding in the premolars; and delayed folding (invagination) of HERS, which resulted in single-rooted molars or taurodontism. Our observation suggests that the mutation in CACNA1S might disrupt calcium influx, resulting in impaired dental epithelium folding, and subsequent abnormal crown and root morphology. calcium homeostasis calcium influx enamel knot root maldevelopment supernumerary cusps single-rooted molars taurodontism terotogenic effect Genomics Thailand Research Grant of the Health Systems Research Institute (HSRI)This work was supported by the Genomics Thailand Research Grant of the Health Systems Research Institute (HSRI). pmc1. Introduction Development of a tooth requires several signaling centers and a series of developmental events. Variation in signaling pathways might have effects on tooth number and morphology . Tooth formation initiates around the 6th or 7th week of human gestation as continuous thickening of the oral ectoderm, called dental lamina or odontogenic bands, in the upper and lower jaws. This dental lamina indicates where the future teeth will form . Subsequently, dental lamina, which expresses a number of signaling centers involving transcription factors and signaling pathways, such as SHH, FGF, and BMP, regulates the invagination process of the dental epithelium . The invagination of the dental epithelium into the underlying neural crest-derived mesenchyme generates tooth placodes at specific positions, which mark the onset of tooth morphogenesis. Tooth germs are formed by the activity of sequential epithelial-mesenchymal interactions via numerous signaling pathways and go through a series of developmental stages prior to mineralization. Epithelial cells within the tooth placodes proliferate and form the bud-shaped structure surrounded by the condensed dental mesenchyme . Initially the intrinsic potential to form a tooth is the dental epithelium and subsequently switches to the underlying mesenchyme during later stages of development . The determination of tooth region, tooth type, crown morphology, and individual cusps is regulated by a large number of signaling molecules that have influence on differential tissue growth and differentiation . Each tooth is highly self-regulated. The final crown morphology is the product of pre-determined epithelial morphogenesis during the cap and bell stages and involves rapid cell proliferation precisely regulated in time and space, as well as the folding of the dental epithelium at the sites of the future tooth cusps . The primary and secondary enamel knots, which comprise non-dividing cells, are thought to direct the differential growth and subsequent folding of the inner dental epithelium. A number of FGF molecules are implicated in the control of cell proliferation around the non-dividing primary and secondary enamel knots . Ectodysplasia (Eda) has a major influence on the spatial formation of the successional signaling centers during the process of tooth formation. It controls the size of enamel knots, while a lack of Eda results in a reduction in enamel knots, abnormal enamel organ, and, subsequently, the abnormal tooth is formed. This phenotype can be rescued by the FGF10 molecule . Increased expression of Eda (increased ectodysplasin signaling) in mice results in an increased number of cusps, changes in shape and position of cusps, and subsequent increased number of teeth . The number and spatial patterning of tooth cusps are precisely regulated by the iterative activation of secondary enamel knots, which are epithelial signaling centers providing developmental information . The spatiotemporal induction of the secondary enamel knots, which are the key players in tooth cusp patterning and occlusal development, involves repeated activation and inhibition of signaling . The effects of FGF signaling on the inner dental epithelium and the areas of non-dividing cells of secondary enamel knots play roles in folding of the inner dental epithelium, leading to tooth cusp formation and subsequent occlusal development . The formation of tooth cusps within a single tooth can be explained by a patterning cascade model, the product of activating and inhibiting activity in sculpturing occlusal morphology . The dental epithelium determines the cusp size and shape, and the dental mesenchyme determines the tooth size. Therefore, the final number of tooth cusps depends on the sizes of the tooth and the previously formed cusps . The morphology and size of the later developing cusps are dependent on the position and size of the earlier forming ones . In general, an increase in morphological complexity is apparent throughout evolution . However, teeth in patients with genetic mutations or mutant or transgenic mice generally have simpler tooth morphology or less dental complexity . Interestingly, a unique set of dental anomalies, including molars with multiple supernumerary cusps, single-cusped premolars, taurodontism, single-rooted molars, and tooth agenesis, has been reported in patients with a heterozygous missense variant (c. 865A>G; p.Ile289Val) in Calcium Channel voltage-dependent, L-type, Alpha-1S subunit (CACNA1S; MIM 114208) . It is interesting to note that every reported patient with that variant had molars with multiple supernumerary cusps, single-rooted molars, or taurodontism. CACNA1S encodes the pore-forming subunit of the dihydropyridine (DHP) channel. These findings suggest the mutation in CACNA1S led to an impairment in calcium influx, abnormal calcium homeostasis, and resulted in teeth with abnormal cusp and root formation. Thus, crown morphology may reflect the morphology of roots. Here, we report seven new patients from three unrelated Thai families affected with multiple supernumerary cusps, single-cusped premolars, single-rooted molars, taurodontism, and tooth agenesis. Whole-exome and Sanger sequencing identified a heterozygous variant in CACNA1S. Molecular findings and gene expression study suggest that the basic pathogenetic mechanism of molars with multiple supernumerary cusps and single roots involves disruptive folding of the dental epithelium as a result of abnormal calcium homeostasis. 2. Case Presentation We recruited patients for genetic study. The inclusion criteria were patients with multiple supernumerary cusps, round-shaped occlusal surface molars, molars with multiple supernumerary cusps, premolars with single prominent cusp, single-rooted or taurodontic molars, and tooth agenesis. Exclusion criteria were patients with normal teeth with no multiple supernumerary cusps or single-rooted molars. 2.1. Patients Patients 1-7 were from three unrelated Thai families . Patients 2 and 7 had mixed dentition; the remaining five patients were in permanent dentition. All patients share similar dental phenotypes, including round-shaped occlusal surface molars, molars with multiple supernumerary cusps, premolars with single prominent cusp, single-rooted or taurodontic molars, and tooth agenesis. Prominent middle mamelon of the mandibular lateral permanent incisors was observed in patient 2 . 2.2. Whole-Exome and Sanger Sequencing and Bioinformatic Analysis Genomic DNA was isolated from saliva using Oragene-DNA (OG-500) Kit (DNA Genotek, CANADA). Using the targeted capture kit, SureSelect V6 (PR7000-0152; Agilent Technologies, CA, USA), whole-exome sequencing (WES) of an affected father (patient 1) and his affected daughter (patient 2) from family 1 was carried out Macrogen Inc. (Seoul, Korea) provided the WES service with 80% coverage of the exonic target regions guaranteed at 30x depth. The germline variant discoveries were predicted by using Genomics analysis toolkit (GATK) version 3.8.1. The alignment of the raw sequencing data, FASTQ files, to the reference sequence GRCh37v1.6 was carried out using BWA-mem. The functional annotations of these variants were identified by the Variant Effect Predictor (VEP) tool build 102 with the additional plugin and the database of nonsynonymous functional prediction (dbNSFP) version 4.1a. Then, pathogenic variants were prioritized according to inheritance model, functional annotation. Rare variants of interest were identified by standard variant filtering pipelines (allele frequencies < 0.0001), the algorithm Combined Annotation Dependent Depletion (CADD) with scores > 15. Furthermore, variant allele frequencies were determined by comparing against public databases, including gnomAD, 1000G, GenomeAsia, and the Thai Reference Exome database (T-Rex). Once the variant in CACNA1S (NM_000069.2; NP_000060.2) was identified from patients 1 and 2, Sanger sequencing for this variant was performed in patients 3-7 and the unaffected family members (if available), in order to identify if the affected patients had the same variant. The forward and reverse primers for Sanger sequencing (sense: 5'-GGGGATTTCCCCATAGGATGC-3' and antisense: 5'-TACACCTTTCCTCCTGTCGT-3') for exon 6 of CACNA1S gene were used to amplify the target. The sequence analysis software, Sequencher 4.8 (Genecodes, Ann Arbor, MI, USA) was used to identify the presence of variants and co-segregation between genotype and phenotype within the families. Molecular Findings of Patients Whole-exome or Sanger sequencing showed a heterozygous missense variant c. 865A>G; p.Ile289Val in CACNA1S in patients 1-7. It was not found in the normal control and the unaffected family member (I-2; family 2) . This variant was previously reported in unrelated Thai patients in the original report . The amino acid residue 289Ile is highly conserved in vertebrates . According to gnomAD, the allele frequency is 0.00003185. It is not reported in South Asian and East Asian populations. This variant was not found in our in-house exome database of 1016 people with different phenotypes. 2.3. Immunohistochemistry of Cacna1s during Early Tooth Development All animal experiments were reviewed and approved by the Niigata University Institutional Animal Care and Use Committee (approval number SA00610, SD01308). CD-1-strain mice were used in this study. Embryo heads were fixed in 4% buffered paraformaldehyde, wax embedded in paraffin, and serially sectioned at 7 mm. Paraffin sections were incubated with the antibodies against CACNA1S (ThermoFisher, Waltham, MA, USA; MA3-920, 1:100). The tyramide signal amplification system (Parkin Elmer Life Science, Waltham, MA, USA) with biotinylated horse antibodies (Vector, BA-2001, 1:100) was used for detecting the CACNA1S antibody. As a negative control, normal mouse serum was used instead of primary antibody. Cacna1s Expression Cacna1s expression was observed in the secondary enamel knot, which regulates cusp formation, while it could not be found in other parts of the tooth epithelium . Cacna1s was expressed in the caudal part of the dental papillae, but not in the cranial part. No expression of Cacna1s was observed in the stellate reticulum. Cacna1s was strongly expressed in mesenchyme at the collar region of the tooth germ. 3. Discussion We identified a heterozygous missense variant c. 865A>G; p.Ile289Val in CACNA1S in seven affected patients, but not in the unaffected family member and control, suggestive of co-segregation of the genotype and phenotype. Dental anomalies caused by the heterozygous variant p.Ile289Val in CACNA1S appear to be inherited as an autosomal-dominant inheritance with complete penetrance. This variant has been reported once in Thai patients affected with similar dental anomalies . CACNA1S encodes the pore-forming subunit of the dihydropyridine channel. The variant is located in the first pore-forming intramembrane domain between segment 5 and segment 6 of transmembrane domain 3, close to the three amino acid residues involved in calcium selectivity . Therefore, the dental anomalies were likely the results of abnormal calcium selectivity and subsequent disruptive calcium homeostasis. Tooth is formed by a sequence of epithelial-mesenchymal interactions of dental epithelium and neural crest-derived mesenchyme. Developing tooth germs go through a number of developmental stages prior to mineralization. The development of tooth shape requires the spatial and temporal control of the primary and secondary enamel knot signaling centers, the non-proliferative signaling centers . Each tooth is considered to be highly self-regulated. The number and patterning of cusps are determined by the iterative activation of secondary enamel knots, which provide positional information via inductive interaction between the dental epithelium and the underlying mesenchymal cells . Enamel knots regulate the growth and folding of the inner dental epithelium, which subsequently determines the final form and size of the tooth crown . Differential growth and folding of the dental epithelium determine size and cusp patterns. The apoptotic mechanism also plays an additional role in sculpturing the final shape and size of cusps . The cusp number is regulated by the sizes of the teeth and cusps . The activation and inhibition of signaling from enamel knots result in differential growth and folding of the dental epithelium within the tooth germ, and subsequently determine the cusp patterns and dimensions . The transition from the bud to the cap stage is important because most of the tooth morphology is already determined at this stage . Once teeth are completely formed, each tooth anatomically has its own identity . Having multiple supernumerary cusps in the molars in our patients implies that supernumerary secondary enamel knots were additionally formed as a result of the CACNA1S variant. High expression of Cacna1s at the secondary enamel knot in developing mouse molars in our study supports the role of CACNA1S in cusp formation . Since tooth cusps and separation of developing roots are a result of physiological folding of Hertwig epithelial root sheath, a dental epithelium . Therefore, the dental malformations, including abnormal cusps, single-rooted molar, and taurodontism seen in our patients highlight the importance of proper calcium homeostasis in folding the dental epithelium. The final shape of tooth crown depends on the number of secondary enamel knots and where they are located within the tooth germ. The shape of molars is determined by number, shape, and sizes of the cusps . The round-shaped molars in our patients were likely the consequence of having so many supernumerary cusps because developmentally, cusps are formed first, and the formation process spreads centrifugally towards the apical end of the tooth. The supernumerary cusps in the molars in our patients appear smaller than the normal cusps. This was likely the consequence of having so many cusps on the limited occlusal surface area and the positions and proportions of the earlier developing cusps have great influence on the later developing ones within the same molar tooth . In other words, cusp size dictates the cusp number, and the number of cusps is determined by tooth size . The development of the single-cusped premolars in the patients might imitate that of ball python or bearded dragon, as their inner dental epithelium does not undergo folding; therefore, a tooth with a single prominent cusp is formed . The CACNAS variant seems to cause impaired dental epithelial folding; too much folding in the molars and less folding in the premolars; and delayed folding (invagination) of Hertwig epithelial root sheath, which resulted in single-rooted molars or taurodontism. Apparently, the dental epithelium functions differently when it forms the crown or the root, depending on its intrinsic factors. Evidently, the consequences of the altered CACNA1S are different between incisors, premolars, and molars, suggestive of differential regulatory roles of CACNA1S in different teeth. Since calcium influx appears to have an influence on tooth morphogenesis, it is suggested that the study of the effects of calcium channel blockers taken during pregnancy on developing teeth should be performed. Pathologies, such as the presence of multiple supernumerary cusps or reawakening of the potential to form more cusps, can be linked with Evo-Devo to elucidate a better understanding of how tooth structures, especially tooth cusps, form during development and through evolution . 4. Conclusions In conclusion, the genetic variant (c. 865A>G; p.Ile289Val) in the CACNA1S gene is associated with abnormal crown and root morphology. Our observation suggests that crown morphology may be able to predict root morphology. Therefore, patients with atypical crown morphology should be referred for radiographs to assess root shape. Acknowledgments We thank our patients and their families for their kind cooperation and for allowing us to use their medical and dental information for the benefit of other patients. Author Contributions Conceptualization, P.K., N.L., A.H., N.Q., W.I., S.T., K.K., A.O., C.N. and P.W.; methodology, P.K., N.L., A.H., W.I., S.T., K.K., A.O., C.N. and P.W.; validation, P.K., N.L., A.H., W.I., S.T., K.K., A.O., C.N. and P.W.; formal analysis, P.K., A.H., W.I., S.T., K.K., A.O., C.N. and P.W.; investigation, P.K., N.L., A.H., W.I., S.T., K.K., A.O., C.N. and P.W.; resources, P.K.; data curation, P.K., N.L., A.H., N.Q., W.I., S.T., K.K., A.O., C.N. and P.W.; writing--original draft preparation, P.K., N.L., A.H., N.Q., W.I., S.T., K.K., A.O., C.N. and P.W.; writing--review and editing, P.K., N.L., A.H., N.Q., W.I., S.T., K.K., A.O., C.N. and P.W.; supervision, P.K.; project administration, P.K.; funding acquisition, P.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the Human Experimentation Committee of the Faculty of Dentistry, Chiang Mai University (no. 71/2020), and was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from participants or parents. Informed Consent Statement Written informed consent was obtained from the patients to publish this paper. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A-E) Family 1. (A) Pedigree of family 1. Patients 1 and 2. (B-D) Patient 1. Permanent dentition. Round-shaped permanent molars, molars with multiple supernumerary cusps, premolars with single prominent cusps, torus palatinus (arrow in B), and torus mandibularis (arrows in C). Close-up view of mandibular premolars with single prominent cusps. (E) Panoramic radiograph showing agenesis of the right permanent mandibular third molar, single-rooted permanent molars, and taurodontism (arrows). Figure 2 Patient 2. (A-E) Mixed dentition. (A-C) Round-shaped primary and permanent molars with multiple supernumerary cusps. (D) Prominent medial mamelon of the mandibular lateral permanent incisors (arrows). (E) Panoramic radiograph showing agenesis of all third permanent molars, single-rooted primary and permanent molars, and taurodontism. Figure 3 Family 2. (A) Pedigree of family 2. Patients 3 and 4. (B,C) Patient 3 and (D,E) Patient 4. Both are in permanent dentition. Round-shaped permanent molars, molars with multiple supernumerary cusps, and premolars with single prominent cusps. Figure 4 Family 3. (A) Pedigree of family 3. Patients 5-7. (B,C) Patient 5. Permanent dentition. Round-shaped permanent molars, molars with multiple supernumerary cusps, and premolars with single prominent cusps. (D) Patient 5. Panoramic radiograph showing agenesis of all third permanent molars (blue stars), single-rooted permanent molars, and taurodontism (yellow asterisks). Figure 5 Patient 6. (A-C) Patient 6. (A,B) Permanent dentition. Round-shaped permanent molars, molars with multiple supernumerary cusps, and premolars with single prominent cusps. (C) Panoramic radiograph showing agenesis of second and third permanent molars (blue stars) and single-rooted permanent molars (yellow asterisks). Note severe taurodontism (yellow arrow). Figure 6 Patient 7 in mixed dentition. (A,B) Round-shaped permanent molars and molars with multiple supernumerary cusps. (C) Panoramic radiograph showing agenesis of second and third permanent molars (blue stars) and single-rooted primary and permanent molars (yellow asterisks). Figure 7 Sequence chromatograms of patients 1-7, the unaffected II-2 of family 2, and a control. The single base substitution from A to G at nucleotide 865 in CACNA1S gene is predicted to cause a change in amino acid isoleucine (Ile) to valine (Val) at amino acid residue 289 (c.865A>G; p.Ile289Val). Figure 8 Frontal section showing immunohistochemistry of Cacna1S in wild-type mouse at day 17.5 (B). Negative control (A). Arrow in B indicates Cacna1s expression at the secondary enamel knot. Scale bar: 100 mm. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Zhang H. Gong X. Xu X. Wang X. Sun Y. Tooth number abnormality: From bench to bedside Int. J. Oral Sci. 2023 15 5 10.1038/s41368-022-00208-x 36604408 2. Hovorakova M. Zahradnicek O. Bartos M. 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PMC10000454 | Introduction: Stereotactic ablative body radiotherapy (SABR) offers patients with stage I non-small-cell lung cancer (NSCLC) a safe, effective radical therapy option. The impact of introducing SABR at a Scottish regional cancer centre was studied. Methods: The Edinburgh Cancer Centre Lung Cancer Database was assessed. Treatment patterns and outcomes were compared across treatment groups (no radical therapy (NRT), conventional radical radiotherapy (CRRT), SABR and surgery) and across three time periods reflecting the availability of SABR (A, January 2012/2013 (pre-SABR); B, 2014/2016 (introduction of SABR); C, 2017/2019, (SABR established)). Results: 1143 patients with stage I NSCLC were identified. Treatment was NRT in 361 (32%), CRRT in 182 (16%), SABR in 132 (12%) and surgery in 468 (41%) patients. Age, performance status, and comorbidities correlated with treatment choice. The median survival increased from 32.5 months in time period A to 38.8 months in period B to 48.8 months in time period C. The greatest improvement in survival was seen in patients treated with surgery between time periods A and C (HR 0.69 (95% CI 0.56-0.86), p < 0.001). The proportion of patients receiving a radical therapy rose between time periods A and C in younger (age <= 65, 65-74 and 75-84 years), fitter (PS 0 and 1), and less comorbid patients (CCI 0 and 1-2), but fell in other patient groups. Conclusions: The introduction and establishment of SABR for stage I NSCLC has improved survival outcomes in Southeast Scotland. Increasing SABR utilisation appears to have enhanced the selection of surgical patients and increased the proportion of patients receiving a radical therapy. non small-cell lung cancer stage I stereotactic ablative radiotherapy real-world clinical data This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. pmc1. Introduction Lung cancer is the leading cause of cancer death in Scotland, accounting for one in five cancer deaths . Non-small-cell lung cancer (NSCLC) represents approximately 85% of all cases . In Scotland, approximately 20% of patients present with stage I disease, typified by small (<4 cm) localised disease without spread to lymph nodes or distant organs . Surgical resection, involving lobectomy with mediastinal lymph node dissection or sampling, has been the curative treatment of choice for stage I NSCLC. However, many patients with lung cancer are burdened by multiple co-morbidities, including chronic obstructive pulmonary disease (COPD) or cardiovascular disease, which make them less suitable for surgery . Non-surgical treatment options such as conventional fractionated radical radiotherapy (CRRT) may also be used with radical intent. However, historically, outcomes are poorer than those achieved by surgery . More recently, stereotactic ablative body radiotherapy (SABR) has become the treatment of choice in patients who are unfit for surgery or decline resection . SABR is a well-tolerated and effective treatment in these patients . Registry data suggest SABR improves survival when compared to best supportive care . When compared to standard CRRT, SABR is more convenient for patients, has no minimum threshold for respiratory function, fewer side effects, a higher local control rate and is likely to have a survival benefit . Unfortunately, randomised controlled trials of SABR vs. surgery have struggled to recruit, largely due to patient preference for radiotherapy over surgery or vice versa . However, in younger, fitter patients, surgical resection would be considered the standard of care . For patients who are potentially operable, SABR and surgery outcomes appear to be similar in the limited trial data available . This suggests SABR is a reasonable alternative to surgery in those who decline an operation, or in those who have a higher risk of surgical complications. A key benefit of SABR is that it increases the pool of patients who could receive an effective radical treatment . In a previous observational cohort study, the use of SABR increased the proportion of older patients, at the highest risk of surgical complications, who received a radical treatment . Consequently, the average survival of the whole cohort increased. The aim of this study was to understand the impact of SABR on outcomes for stage I NSCLC at a regional cancer centre in the United Kingdom (UK). We demonstrate the positive effect of the introduction of SABR as a treatment option for stage I NSCLC in a real-world setting. We present novel data demonstrating the impact of clinical factors on treatment selection and outcomes. Interestingly, we find that the availability of an alternative low-toxicity treatment to surgery appears to affect the selection of surgical patients, leading to improved surgical outcomes. 2. Methods All NHS Lothian patients discussed in the Southeast Scotland Cancer Network (SCAN) lung-cancer multidisciplinary meeting between January 2012 and December 2019, diagnosed clinically with a stage I NSCLC, were identified . Patients with multiple synchronous or metachronous primary lung cancers were excluded. Patients upstaged at surgery were included in analyses based on an intention to treat as stage I NSCLC. Data were extracted from the Edinburgh Cancer Centre Lung Cancer Database, containing detailed clinical information for all patients with lung cancer across SCAN since 2012. Patient characteristics, including age, Eastern Cooperative Group Performance Status (PS) and Charlson Comorbidity Index (CCI) at the time of diagnosis of stage I NSCLC and treatment modality were recorded . CCI was calculated using hospital admission data obtained from the Scottish Morbidity Records dataset . CCI was grouped by no comorbidity (CCI 0), mild/moderate comorbidity (CCI 1-2) or significant comorbidity (CCI >= 3). Radical radiotherapy treatment status was defined as: CRRT--55 Gy in 20 fractions as fractionated dose; SABR--54 Gy in 3 fractions, 55 GY in 5 fractions or 60 Gy in 8 fractions. This is in keeping with previously reports . Three distinct time periods were studied reflecting the availability of treatment options within SCAN: A--January 2012-December 2013 (pre-SABR); B--January 2014-December 2016 (introduction of SABR); C--January 2017-December 2019, (SABR established). The overall survival, defined as the number of months from the date of diagnosis of stage I NSCLC and death, or censorship if still alive at follow-up (1 November 2021), was calculated. Survival curves were plotted using Kaplan Meier methods, and the log rank test applied. Survival analysis was carried out using Cox's proportional-hazards model, and hazard ratios were calculated. Differences in treatment groups and time periods were compared using t-tests for continuous variables and chi-square tests for categorical variables as appropriate. A p-value < 0.05 was considered significant throughout. All analyses were performed in SPSS version 27.0 (SPSS Inc). 3. Results Patient Characteristics: 1143 patients meeting the inclusion criteria were identified. Patient characteristics were in keeping with reported real-world populations of stage I NSCLC (Table 1). A total of 41 (9%) patients treated with surgery were upstaged. Analyses of all patients diagnosed with NSCLC within NHS Lothian during the study time periods demonstrated no evidence of stage migration (Supplemental Table S1). The median age was 74 (interquartile range (IQR) 68-81) and 55% were female. Median OS was 41.6 (interquartile range (IQR) 15.4-95.8) months. A total of 407 (36%) patients were censored in whom minimum and median follow-up was 26.9 and 58.4 months, respectively. Age (<=65, 65-74, 75-84, >=85 years old), PS (0, 1, 2, 3+) and CCI (0, 1-2, 3) were independently associated with survival (each log-rank p < 0.001). Surgery was the most frequently employed treatment modality (41%). Age, PS and comorbidities were important factors for treatment choice . Patients treated with surgery were younger (median age 70 (IQR 63-75) vs. 78 (IQR 72-84), p < 0.001), of better PS (PS0/1 86% vs. 50%, p < 0.001) and less comorbid (CCI 0 54% vs. 45%, p < 0.001) than all other patients. A total of 82% of patients aged <=65 and PS0 were treated surgically, whilst 74% of those aged >=85 and PS2+ received no radical treatment . Outcomes by Treatment Modality: As expected, patients with no radical treatment had the poorest survival (13.5 (IQR 5.3-30.3)) . Outcomes for patients treated with surgery (92.3 (IQR 40.6--not reached)) were more favourable than those treated with SABR (65.3 (IQR 29.1-85.3), which were more favourable than those treated with CRRT (37.1 (IQR 18.5-59.6)) (p < 0.001 and p < 0.001, respectively). Outcomes by Time Period: Survival estimates by time period for all patients, and for each treatment subgroup, are shown in Figure 2 (Supplemental Table S3). Patients in time period C had more favourable survival than those in time period A (HR 0.85 (95% confidence interval (CI) 0.77-0.94)), with median survival improving from 32.5 (IQR 13.0-74.8) months to 48.8 (15.3-95.8) months (p = 0.006) (Supplemental Table S4). The greatest improvement in survival was seen in patients treated with surgery between time periods A and C (HR 0.69 (95% CI 0.56-0.86), p < 0.001). The survival of patients treated with any radical radiotherapy (i.e., CRRT or SABR) improved between time periods A and B (HR0.70 (95% CI 0.49-0.99), p = 0.045) and between time periods A and C (HR0.75 (95% CI 0.61-0.91), p = 0.004). Patient selection with increasing availability of SABR: Changes in treatment patterns were observed across time periods . The proportion of patients who received no radical therapy fell from 33% to 30% amongst all patients, and from 52% to 46% in the elderly (>=75 years old) population . SABR use rose from 11% to 18% between time periods B and C in all patients, offset by stepwise reductions in the use of CRRT and surgery. Changes in treatment patterns were observed between time periods by age group, PS and CCI . The proportion of patients receiving a radical therapy rose between time periods A and C in younger (age <= 65, 65-74 and 75-84 years), fitter (PS 0 and 1) and less comorbid patients (CCI 0 and 1-2). In each of these patient cohorts, the use of CRRT and surgery fell between time periods A and C, with SABR increasingly utilised between time periods B and C. In older (aged >= 85 years), less fit (PS 2) and more comorbid patients (CCI >= 3) fewer patients received a radical therapy in time period C than time period A. In each of these patient groups, the use of CRRT and surgery also fell between time periods A and C. There were no statistically significant differences in patient characteristics for each treatment group between time periods (p > 0.05). 4. Discussion Our real-world data demonstrate an increase in the proportion of patients with stage I NSCLC receiving a radical therapy between 2012 and 2019. The median overall survival of the study population increased by 16.3 months between time periods A and C, with the most significant improvement was seen in patients undergoing surgical management of their cancer. These changes correlated with the introduction and establishment of SABR as a standard treatment option at the Edinburgh Cancer Centre. This is the first time this has been demonstrated in a UK population. Our findings largely reflect those previously demonstrated in a Dutch population-based study, which found that the introduction of SABR correlated with a decline in the number of untreated elderly patients with stage I NSCLC, corresponding to an 8-month improvement in median overall survival . A key clinical challenge is to improve radical treatment rates for patients with stage I NSCLC. In a 2015/16 Cancer Registry analysis, rates of no radical therapy were 26% in England, 13% in Norway and 9% in the Netherlands . Significantly, in that study, only 8% of patients in England were treated with SABR, compared to 26% in Norway and 27% in the Netherlands, reflecting the slower establishment of SABR in the UK. Our rates of SABR remain lower than this (18%), despite SABR now being an established treatment. Previous studies examining the impact of SABR on the management of stage I NSCLC have lacked recognised clinical prognostic factors such as PS and detailed comorbidity data . We find that age, PS and comorbidity burden, as measured by the CCI, are associated with overall survival outcomes in this population. We present novel data demonstrating that treatment patterns strongly correlated with these factors. For example, surgical rates were lower with increasing age, whilst any radical radiotherapy (CRRT or SABR) use became more frequent. Significantly, the commonest treatment for patients >=75 years in our study was no treatment (49%), whereas 85% of those <75 years received a radical therapy. We add to this by demonstrating that patients with poor PS or significant comorbidities are also less likely to be treated radically. In particular, these patients are less frequently treated with surgery. Pre-existing respiratory comorbidities, such as COPD, may increase the risk of post-operative complications, limit the extent of lung that can be safely removed and are associated with poorer outcomes in stage I NSCLC . We also note that between time periods A and C, rates of radical therapy increased by only 3% in the overall population and 6% in patients >=75 years old. This is lower than that seen in a previous real-world observational study . Given that patients in the NRT cohort were older, less fit and more comorbid, we suspect that many had incidental lesions identified but were not fit for further investigation and management. Our institution has no thresholds for minimum lung function for SABR and, broadly, if a patient tolerates PET-CT they are likely to tolerate the delivery of SABR. Indeed, only 2% of patients in the NRT received any direct cancer palliative therapy, including high-dose palliative radiotherapy. This suggests that, in addition to the availability of new treatments, strategies to improve patient fitness or the early detection of cancer are needed to improve radical treatment rates. In our clinical practice, surgery remains the treatment of choice for patients with stage I NSCLC. That patients treated with surgery in our cohort had significantly better survival than those treated with any radical radiotherapy likely reflects differences in treatment selection. SABR offers an alternative treatment option for patients with high surgical risk and technically and medically inoperable disease. Specifically, it is associated with lower 30-day mortality than surgery in patients with severe COPD, but offers similar survival benefit . It is also proven to be a better treatment than CRRT (the only other pre-existing non-surgical radical treatment option) with fewer side effects, higher rates of local control and a likely survival benefit . It appears to be well tolerated in older, frailer patients . It is, therefore, not surprising to find that SABR use increased at the expense of CRRT and surgery in these patient groups. Indeed, rates of any radical therapy fell in these patient groups, but increased in younger, fitter or less comorbid patient groups. Although this may reflect a better selection of patients for radical therapy, which may have contributed to better survival between time periods A and C, we suggest these changes were driven by the introduction of SABR for the treatment of stage I NSCLC. For example, we demonstrate that the introduction of SABR correlated most strongly with a survival improvement for patients treated with surgery. A potential confounder to these findings is the improvement in surgical techniques and perioperative care during the study time periods. However, the most significant reductions in surgical rates between time periods A and C were seen in patients aged >= 85 years (5% vs. 0%), PS 2 (28% vs. 18%) and CCI >= 3 (24% vs. 7%). This likely reflects the availability of an additional efficacious treatment option and highlights that an important real-world impact of SABR has been to facilitate better selection of patients for surgery. This effect of improving outcomes by the migration of the poorer outcome patients into a different group is recognised in the staging of cancer and is known as the Will Rogers effect, first described in 1985 . This has not previously been described for the surgical treatment of NSCLC. Although survival improved between time periods A and C for patients treated with any radical radiotherapy, there was no significant change for patients treated with CRRT, suggesting this improvement was driven by treatment with SABR. CRRT and surgical rates fell in all other patient characteristic subgroups between time periods A and C, with SABR utilised in each. This suggests that SABR has an important role to play in younger, fitter patients too. Use of SABR instead of CRRT in these subgroups may reflect the availability of a better treatment option than CRRT, particularly where surgery is not possible for technical reasons. It is also recognised that patients, when offered the choice, frequently opt for SABR over surgery . Significantly, amongst treated patients, SABR was the most frequently applied radical therapy in those with mild functional limitations (i.e., PS1) and mild/moderate comorbidities (CCI 1-2) (45% and 40%, respectively), where the clinical assessment of suitability for surgery is less clearcut between operable and inoperable. There is longstanding debate around the role of SABR in potentially operable patients, particularly as many of these patients are older or more comorbid . The positive real-world effects of the introduction of SABR identified by our study provides some evidence to fill the void left by the lacking clinical trials data in these patients. Our findings may become more important if computed tomography-based lung-cancer screening is introduced into routine clinical practice. The NELSON trial showed an overall survival benefit in the screened population compared to a control group (HR0.76 (95% CI 0.61-0.94), p = 0.01) . Significantly, there was a large increase in the proportion of patients presenting with stage I NSCLC (58.6% vs. 14.2%, respectively), suggesting the absolute number of patients with stage I NSCLC being considered for radical therapy may well increase if screening is introduced. A better understanding of factors important for treatment selection and outcomes, as explored in this study, will aid service provision. Several limitations for this study are acknowledged. As a single-centre study, it benefits from standardised, comprehensive data collection of all patients with NSCLC, although some information on performance status and comorbidities was not available. The experience of the SCAN lung-cancer multidisciplinary team may have given rise to confounders in patient clinical selection for specific therapies. However, we observe differences in treatment selection through time, suggesting these are not inherent. Like other studies in this area, we have included patients without pathological confirmation, potentially including cases of benign disease, or isolated pulmonary metastases from another cancer. Our clinical practice, however, routinely includes the use of the Herder score and patients are staged with PET-CT imaging in line with UK guidelines . In a previous study, 46% of all English patients with stage I NSCLC were treated with CRRT without histology, compared to 52% in our study . 5. Conclusions This comprehensive study demonstrates how the introduction and establishment of SABR for stage I NSCLC has improved treatment rates and survival outcomes of patients in Southeast Scotland. We highlight recognised clinical prognostic factors that are key for patient treatment selection, which are absent from other similar studies. It is of particular significance that increasing SABR provision appears to have enhanced the selection of surgical patients, amongst whom survival outcomes are most improved. These findings support those of previous studies, suggesting the effects may be seen more broadly. SABR is now routinely available elsewhere, including at all five Scottish radiotherapy centres. Acknowledgments Public Health Scotland Cancer Quality Performance Indicators Cancer Audit Service, Southeast Scotland Cancer Network (Lung Cancer). Supplementary Materials The following supporting information can be downloaded at: Figure S1: Overall survival of patients with stage I NSCLC by A: Age, B: Performance Status, C: Charlson Comorbidity Index; Figure S2: Treatment utilisation for all patients with stage I NSCLC by A: Age, B: Performance Status, C: Charlson Comorbidity Index; Figure S3: Treatment choice matrix by age and performance status for all patients with stage I NSCLC; Figure S4: Treatment utilisation for all patients aged 75 years and over with stage I NSCLC by time period; Table S1: Stage distribution of patients with NSCLC in NHS Lothian during the three study time periods (A: 2012-2103, Pre-SABR, B: 2104-2106, Introduction of SABR, C: 2017-2019, SABR Established); Table S2: Life table for overall survival of all patients with stage I NSCLC by treatment modality. ; Table S3: Life tables for overall survival estimates for all patients with stage I NSCLC, and for each treatment group, by treatment time period, A: All patients, B: No radical therapy, C: Conventional Radical Radiotherapy, D: SABR, E: Any Radical Radiotherapy, F: Surgery. ; Table S4: Overall survival estimates for all patients with stage I NSCLC, and for each treatment group, by treatment time period (A: 2012-2103, Pre-SABR, B: 2104-2106, Introduction of SABR, C: 2017-2019, SABR Established). Click here for additional data file. Author Contributions M.S. and I.P. conceived the idea. M.S., I.P. and P.H. developed the research methodology. M.S., G.L., M.V., A.K., G.T., A.P. and the Edinburgh Cancer Informatics Programme conducted the primary data collection. I.P., M.M, S.H., C.B., K.M., S.C., T.E. and A.T. provided study resources. M.S., G.L., M.V. and G.T. were responsible for data cleaning. M.S. and G.L. analysed the data. M.S., G.L. and I.P. prepared the draft manuscript. M.M. and S.H. provided significant intellectual input and advice in the re-draft of the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement No patient identifiable data were used, the presented work was undertaken in accordance with guidelines from the Academic and Clinical Central Office for Research and Development (ACCORD) (NHS Lothian and University of Edinburgh) and study-specific consent was not required. Informed Consent Statement No patient identifiable data were used, the presented work was undertaken in accordance with guidelines from the Academic and Clinical Central Office for Research and Development (ACCORD) (NHS Lothian and University of Edinburgh) and study-specific consent was not required. Data Availability Statement Research data are available on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Overall survival for all patients with stage I NSCLC by treatment modality. Figure 2 Overall survival estimates for all patients with stage I NSCLC, and for each treatment group, by treatment time period, (A) All patients, (B) No radical therapy, (C) Conventional radical radiotherapy, (D) SABR, (E) Any radical radiotherapy (CRRT or SABR), (F) Surgery. Log-rank regression. Figure 3 Treatment utilisation for all patients with stage I NSCLC by time period. (A: 2012-2103, Pre-SABR, B: 2104-2106, Introduction of SABR, C: 2017-2019, SABR Established). Figure 4 Treatment utilisation for all patients with stage I NSCLC by time period and A: age, B: performance status, C: Charlson comorbidity index subgroups. (A: 2012-2103, Pre-SABR, B: 2104-2106, Introduction of SABR, C: 2017-2019, SABR Established). cancers-15-01431-t001_Table 1 Table 1 Patient characteristics of patients with stage I NSCLC. (NR--not reached). Patient Characteristics All No Radical Treatment Radical Radiotherapy Stereotactic Ablative Body Radiotherapy Surgery n = 1143 n = 361 n = 182 n = 132 n = 468 Age <=64 200 (17) 21 (6) 23 (13) 17 (13) 139 (30) 65-74 372 (33) 66 (18) 60 (33) 44 (33) 202 (43) 75-84 411 (36) 154 (43) 75 (41) 58 (44) 124 (26) >=85 160 (14) 120 (33) 24 (13) 13 (10) 3 (1) Median (IQR) 74 (68-81) 82 (75-87) 76 (70-81) 75 (69-81) 70 (63-75) Sex Female 628 (55) 200 (55) 95 (52) 75 (57) 258 (55) Male 515 (45) 161 (45) 87 (48) 57 (43) 210 (45) ECOG Performance Status 0 244 (21) 51 (14) 21 (12) 22 (17) 150 (32) 1 435 (38) 87 (24) 95 (52) 61 (46) 192 (41) 2 225 (20) 66 (18) 54 (30) 42 (32) 63 (14) 3+ 76 (7) 76 (21) 0 (0) 0 (0) 0 (0) Unknown 163 (14) 81 (22) 12 (7) 7 (5) 63 (14) Charlson Comorbidity Index 0 564 (49) 113 (31) 80 (44) 64 (48) 307 (66) 1-2 301 (26) 114 (32) 60 (33) 44 (33) 83 (18) >=3 103 (9) 62 (17) 19 (10) 10 (8) 12 (3) Unknown 175 (15) 72 (20) 23 (13) 14 (11) 66 (14) Pathological Confirmation Yes 660 (58) 85 (23) 86 (47) 21 (16) 468 (100) No 483 (42) 276 (77) 96 (53) 111 (84) 0 (0) T-stage IA 783 (69) 247 (68) 99 (54) 112 (85) 325 (69) IB 360 (31) 114 (32) 83 (46) 20 (15) 143 (31) Overall survival Median (IQR) 41.6 (15.4-95.8) 13.5 (5.3-30.3) 37.1 (18.5-59.6) 65.3 (29.1-85.3) 92.3 (40.6-NR) 2-year survival n (%) 744 (65) 116 (32) 121 (66) 110 (83) 397 (85) Censored n (%) 407 (36) 30 (8) 40 (22) 69 (52) 268 (57) Period of Diagnosis A (2012-2013) 252 (22) 83 (23) 51 (28) 0 (0) 118 (25) B (2014-2016) 443 (39) 144 (40) 69 (38) 50 (38) 180 (39) C (2017-2019) 448 (39) 134 (37) 62 (34) 82 (62) 170 (36) Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000455 | Background: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers. Given the currently limited therapeutic options, the definition of molecular subgroups with the development of tailored therapies remains the most promising strategy. Patients with high-level gene amplification of urokinase plasminogen activator receptor (uPAR/PLAUR) have an inferior prognosis. We analyzed the uPAR function in PDAC to understand this understudied PDAC subgroup's biology better. Methods: A total of 67 PDAC samples with clinical follow-up and TCGA gene expression data from 316 patients were used for prognostic correlations. Gene silencing by CRISPR/Cas9, as well as transfection of uPAR and mutated KRAS, were used in PDAC cell lines (AsPC-1, PANC-1, BxPC3) treated with gemcitabine to study the impact of these two molecules on cellular function and chemoresponse. HNF1A and KRT81 were surrogate markers for the exocrine-like and quasi-mesenchymal subgroup of PDAC, respectively. Results: High levels of uPAR were correlated with significantly shorter survival in PDAC, especially in the subgroup of HNF1A-positive exocrine-like tumors. uPAR knockout by CRISPR/Cas9 resulted in activation of FAK, CDC42, and p38, upregulation of epithelial makers, decreased cell growth and motility, and resistance against gemcitabine that could be reversed by re-expression of uPAR. Silencing of KRAS in AsPC1 using siRNAs reduced uPAR levels significantly, and transfection of mutated KRAS in BxPC-3 cells rendered the cell more mesenchymal and increased sensitivity towards gemcitabine. Conclusions: Activation of uPAR is a potent negative prognostic factor in PDAC. uPAR and KRAS cooperate in switching the tumor from a dormant epithelial to an active mesenchymal state, which likely explains the poor prognosis of PDAC with high uPAR. At the same time, the active mesenchymal state is more vulnerable to gemcitabine. Strategies targeting either KRAS or uPAR should consider this potential tumor-escape mechanism. pancreatic cancer uPAR KRAS FAK MEK ERK dormancy gemcitabine Deutsche ForschungsgemeinschaftKFO5002 Hunan Provincial Health Committee Foundation of ChinaD202302087111 P.S. is supported by the Deutsche Forschungsgemeinschaft (KFO5002). L.P. received funding from the Hunan Provincial Health Committee Foundation of China (Grant No. D202302087111). pmc1. Introduction Pancreatic ductal adenocarcinomas (PDACs) are among the human tumors with the worst prognosis. Most PDAC patients are already at an advanced stage at diagnosis, and resection as the most effective treatment is only feasible in 20% of patients . With gemcitabine as a baseline combined with FOLFIRINOX, next to albumin-bound paclitaxel, therapeutic options are limited . The current clinical staging of PDAC cannot fully predict tumor behavior, and the prognosis of patients receiving the same treatment varies considerably. Therefore, it is essential to develop robust molecular classifications of PDAC for more tailored therapeutic approaches . An increasing number of molecular and histological subtypes already define subtype-specific therapeutic vulnerabilities and provide the opportunity to supplement current pathological classifications. Recent studies discovered many PDAC subtype-specific markers connected to different clinical behavior; however, the three main subtypes remain classical, quasi-mesenchymal (QM-PDA), and exocrine-like . Nevertheless, there is now good evidence that cancer cells preserve cellular plasticity . Increased levels of urokinase-type plasminogen activator receptor (uPAR) are associated with early invasion, metastasis, and poor prognosis in many solid and hematological tumors, including PDAC . uPAR is a GPI-anchored cell membrane receptor without an intracellular domain that mediates the degradation of extracellular matrix (ECM) components , including fibronectin and vitronectin . It locally increases plasmin activity that facilitates cell migration. Interaction of uPAR with integrins occurs indirectly through stabilized binding to vitronectin . This leads to intracellular activation of the Ras pathway, the focal adhesion kinase (FAK), and the Rho family small GTPase Rac (reviewed in ). PDAC is also one of the tumors with the highest frequency of KRAS mutations. KRAS has not only been shown to activate cell proliferation through RAF/MEK/ERK ; it has also been reported to regulate uPAR expression by AP1-dependent transactivation of the uPAR promoter . Downregulation or blocking of uPAR causes activation of FAK, Src, CDC42, and p38, resulting in cell-cycle arrest and dormancy . We have previously shown that 50% of PDACs show overexpression of uPAR due to low or high-level amplifications of the uPAR gene PLAUR. These tumors are associated with an inferior prognosis . In this study, we functionally studied the role of uPAR in cell lines and validated the results in a cohort of 67 PDAC patients with clinical follow-up supplemented by TCGA data of 316 PDAC patient samples. 2. Materials and Methods 2.1. Human Tissue Samples Tumor samples from 67 PDAC patients organized on a multi-tissue array (TMA) were used for immunohistochemical staining (clinical data are summarized in Table 1). The patient sample collection was approved by the ethics committee of the University Medical Center Gottingen (GO 912/15). 2.2. Immunohistochemistry Immunohistochemical staining (IHC) of 2 mm paraffin sections was performed according to standard methods. Briefly, after deparaffinization in serially diluted alcohol and blocking endogenous peroxide in 0.3% hydrogen peroxide in PBS, antigen retrieval was performed at 95 degC in either a low or high-pH Envision FLEX target retrieval solution (Agilent, Santa Clara, CA, USA) using PT Link (Agilent). Subsequently, the stainings were incubated for 1 h with primary antibodies, followed by washing in PBS and incubation with the appropriate detection system for 30 min (Envision, Agilent). Antibodies were used at predetermined optimal dilutions (Supplementary Table S3) with the proper positive and negative controls. Staining was visualized by 3,3-diaminobenzidine tetrahydrochloride solution, counterstained with hematoxylin, dehydrated, and mounted in Pertex. Using an H-score, all tissue samples were evaluated for nuclear staining of p-p38, uPA, uPAR, and PAI1. The H-score was calculated by 3 x the percentage of the strongest staining signal + 2 x the percentage of a moderate signal + the percentage of a weak signal, resulting in a value range from 0 to 300. HNF1A and KRT81 were graded for "low" or "high" expression according to signal intensity. The optimal levels for the discrimination between high and low signals of uPAR, HNF1A, and KRT81 were determined using the cutoff finder . 2.3. Cell Culture and Transient Expression of uPAR and KRASG12C The human pancreatic cancer cell lines BxPC-3, AsPC-1, CAPAN-2, MIA PaCa-2, PATU8988T, and PANC-1 were obtained from the American Type Culture Collection (ATCC) (Supplementary Table S1). All cells were grown in RPMI-1640 medium (Gibco, Waltham, MA, USA), supplemented with 10% FCS (Gibco), 1% L-glutamine (Gibco), and 1% Penicillin/Streptomycin (Gibco) under humidified conditions at 37 degC and 5% CO2. PANC-1 was transfected with the pCMV-AC-GFP vector PLAUR (NM_002659) human-tagged ORF clone (Origene, Rockville, MD, USA), and BxPC-3 with the pCMV6-Entry-KRASG12C vector (Origene Technologies Inc., Rockville, MD, USA) using the X-tremeGENE HP DNA transfection reagent (Merck, Darmstadt, Germany). Transfected cells were selected with G418 (400 ng/mL). uPAR protein levels were tested by ELISA as described above. KRASG12C-expressing cells were selected using 2mg/mL puromycin. 2.4. Generation of ASPC-1 uPAR Knockouts by CRISPR/Cas9 The uPAR CRISPR/Cas9 knockout strategy is shown in Supplementary Figure S1. Cells were transfected with two CRISPR/Cas9 constructs, pCMV-Cas9-RFP (target site: 5'-GGACCCTGAGCTATCGGACTGG-3'), and pCMV-Cas9-GFP (target site: 5'-AGGTAACGGCTTCGGGAATAGG-3') (Sigma-Aldrich, Darmstadt, Germany) using the X-tremeGENE HP DNA transfection reagent (Merck, Rahway, NJ, USA) according to the manufacturer's instructions. After transient CRISPR/Cas9 activation, fluorescence-activated cell sorting (FACS) of GFP/RFP double-positive cells was performed for clone selection. PCR-screened clones for the gRNA target site or a potential deletion, as described later . Clones that were heterozygous for the deletion were further screened for specific gRNA target site mutations by Sanger sequencing . 2.5. Genomic PCR and Sanger Sequencing The gRNA target sites were amplified with the primers GFP F: 5'-CTGTCCCCATGGAGTCTCAC-3', GFP R:5'-CATCCAGGCACTGTTCTTCA-3', RFP F: 5'-CTGGAGCTGGTGGAGAAAAG-3', and RFP R: 5'-GGATTGGGATGATGATGAGG-3' using MyTaqTM Mix (Bioline, London, UK) and the PCR products were analyzed via QIAxcel (Qiagen, Hilden, Germany). The PCR product was purified with ExoSAP-ITTM (Applied Biosystems, Foster City, CA, USA), and sequenced according to Sanger sequencing using the BigDye(r) terminator v3.1 cycle sequencing kit (Applied Biosystems, Waltham, MA, USA). Sequences were analyzed using an ABI 3500 genetic analyzer (Applied Biosystems). 2.6. Cell Viability Assay The CellTiter 96(r) AQueous one-solution cell-proliferation assay (MTS, Promega, Madison, WI, USA) was performed according to the manufacturer's recommendations. In brief, 1 x 104 cells were grown in a 96-well format in 100 mL/medium and treated with indicated conditions over different periods, as described under results. Then, 20 mL of the MTS reagent was added and incubated for 1-3 h at 37 degC, and the absorbance was measured at 490 nm and 655 nm. Relative cell viability after treatment was calculated by normalizing each value by the mean of the untreated control replicates. Unless stated otherwise, all experiments were conducted by pretreating cells with 80 nM of the specific siRNA or inhibitors for 24 h and subsequent treatment with 0.1 mM gemcitabine for 72 h. 2.7. Wound Healing Assay siRNA or mock-transfected cells were grown to almost 100% confluency before synchronizing the cells by decreasing FCS to 1% for 24 h. Wounds were created by scratching the cell monolayer with a 100 mL sterile pipette tip. Wound healing was monitored at 0, 24, and 48 h. Relative wound healing was calculated by measuring the mean distance at three defined positions of the scratch expressed as a percentage of the 0 h control. 2.8. siRNA Knockdown Experiments siRNA transfection was performed using HiPerFect transfection reagent (Qiagen) as described elsewhere . In brief, 80 nM of gene-specific or negative control siRNA (all Star Negative Control, Qiagen) was incubated with 12 mL HiPerFect in 100 mL transfection medium containing serum-free RPMI at RT for 20 min and added to freshly seeded cells (3 x 105 cells). After 24 h or 48 h incubation, cells were further processed as indicated. siRNAs used were purchased from Qiagen and are summarized in Supplementary Table S2. 2.9. Protein Extracts, Western Blot Analyses, and uPAR Quantification by ELISA Cells at 60-70% confluency were treated as indicated in the results section. Cells were washed in PBS and scraped in a 100 mL RIPA lysis buffer containing protease inhibitor cOmplete (Roche, Mannheim, Germany), PMSF (1 mM), and orthovanadate (1 mM). Total protein was quantified using a DCTM protein assay (Bio-Rad, Hercules, CA, USA). A total of 15 mg of proteins was separated using gradient SDS gels (4-20%, Bio-Rad) and blotted on nitrocellulose membranes by a Turbo Blot (Bio-Rad). Gene signals were detected as described before . uPAR protein levels were determined by ELISA (DUP00, R&D Systems, Minneapolis, USA) according to the manufacturer's protocol. In brief, cell lysates from 105 to 106 cells were 10-fold diluted in a RIPA lysis buffer, and 50 mL of cell lysates or standard was added to 100 mL of assay diluent RD1W solution. The samples were incubated for two hours at RT and washed four times with a 400 mL wash buffer. A total of 200 mL of human uPAR conjugate was added and incubated for 2 h at RT. After four washing steps, 200 mL of substrate solution was added and incubated for 30 min at RT protected from light before adding 50 mL of stop solution. The optical density was measured at 450 nm with a reference of 540 nm on a Tecan reader Infinite 200 Pro. uPAR concentrations were calculated for 106 cells. 2.10. KRAS Activity Measurement KRAS activity was quantified using the STA-400-K-T assay (Cell Biolabs) following the manufacturer's instructions. In brief, 1 mg protein was subjected to raf1 RBD agarose beads and incubated at 4 degC for one h. Beads were pelleted, washed, and resuspended in 4x Laemmle buffer. KRAS activity was quantified by Western blotting of 20 mg supernatant protein. 2.11. Statistical Analysis Statistical analysis and AUC estimation were performed using GraphPad 8.3.0. Data are shown as mean +- SEM. Two group comparisons were performed using Student's t-test. Two-way ANOVA was applied to compare cell growth and resistance analyses. Survival was analyzed using the Kaplan-Meier test and significance was evaluated using the log-rank (Cox-Mantel) test. A p-value of < 0.05 was considered significant (* = p < 0.05, ** = p < 0.01, *** = p < 0.001). 3. Results 3.1. uPAR Protein and mRNA Expression Levels Have Prognostic Significance in PDAC Our previous study showed that uPAR gene amplification in PDAC correlates with poor prognosis . Immunohistochemical (IHC) staining for uPAR, its ligand uPA, and the inhibitor PAI1 in a clinical cohort of 67 patients also confirmed a prognostic relevance of uPAR on the protein level. Patients with high uPAR expression (n = 46) had significantly shorter overall survival (OS) than patients with low uPAR levels (n = 23) (median survival 320 days in uPARhigh vs. 603 days in uPARlow patients, log-rank (Cox-Mantel) test, p = 0.0273) . Using gene expression data from two TCGA datasets including 312 PDAC patients , patients with high uPAR mRNA expression had a significantly reduced OS compared to patients with tumors of low expression (log-rank (Cox-Mantel) test, p = 0.0099) . IHC did not reveal any significant difference in OS for uPA and PAI1 ; however, on the transcriptional level, high expression of both uPA and PAI1 showed a significantly decreased OS . 3.2. Generation of CRISPR/Cas9 uPAR Knockout Clones in AsPC-1 Cells Next, we wanted to investigate the molecular function of uPAR in PDAC cells. Therefore, we measured the uPAR protein expression levels by ELISA in six PDAC cell lines with known gene mutation status of KRAS, TP53, and PIK3CA as described in the Material and Methods section . We then generated uPAR knockout clones of the cell line with the highest uPAR expression (AsPC-1), using two gRNAs directed against uPAR exons 3 and 4 . Two clones with homozygous functional uPAR knockout (KO#1 and KO#2), carrying a deletion on one allele and a gRNA target-site-specific frameshift mutation on the other, revealed a virtually absent uPAR protein . 3.3. uPAR Influences Cell Growth, Cellular Plasticity, and the Response to Gemcitabine in AsPC-1 (KRASG12D) Functional roles of uPAR have been described in cell proliferation, migration, and cellular plasticity . Both AsPC-1 uPAR-/- clones showed a significant decrease in growth and migration capacity compared to the AsPC-1 WT controls . To evaluate the role of uPAR in cellular plasticity, we immunoblotted nine markers involved in epithelial-mesenchymal transition (EMT) . Western blot revealed a marked upregulation of epithelial markers E-cadherin and b-catenin. While the transcription factor Slug was slightly upregulated, Snail and TCF8/ZEB1, together with claudin and ZO1, showed a decreased expression, further indicating the mesenchymal to epithelial transition (MET) in uPAR-/- clones compared to AsPC-1 WT . In accordance with this phenotype, we detected a marked increase in chemoresistance against up to 1 mM gemcitabine in uPAR-/- cells . 3.4. Depletion of uPAR Activates FAK, CDC42, and p38 and Induces Autophagy uPAR signaling has been described to involve FAK, Src, CDC42, p38, autophagy, and RAS signaling . In addition, Wu et al. reported that FAK signaling contributes to intrinsic gemcitabine chemoresistance in pancreatic cancer cell lines . By immunoblotting, we detected the activation of FAK, CDC42, p38, and LC3B, while ERK was inactivated in AsPC-1 uPAR-/- cells . The influence of FAK on Ras signaling has been described before . However, in cells with aberrant KRAS activation, FAK-Ras regulation seems to be disturbed. Knockdown of FAK in uPAR-/- cells using siRNAs led to decreased phosphorylation of CDC42, p38, and LC3B, and reactivation of ERK . The diminished FAK activity also partially restored the sensitivity towards gemcitabine . Knockdown of CDC42 and p38 also reactivated ERK, decreased LC3B, and increased gemcitabine sensitivity . This indicates that CDC42 and p38 suppress ERK activity downstream of KRAS in the absence of uPAR. 3.5. Re-expression of uPAR Restores the Migratory Capability and Gemcitabine Sensitivity of uPAR-/- Cells To evaluate whether uPAR re-expression could restore the WT phenotype, uPAR-/- cells were transfected with a human uPAR gene expression vector as described in the Material and Methods section. This recovered uPAR protein levels and significantly enhanced migratory capacity . uPAR re-expression also recovered gemcitabine sensitivity and induced resistance against the p38 inhibitor JX401 . Pharmacological inhibition of ERK with SCH772948 reduced gemcitabine sensitivity only in uPAR WT but not in AsPC-1 uPAR-/- cells . Together, this indicates that uPAR mediates gemcitabine sensitivity in an ERK-dependent manner. 3.6. Resistance against Gemcitabine in AsPC-1 uPAR-/- Cells through Autophagy The autophagy marker LC3B was induced in AsPC-1 uPAR-/- cells. Autophagy promotes tumor cell survival and contributes to chemoresistance . Increased autophagy has been described to be responsible for the resistance of PDAC to gemcitabine that could be partially reversed by specific inhibitors . To investigate whether increased autophagy in uPAR-/- clones was responsible for the observed gemcitabine resistance, we inhibited autophagy with 3-methyladenine (3-MA) or chloroquine (CQ). Both inhibitors significantly restored sensitivity towards gemcitabine in AsPC-1 uPAR-/- but not in AsPC-1 WT . 3.7. uPAR and Mutated KRAS Cooperate in Maintaining a Mesenchymal Phenotype To evaluate the interplay of uPAR and mutated KRAS in response to gemcitabine, we used the KRAS WT cell line BxPC-3 (uPAR high), the KRAS mutant cell line AsPC1 (uPAR high), and the KRAS mutant cell line PANC-1 (uPAR low) . AsPC1 responded best towards gemcitabine, PANC-1 showed a medium response, and BxPC3 was the most resistant cell line . KRAS has been described to induce uPAR expression . Silencing of KRAS in AsPC1 using siRNAs reduced uPAR levels significantly . Silencing of KRAS in AsPC1 reduced the response towards gemcitabine whereas the expression of mutated KRAS in BxPC-3 cells increased gemcitabine sensitivity. Transfection of uPAR in PANC-1 likewise increased gemcitabine sensitivity . uPAR and mutated KRAS switched cells to a mesenchymal phenotype , at the same time promoting activation of MEK and ERK and suppressing FAK and CDC42 signaling . 3.8. uPAR Modulates the Clinical Risk in Different PDAC Subgroups Noll et al. published HNF1A as a surrogate marker for the exocrine-like PDAC subtype and expression of keratin 81 (KRT81) as a marker for the quasi-mesenchymal (QM) type. Tumors negative for both markers (DN) were enriched for the classical PDAC subtype. We wanted to know if tumors with high uPAR expression segregate with one of these subtypes. In our own cohort of 57 patients with clinical follow-up, n = 31 (54%) showed expression of HNF1A, n = 19 (33%) were positive for KRT81, and n = 7 (12%) were DN. Because the DN group was too small, we excluded it from further analysis. The exocrine-like group consisted of 21 uPAR low and 10 uPAR high cases, and the QM group contained 9 uPAR low and 10 uPAR high cases. Survival analysis was supplemented by gene expression data from the two TCGA cohorts (n = 82 cases HNF1A high vs. n = 85 cases KRT81 high). The overall survival of patients with HNF1A-positive exocrine-like PDAC was significantly longer than patients with KRT81-positive QM tumors . In the HNF1A-positive cohort, tumors with low levels of uPAR had a significantly better outcome than tumors with high expression and the mortality curve even reached a plateau after 1000 days, indicating long-term survival of some patients. In the KRT81high QM and DN group, there was a trend towards longer survival in patients with tumors with low levels of uPAR that did not reach statistical significance , indicating that the prognostic impact of uPAR may vary among different molecular subgroups. 4. Discussion PDAC remains one of the human tumors with the highest mortality. uPAR is associated with early invasion, metastasis, and poor prognosis in many solid and hematological tumors . We have previously shown that PDAC with high-level gene amplifications of uPAR have a particularly poor prognosis . We here show in our cohort of 67 samples and in 168 PDAC samples from the TCGA database that overexpression of uPAR on the mRNA and protein level is also associated with significantly shorter OS. Importantly, although our data suggest that high expression of uPAR is an adverse prognostic factor in all PDAC, its negative impact on survival is more pronounced in some molecular subgroups (especially in exocrine-like tumors) than in others. uPAR has been described to act through its vitronectin-mediated interaction with integrins to transmit mechanical forces across the cell membrane . The ECM-integrin interaction mediates the intrinsic chemoresistance of cancer cells , a phenomenon that has also been called cell-adhesion-mediated drug resistance (CMDR). CMDR has been explained by the strong binding of integrins to the ECM, which activates FAK. Integrin and EGFR signaling activates FAK and influences adhesion, motility, and cell growth . FAK has seemingly paradoxical roles in cell migration and metastasis . FAK is a ubiquitously expressed tyrosine kinase that localizes at focal adhesion complexes and transmits growth-factor-dependent signals into the cell . In contrast to normal cells where FAK is a positive regulator of cell migration and proliferation , tumors with constitutive growth factor signaling (such as EGFR) or RAS mutations and consecutive high intrinsic levels of ERK utilize FAK as a negative regulator of cell migration through ERK-dependent dephosphorylation of particular FAK tyrosine residues . Constitutive activation of FAK has also been proposed to contribute to the intrinsic chemoresistance against gemcitabine in the pancreatic cancer cell line AsPC-1 . We here show that uPAR knockout in AsPC1 cells leads to induction of FAK, Src, CDC42, and p38, as well as chemoresistance towards gemcitabine. Our data further show that this chemoresistance is mediated through p38-induced autophagy. Numerous early clinical trials have shown significant antitumor activity with tolerable toxicity of the autophagy inhibitor chloroquine, in combination with other cytotoxic chemotherapies in a variety of solid cancers, including colorectal and renal cell carcinomas . A randomized clinical phase II trial in 102 PDAC patients treated with gemcitabine and nab-paclitaxel with or without CQ showed no difference in progression-free survival. Still, the authors proposed that preoperative CQ might increase curative resection rates . A total of 90-95% of PDACs harbor activating mutations of KRAS that are thought to occur early in carcinogenesis . Mutated KRAS is a potent oncogenic driver that promotes cell proliferation and migration by activating the downstream MAP kinases ERK1/2 . KRAS has not only been reported to induce uPAR expression by AP-1-dependent transactivation of the uPAR promoter , but also mediates FAK dephosphorylation . We here show that a) constitutively active KRAS induces uPAR and b) KRAS and uPAR cooperate in promoting a mesenchymal cell phenotype by activating MEK/ERK signaling and by the suppression of FAK/CDC42/p38 signaling. At the cellular level, this mesenchymal state implies increased cell proliferation and migration as a possible explanation of the poor prognosis of tumors with high levels of uPAR. At the same time, it also implies suppressed cellular dormancy via FAK signaling and p38-mediated autophagy, thus rendering the cells more vulnerable to gemcitabine. These observations highlight a potential therapeutic dilemma that applies both to KRAS and uPAR as emerging targets. Although recent studies propose uPAR as a good candidate for antibody-targeted therapy in cancer , our results show that these treatments could, at the same time, induce cellular dormancy and render the tumor more resistant to chemotherapy (such as gemcitabine). Tailored strategies should consider this resistance by adding autophagy inhibitors, such as chloroquine, to the regimens. 5. Conclusions In summary, we have confirmed uPAR as a potent modulating prognostic factor, especially in the large molecular subgroup of exocrine-like tumors. uPAR cooperates with mutated KRAS in the important switch between an active mesenchymal vs. a dormant epithelial cellular phenotype. By keeping tumor cells in the active mesenchymal state, uPAR promotes KRAS-driven proliferation and cell migration as a likely explanation for the poor prognosis of PDAC with high expression of uPAR. At the same time, this active mesenchymal state renders tumor cells more vulnerable to chemotherapy such as gemcitabine. Targeting either uPAR or KRAS could induce cellular dormancy and autophagy, thus leading to relative chemoresistance and limited therapeutic efficacy. Emerging clinical trials should take this possibility into account. Acknowledgments We thank Ulrike Ehbrecht, Jennifer Appelhans, Monique Kuffer, and Stefanie Schwager for their excellent technical support. Supplementary Materials The following supporting information can be downloaded at: Supplementary Figure S1: (a) Staining intensities (300 score) of uPA, uPAR, and PAI1 of 69 PDAC patient samples. (b) OS analysis of PDAC patients with low vs. high protein expression of uPA on immunohistochemistry, and (c) PAI1. (d) OS analysis of PDAC patients with low vs. high mRNA expression of uPA (Cox-Mantel-test, p = 0.0475) and (e) PAI1; Supplementary Figure S2: (a) uPAR and (b) uPA protein levels of the pancreatic cell lines AsPC-1, BxPC-3, CAPAN-2, MIA PaCa-2, PATU8988T, and PANC-1 measured by ELISA. (c) Schematic representation of the uPAR CRISPR/Cas9 strategy. Two gRNAs were directed against exon three and exon 4 of the uPAR gene and were used to generate uPAR-/- clones. (d-f) Sanger sequencing analysis of two uPAR-/- clones consisting of a large deletion and a site-specific mutation. (g) ELISA measurement of uPAR levels in KO#1 and KO#2 compared to uPAR WT and (h) of rescue KO#2 by re-expressing uPAR compared to KO#2. (i) Exemplary pictures of the migration assay of AsPC-1 WT, KO#1 and KO#2 over 48 h; Supplementary Figure S3: Gemcitabine treatment after siRNA knockdown and p38 inhibition in AsPC1 WT and uPAR-/- cells. Gemcitabine response (0.1 mM, 72 h) after siRNA knockdown (80 nM, 24 h) of (a) FAK, (b) CDC42 and (c) of p38 in AsPC1 KO#2. (d) Gemcitabine treatment of AsPC-1 WT and uPAR-/- cells (KO#2) in combination with the p38 inhibitor JX401. (e) Gemcitabine treatment (0.1 mM, 72 h) vs. combination with ERK inhibition (SCH772948, 3mM) of uPAR-/- cells (KO#2). (f) Treatment of uPAR knock-out clones (KO#2) with either gemcitabine (0.1 mM) or in combination with the autophagy inhibitors 3-MA (5 mM) or CQ (5 mM) (n = 4); Supplementary Figure S4: Kaplan Meyer OS analysis of TCGA patient cohort. (a) uPAR low (n = 15) vs. uPAR high (n = 49) in DN cases and (b) uPAR low (n = 22) vs. uPAR high (n = 69) in DP cases; Table S1; Human PDAC cell lines with TP53 and KRAS mutation status; Table S2: siRNAs (Qiagen); Table S3: Antibodies and chemicals; Supplementary Material File S1: Uncropped WB images. Click here for additional data file. Author Contributions Conceptualization, S.K., L.P. and P.S.; data curation, S.K., L.P., Y.L., S.Y., J.K., V.M.B., C.F.M.S., F.F. and H.B.; formal analysis, S.K., L.P., Y.L., J.K., V.M.B., C.F.M.S., F.F. and H.B.; investigation, S.K., Y.L. and L.P.; methodology, S.K. and L.P.; project administration, S.K., L.P. and P.S.; resources, J.G., A.N., V.E. and P.S.; supervision, S.K. and P.S.; visualization, S.K.; writing--original draft, S.K., L.P. and P.S.; writing--review and editing, S.K. and P.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the University Medical Center Gottingen (GO 912/15). Informed Consent Statement Written informed consent for the clinical procedure was obtained from all participants. Data Availability Statement The data presented in this study are available in the article, the Supplementary Materials and at TCGA accessed on 30 January 2023: Pancreatic Adenocarcinoma, Firehose Legacy and PanCancer Atlas). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Prognostic significance of uPAR expression in PDAC patients. (a) Exemplary immunohistochemical staining of PDAC with high vs. low expression of uPAR. (b) Statistically significant difference in OS for n = 67 PDAC patients with high (orange, n = 45) vs. low (black, n = 22) immunohistochemical expression of uPAR. (c) Statistically significant difference in OS for n = 83 PDAC patients with high (black) vs. n = 219 patients with low (orange) expression levels of uPAR mRNA (source: TCGA dataset). Figure 2 Decreased cell growth, motility, and response to gemcitabine of AsPC uPAR knockout clones. (a) Cell growth analysis (6 days) of uPAR-/- clones with a significantly slower proliferation rate than WT controls (n = 3). (b) Reduced migratory capacity of AsPC-1 uPAR-/- clones compared to uPARWT cells (n = 3). (c) Western blot analysis of 9 epithelial and mesenchymal markers in PANC-1, AsPC-1, and uPAR-/- clones indicated mesenchymal to epithelial transition (MET) in uPAR-/- cells. Uncropped Western blot images available in Supplementary Material File S1 (d) Increased resistance of uPAR-/- clones to gemcitabine treatment (0.1, 0.5 and 1 mM) for 72 h (n = 4 biological replicates). (KO#1 and KO#2, uPAR-/- clones) (*** p < 0.001). Figure 3 uPAR regulates CDC42, p38, LC3B, and ERK activity. (a) Immunoblot showing increased signals for pCDC42, pSrc, p-p38, pERK, and LC3B in KO#1 and KO#2.). Uncropped Western blot images could be found at in Supplementary File S1. Restoration of (b) the wild-type signaling phenotype after FAK siRNA knockdown in AsPC-1 uPAR-/- cells and (c) of the response to gemcitabine (n = 4). Uncropped Western blot images could be found at in Supplementary File S1 (d) Knockdown of CDC42 by siRNA and (e) response to gemcitabine and (f) siRNA knockdown of p38 and (g) the corresponding gemcitabine response. Uncropped Western blot images available in Supplementary File S1. (h) Increased cellular motility after transient uPAR expression in KO#2 (KO#2 rescue) compared to AsPC-1 uPAR-/- cells (n = 4). (i) Gemcitabine (0.1 mM) and combinational treatment with the p38 inhibitor JX401 for 72 h in AsPC-1 uPAR-/- and KO#1 uPAR rescue cells (n = 3). (j) Gemcitabine (0.1 mM) and combinational treatment with the ERK inhibitor SCH772948 in uPAR WT and AsPC-1 uPAR-/- cells (KO#1). (k) Treatment of AsPC-1 WT and AsPC-1 uPAR-/- (KO#1) with either gemcitabine (0.1 mM) or in combination with the autophagy inhibitors 3-MA (5 mM) or CQ (5 mM). Relative viability is shown in response to gemcitabine and in combination with siRNA/inhibitors. (n = 4 biological replicates (** p < 0.01, *** p < 0.001). Figure 4 uPAR and mutated KRAS cooperate in maintaining a mesenchymal phenotype that also regulates gemcitabine sensitivity. (a) Immunoblot showing uPAR, HNF1A, and KRT81 expression in BxPC-3, AsPC-1, and PANC-1. Uncropped Western blot images available in Supplementary File S1 (b) IC50 of gemcitabine treatment (0-100 mM, 72 h) in BxPC-3 (1.323 mM), AsPC-1 (0.025 mM), and PANC-1 (0.112 mM). (c) uPAR levels after KRAS siRNA knockdown in AsPC-1 (n = 3 biological replicates, ** Student's t-test, p < 0.01, *** Student's t-test, p < 0.001). (d) Gemcitabine response (0.125 mM, 72 h) in AsPC-1 WT, AsPC-1 uPAR-/- (KO#1), BxPC-3 (KRAS WT), BxPC-3 (KRASmut), PANC-1 (uPARlow), and PANC-1 (uPARhigh). (e) Immunoblot of protein lysates from the same cell lines for EMT markers and (f) pFAK, pCDC42, p-p38, pMEK, p-ERK, and LC3B. Kaplan-Meier curves using mRNA expression data of PDAC from the TCGA cohort. Uncropped Western blot images available in Supplementary File S1. (g) Comparison of PDAC with high expression of HNF1A vs. KRT81. (h) KRT81high tumors with high vs. low expression of uPAR and (i) HNF1Ahigh tumors with high vs. low expression of uPAR (log-rank test, p < 0.05). cancers-15-01587-t001_Table 1 Table 1 Clinical data summary. Patients 67 Male (%) 37 (55) Female (%) 30 (45) Age median (range) 68 (44-84) Tumor grade (G) 1-2 (%) 6 (9) 2-3 (%) 41 (61.1) 3-4 (%) 20 (29.9) Tumor stage (TNM) T 1 (%) 1 (1.5) T 2 (%) 3 (4.5) T 3 (%) 58 (86.6) T 4 (%) 5 (7.4) N 0 (%) 14 (20.9) N 1-3 (%) 53 (79.1) Median follow-up time (range) [day] 417 (4-2768) Reported deaths (%) 62 (92.5) Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000456 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050911 foods-12-00911 Article Organic Acid Accumulation and Associated Dynamic Changes in Enzyme Activity and Gene Expression during Fruit Development and Ripening of Common Loquat and Its Interspecific Hybrid Deng Honghong Methodology Writing - original draft Writing - review & editing Li Xuelian Methodology Software Wang Yang Methodology Ma Qiaoli Methodology Zeng Yuge Methodology Xiang Yinchun Methodology Chen Mingmin Methodology Zhang Huifen Software Xia Hui Software Liang Dong Software Lv Xiulan Software Wang Jin Software Deng Qunxian Conceptualization Writing - review & editing * da Cruz Adriano Gomes Academic Editor Freitas Otniel Academic Editor Teodoro Anderson Junger Academic Editor College of Horticulture, Sichuan Agricultural University, Chengdu 611130, China * Correspondence: [email protected]; Tel.: +86-13551551617 21 2 2023 3 2023 12 5 91107 12 2022 02 2 2023 06 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Loquats have gained increasing attention from consumers and growers for their essential nutrients and unusual phenology, which could help plug a gap period at market in early spring. Fruit acid is a critical contributor to fruit quality. The dynamic changes in organic acid (OA) during fruit development and ripening of common loquat (Dawuxing, DWX) and its interspecific hybrid (Chunhua, CH) were compared, as well as the corresponding enzyme activity and gene expression. At harvest, titratable acid was significantly lower (p <= 0.01) in CH (0.11%) than in DWX loquats (0.35%). As the predominant OA compound, malic acid accounted for 77.55% and 48.59% of the total acid of DWX and CH loquats at harvest, followed by succinic acid and tartaric acid, respectively. PEPC and NAD-MDH are key enzymes that participate in malic acid metabolism in loquat. The OA differences in DWX loquat and its interspecific hybrid could be attributed to the coordinated regulation of multiple genes and enzymes associated with OA biosynthesis, degradation, and transport. The data obtained in this work will serve as a fundamental and important basis for future loquat breeding programs and even for improvements in loquat cultural practices. loquat organic acid metabolism gene expression enzyme activity Science and Technology Department of Sichuan Province2021YFYZ0023-07 fruit innovation team of Sichuan Province within national modern agricultural industrial technology systemsccxtd-2023-04 Science and Technology Department of Sichuan Province program2022NSFSC0092 agricultural public security and resource protection of Sichuan ProvinceThis research was funded by the program of Science and Technology Department of Sichuan Province (2021YFYZ0023-07), the fruit innovation team of Sichuan Province within national modern agricultural industrial technology system (sccxtd-2023-04), the Science and Technology Department of Sichuan Province program (2022NSFSC0092), and agricultural public security and resource protection of Sichuan Province. pmc1. Introduction Common loquat (Eriobotrya japonica Lindl.) is an important sub-tropical fruit crop belonging to the tribe Photinieae, subfamily Maloideae, and family Rosaceae . Consumers now demand nutritional and health-promoting qualities in fruit and its derivatives. The consumption of loquat fruit has been following an increasing trend, which could be mainly ascribed to its delicious taste and high content of nutritional compounds such as carbohydrates, proteins, vitamins, minerals, carotenoids, phenolics, flavonoids, dietary fibers, phenolic compounds, and organic acids (OAs) . In addition, its roots, leaves, and flowers have been credited with important medical value due to their anti-inflammatory and antitumor properties. They have long been used to treat inflammation, diabetes, cancer, bacterial infection, aging, pain, and allergy in traditional Chinese medicine . Unlike other temperate fruit crops, common loquat trees bloom in autumn and early winter, and the fruit matures in spring and early summer, when very few fleshy fruits are available at that time in the marketplace . This unusual phenology makes it a popular fruit crop for consumers, and few competitive fruits being in the market makes it a profitable crop for growers. However, common loquat flowers and young fruits are susceptible to low temperature and damage by winter frosts . Different from the flowering time of common loquat, bangal loquat (E. bengalensis f. Hook.) blooms in spring and is a late-maturing loquat. However, when used as parent in the processing of interspecific hybridization, it shows poor compatibility: the success hybridization rate is less than 10% based on our more than 20 years of loquat-breeding experience. In our loquat-breeding programs, 'Chunhua' (CH), an interspecific hybrid of common loquat (Dawuxing, DWX, E. japonica (Thunb.) Lindl.) and bangal loquat (E. bengalensis f. Hook.), was recently released . Combining the advantages of parents, CH loquat blooms in spring, thus escaping chilling injuries in winter, and matures almost one month later than common loquat. This late-maturing characteristic of CH is essential to extend the loquat market season when common loquat is no longer in supply. In addition, CH loquat is defined as a low-acid cultivar, while its female parent (DWX) is a moderate-acid cultivar based on more than ten years of observation. DWX is the most popular common loquat cultivar among the commercially available varieties in China. It originated from the seedlings of local loquat and was developed in 1983 by Yongnian Zhou of the Institute of Pomology, Longquanyi District, Chengdu City, Sichuan Province, China. Sugar, acid, aroma, color, and texture are key components of fruit quality traits determining consumer satisfaction and appreciation. The acidity levels are mostly attributed to the components and contents of OAs , particularly the malic and citric acids in fleshy fruits . OAs also contribute to plant growth and development, pH regulation, storage carbon molecule, and stress responses . The similarity in the genetic origin and difference in fruit acidity between these two important loquat cultivars provide us an excellent opportunity to understand OA metabolism and accumulation in loquat fruits and identify key factors influencing loquat fruit acid. The current consensus is that the net balance of synthesis, degradation, and transport determines OA accumulation in fruit . Several pathways for malic and citric acid metabolism in fleshy fruits have been characterized , as illustrated in Figure 1. Key enzymes involved in malate and citrate biosynthetic pathways are phosphoenolpyruvate carboxylase (PEPC), malate dehydrogenase (MDH), and citrate synthase (CS), while key enzymes involved in OA degradation are phosphoenol carboxykinase (PEPCK), malic enzyme (ME), and aconitase (ACO) . Once malic and citric acids have been synthesized in cytosol, their accumulation levels depend largely on the transport from cytosol to vacuole . These complex processes are mediated by numerous vacuolar transporters , such as tonoplast dicarboxylate transporter (tDT) and channels of aluminum-activated malate transporters (ALMTs) . In addition, the facilitated diffusion of malic and citric acids into vacuole can be caused by tonoplast proton pumps like vacuolar-type H+-ATPase (VHA) and vacuolar-type H+-PPase (VHP) . A better understanding of the composition, content, and accumulation of OAs is necessary before any genetic improvements or cultural practices can be made. The objectives of this study were to evaluate the composition and content of OAs in key stages of fruit development and ripening of DWX loquat and its interspecific hybrid. The corresponding gene expression and enzyme activity changes concomitant with fruit development and ripening were also explored. The outcomes of this study reveal the physiological processes and molecular mechanisms underlying the OA changes of loquat fruit. The comparisons of the two important cultivars provide an excellent opportunity to identify factors impacting loquat OAs. 2. Materials and Methods 2.1. Plant Materials and Sampling This study was conducted using five-year-old (in 2021) bearing loquat trees in fields of the loquat experimental station of College of Horticulture, Sichuan Agricultural University, located at Shimian County, Ya'an City, Sichuan Province, China (29deg18' N, 102deg32' E). The trees were grafted on DWX rootstock with 4 m spacing between rows and 4 m between plants. The row orientation was from north to south. All plants were subjected to identical cultural practices for loquat in this area throughout the experiment, including normal irrigation, fertilization, pest control, and fruit-thinning. Four representative stages of loquat fruit development and ripening are the fruitlet (including a lag phase), cell expansion, breaker, and ripening stages according to and our previous observations. CH loquat blooms in spring, so there is no lag phase in young fruit. Specifically, nine sampling points of DWX loquat included 40, 60, 80, 100, 120, 135, 150, 160, and 165 days after full bloom (DAFB), and eight sampling points of CH loquat were 30, 50, 60, 70, 80, 87, 94, and 101 DAFB, as shown in Figure 2A. The time when the whole inflorescence had approximately 75% of the flowers open at full-bloom stage was set as the baseline (0 DAFB). Loquat fruits grow rapidly approximately one and half months before harvest and were thus sampled at a shorter-time interval. Three fruit samples were randomly collected from the upper, middle, and lower canopy of each tree. The fruit samples from five trees (in total fifteen fruits) consisted of one biological replicate. Each stage consisted of three biological replicates. 2.2. Chemicals and Reagents High-performance liquid chromatography (HPLC)-grade regents, including potassium dihydrogen phosphate, phosphoric acid, oxalic acid, tartaric acid, malic acid, a-ketoglutaric acid, citric acid, and succinic acid, were purchased from Sigma-Aldrich (St. Louis, MO, USA). Aqueous solutions were prepared using ultra-purified water (18.2 MO. cm) from a Milli-Q gradient water purification system (Millipore Corporation, Bedford, MA, USA). 2.3. Fruit Weight, Shape, and Color Measurement Fruit weight was determined using a 0.01-g sensitive balance and obtained from an average of five fruits of each biological replicate. Fruit length was measured longitudinally from the top to the base of fruit and diameter was determined at the equator of the fruit, cut longitudinally. Dividing the fruit vertical length by its transverse diameter yielded the fruit shape index. A CM-2600d spectrophotometer (Konica Minolta, Tokyo, Japan) was used to determine the fruit color. Five fruits of each biological replicate were randomly selected and transversely sectioned. Three points around the equatorial plane of each fruit were measured. The resulting L*, a*, and b* values indicate lightness, greenness, and yellowness, respectively. 2.4. Determination of Titratable Acidity (TA) Fruit TA was determined by titration to a pH of 8.2 with 0.1 mol L-1 NaOH and the results were represented as percentage of malic acid (g of malic acid per 100 g fresh weight (FW)). 2.5. Determination of OAs Using HPLC Coupled with Ultraviolet (UV) Detection Extraction and quantification of OAs were performed using HPLC coupled with UV detection following the previously published protocol by with minor modifications. Briefly, loquat pulp samples were grinded to a fine powder in liquid nitrogen. Then, 0.5 g powder was suspended in 5 mL ultra-purified water, boiled in 80 degC for 1 h, and centrifugated at 8000x g for 10 min. The resultant supernatant was filtered through 0.22 mm filter (Millipore Corporation). Finally, 10 mL of sample was injected to an HPLC instrument equipped with an Agilent 1260 Infinity II system and a diode array detector (Agilent Technologies Inc., Palo Alto, CA, USA). OA compound separation was achieved using a ZORBOX SB-C18 column (4.6 x 150 mm, 5 mm) (Agilent Technologies Inc.). Elution was carried out with a mobile phase made of 0.04 mol*L-1 KH2PO4-H3PO4 solution, adjusted to pH 2.3 with H3PO4. The flow rate was 0.5 mL*min-1, column temperature was 35 degC, and UV detection wavelength was 210 nm. OA compounds were identified using authentic standard compounds and calibrated with solution of known concentrations. 2.6. Assay of OA Metabolism-Related Enzyme Activity Crude enzymes were extracted according to the methods described by with some modifications. In brief, the extraction buffer contained 0.2 mol*L-1 Tris-HCl (pH8.2), 10 mmol*L-1 isoascorbic acid, 5 mmol*L-1 MgCl2, 2 mmol*L-1 ethylenediaminetetraacetic acid (EDTA), 0.1% (w/v) bovine serum albumin (BSA), 0.1% (v/v) Triton X-100, 10% (v/v) glycerol, 0.5 mmol*L-1 phenylmethylsulfonyl fluoride (PMSF), and 2% (w/v) insoluble polyvinylpolypyrrolidone (PVPP). The reaction mixtures used for each enzyme activity measurement are as follows. PEPC: 50 mmol*L-1 Tris-HCl (pH 8.5), 2 mmol*L-1 MgCl2, 2 mmol*L-1 dithiothreitol (DTT), 0.5 mmol*L-1 glutathione (GSH), 0.2 mmol*L-1 reduced nicotinamide adenine dinucleotide-disodium salt (NADH-Na2), 4 mmol*L-1 MnSO4, and 2.5 mmol*L-1 phosphoenolpyruvate. Nicotinamide adenine dinucleotide-malate dehydrogenase (NAD-MDH): 50 mmol*L-1 Tris-HCl (pH 8.5), 2 mmol*L-1 MgCl2, 10 mmol*L-1 NaHCO3, 0.5 mmol*L-1 EDTA, 0.5 mmol*L-1 GSH, 0.2 mmol*L-1 NADH-Na2, and 2 mmol*L-1 oxaloacetic acid (OAA). Nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME): 50 mmol*L-1 Tris-HCl (pH 7.5), 2 mmol*L-1 MnSO4, 0.5 mmol*L-1 EDTA, 2 mmol*L-1 DTT, 0.2 mmol*L-1 NADH-Na2, and 3 mmol*L-1 malic acid. CS: 50 mmol*L-1 Tris-HCl (pH 9.0), 0.05 mmol*L-1 5,5-dithio-bis-(2-nitrobenzoic acid), 0.08 mmol*L-1 acetyl coenzyme A, and 2 mmol*L-1 OAA. ACO: 50 mmol*L-1 Tris-HCl (pH 7.5), 0.1 mmol*L-1 NaCl, 4 mmol*L-1 FeSO4, 0.2 mmol*L-1 NAD, and 20 mmol*L-1 citric acid monohydrate. NAD-isocitrate dehydrogenase (NAD-IDH): 40 mmol*L-1 HEPES buffer solution (pH 8.2), 0.5 mmol*L-1 EDTA, 4 mmol*L-1 MnSO4, 0.2 mmol*L-1 NAD, and 10 mmol*L-1 trisodium hydrogen 3-carboxylato-2,3-dideoxy-1-hydroxypropane-1,2,3-tricarboxylate. The enzyme activity of CS was measured spectrophotometrically at 412 nm, and the enzyme activities of PEPC, NAD-MDH, NADP-ME, ACO, and NAD-IDH were at 340 nm. 2.7. Quantification of Gene Expression Using Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) Total RNA from the fruit samples described above was extracted using TRIzol(r) reagent (Invitrogen, Carlsbad, CA, USA) and treated with TURBO DNA-freeTM kit (Ambion, Austin, TX, USA) to remove DNA contamination, following the manufacturer's protocol. Purified RNA was quantified using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and RNA integrity was evaluated using 1% agarose gel electrophoresis. First-strand complementary DNA synthesis was conducted using a reverse transcription kit containing a PrimeScriptTM RT reagent kit with gDNA Eraser (Perfect Real Time) (Takara, Dalian, China). Genes related to OA metabolism were selected according to the loquat whole genome sequence . The internal reference genes for normalization of relative gene expression were obtained from . PEPC2, NAD-MDH, NADP-ME2, VHA-A, and VHP1 were obtained from . ALTMs were obtained from . The detailed sequences of primers used are listed in Supplementary Table S1. qRT-PCR was performed on a CFX96 Touch Real-Time PCR C1000 Thermal Cycler system (Bio-Rad, Hercules, CA, USA) using Brilliant III Ultra-Fast SYBR Green QPCR Master Mix (Agilent Technologies Inc., Santa Clara, CA, USA), following the manufacturer's recommendations. For each biological replicate, three technical replicates of each PCR were performed. 2.8. Statistical Analyses Means and standard deviation (SD) were calculated using the Microsoft Excel software. Differences within cultivars at each time point were statistically evaluated by one-way analysis of variance (ANOVA) using Tukey's honest significant difference test with a statistical significance of p <= 0.05. The association between OA components and other continuous variables, namely, OA metabolism enzyme activities and associated gene expressions, was determined using Person's correlation coefficient (p <= 0.05). For qRT-PCR, the 2-DDCT method was used to calculate gene expression levels after normalization to the internal reference gene. 3. Results 3.1. Comparative Analyses of Fruit Phenotype, Weight, Shape, and Color of Dawuxing Loquat and Its Interspecific Hybrid The fruit skin color of DWX and CH was changing from green in initial breaker stage gradually to dark orange in appearance and as pulp color measurements as the fruit ripened , respectively. The development of DWX and CH fruits encompassed an average period of approximately 165 and 101 days, respectively . The fruit weight curve of DWX loquat followed a single-sigmoid pattern, with very slow growth in the fruitlet stages (80 DAFB) and a dramatic increase during the expansion stages (80-135 DAFB), followed by a gradual increase afterwards (150-165 DAFB). However, the fruit weight curve of CH loquat exhibited a nonclassical single-sigmoid pattern. At harvest, the fruit weight of DWX loquat (60.54 +- 0.55 g) was significantly higher (p <= 0.001) than that of CH loquat (21.26 +- 0.08 g) . Fruit shape index of DWX and CH loquats reached approximately 1.0 after the breaker stage . 3.2. Comparative Analyses of Organic Acid Compositions and Contents of Dawuxing Loquat and Its Interspecific Hybrid TA content of DWX loquat remained at a relatively low level at fruitlet stage, then rapidly increased over time, peaking at 135 DAFB (3.02%), and dramatically decreased thereafter. TA content of CH loquat showed a similar trend but peaked at 70 DAFB (1.35%). At harvest, TA was significantly lower (p <= 0.01) in CH loquat (0.11%) than in DWX loquat (0.35%) . The dynamics of total acid were similar to that of TA. At harvest, total acid was significantly (p <= 0.01) lower in CH loquat (1.94 +- 0.03 mg g-1 FW) than in DWX loquat (2.94 +- 0.01 mg g-1 FW) . A total of six OAs, namely, malic acid, tartaric acid, succinic acid, oxalic acid, citric acid, and a-ketoglutaric acid, were detected . Their linear regression equations of standard curves and regression coefficients (R2) are listed in Supplementary Table S2. The regression coefficients were generally beyond 0.9995. The predominant OA compound was malic acid, whose accumulation exhibited a similar trend with TA and total acid . The mature CH fruits (0.95 +- 0.02 mg g-1 FW) contained significantly lower (p <= 0.01) levels of malic acid compared to mature DWX fruits (2.28 +- 0.02 mg g-1 FW) . There was a distinct difference in tartaric acid accumulation between DWX and CH loquats. Tartaric acid content in DWX loquat showed a rapid increase in initial stages, peaking at 100 DAFB, decreased dramatically thereafter until 150 DAFB, and remained at a relatively low level during the subsequent fruit-ripening stages. Differently, it exhibited a continuous decreasing tread in CH loquat until 87 DAFB, followed by a stably low level. At harvest, CH fruits (0.42 +- 0.03 mg g-1 FW) contained significantly higher (p <= 0.01) level of malic acid compared to DWX fruits (0.06 +- 0.00 mg g-1 FW) . The contents of succinic acid , oxalic acid , and citric acid exhibited an overall downward trend during fruit development and ripening of the two loquat cultivars, although a unique peak of succinic acid was found at 70 DAFB in CH loquat (3.36 +- 0.16 mg g-1 FW). At harvest, CH fruits contained a significantly higher (p <= 0.01) level of succinic acid but a significantly lower (p <= 0.01) level of oxalic acid compared to DWX fruits. The content of a-ketoglutaric acid increased gradually at fruitlet and expansion stages and reached a maximum value at 160 and 87 DAFB in DWX and CH loquats, respectively, before subsequently declining . The mature CH fruits contained a significantly higher (p <= 0.01) level of a-ketoglutaric acid compared to mature DWX fruits. Tartaric acid was the main OA before expansion stages of these two loquat cultivars, and then malic acid was the predominant OA until ripening stages (Table 1). The largest proportion of tartaric acid in DWX loquat (58.00%) was reported at 100 DAFB, while it plateaued in CH loquat from 30 (57.37%) to 50 (51.58%) DAFB. The proportion of malic acid in DWX loquat reached its maximum value (82.58%) at half-ripe stage (160 DAFB), while that in CH loquat (60.98%) was recorded at breaker stage (80 DAFB) (Table 2). At harvest, tartaric acid (21.79%) and succinic acid (11.22%) had the second largest proportions in CH and DWX loquats, respectively (Table 1). The correlations between the TA, total acid, and OAs are summarized in Table 2. In this study, we set the threshold for statistically significant correlation between datasets as a p-value of less than 0.05 (p <= 0.05, *) or 0.01 (p <= 0.01, **). Strongly significantly positive (p <= 0.01) correlations were found among TA, total acid, and malic acid of the two loquat cultivars. Total acid was significantly positively correlated with tartaric acid in DWX (R2 = 0.390 *) and CH (R2 = 0.714 **) loquats. a-Ketoglutaric acid had significantly positive correlations with TA (R2 = 0.703 **) and total acid (R2 = 0.437 *) in DWX loquat, whereas it had significantly negative correlation with total acid (R2 = -0.612 **) in CH loquat. Citric acid had a significantly negative correlation with TA (R2 = -0.456 *) and a positive correlation with total acid (R2 = 0.616 **) in DWX and CH loquat, respectively. Extremely significantly positive correlations were found between succinic acid and TA (R2 = 0.866 **) and total acid (R2 = 0.950 **) in CH loquat (Table 2). 3.3. Comparative Analyses of Enzyme Activity for Organic Acid Metabolism of Dawuxing Loquat and Its Interspecific Hybrid The two loquat cultivars showed a similar dynamic change of PEPC activity during fruit development and ripening, with an initial gradual increase and then a steep drop at breaker stage, followed by a slight decline at the ripening stages . Although NAD-MDH activity showed a similar trend with PEPC activity, it peaked at 135 DAFB in DWX loquat and plateaued from 60 to 87 DAFB in CH loquat . NADP-ME activity of DWX and CH loquats increased steadily to a peak at half-ripe stage and then declined at full-ripe stage . CS activity exhibited an overall downward trend in DWX loquat and fluctuated in CH loquat with two peaks detected at 80 and 94 DAFB . ACO activity initially increased, then fluctuated in a small range with two peaks detected at the expansion and breaker stages, and gradually stabilized to a low level at ripening stages . NAD-IDH activity increased continuously until full-ripe stage in DWX loqua, t and it increased continuously to a peak at 87 DAFB in CH loquat . Significantly higher (p <= 0.05) enzyme activities of PEPC, NAD-MDH, and NADP-ME were observed across almost all stages in DWX loquat compared to CH loquat . Malic acid content was strongly positively (p <= 0.01) correlated with PEPC and NAD-MDH activities in the two loquat cultivars and NAD-IDH activity in CH loquat. a-Ketoglutaric acid content in DWX loquat had significantly positive association with NAD-MDH (R2 = 0.405 *) and NADP-ME (R2 = 0.423 *) activities and strongly significantly negative association with CS activity (R2 = -0.642 **). However, the a-ketoglutaric acid content in CH had a strongly significantly positive association with NADP-ME (R2 = 0.908 **) and NAD-IDH (R2 = 0.907 **) and had significantly negative association with ACO (R2 = -0.420 *). Citric acid had strongly significantly negative (p <= 0.01) correlations with NADP-ME and NAD-IDH in the two loquat cultivars and significantly positive correlations with CS (R2 = 0.751 **) in DWX and NAD-MDH (R2 = 0.414 **) in CH. Total acid was extremely significantly positively (p <= 0.01) correlated with PEPC, NAD-MDH, and ACO activities and positively (p <= 0.05) correlated with NADP-ME in the two loquat cultivars. An extremely significantly negative (p <= 0.01) correlation was observed between total acid and NAD-IDH activity (Table 3). 3.4. Comparative Analyses of Gene Expression for Organic Acid Metabolism of Dawuxing Loquat and Its Interspecific Hybrid In total, expressions of forty genes associated with OA metabolism were analyzed using qRT-PCR . The association between OAs and the expressions of related genes are summarized in Table 4. 4. Discussion 4.1. Characteristics of Fruit Growth and Development in Dawuxing Loquat and Its Interspecific Hybrid Common loquat trees bloom in the cold autumn and early winter . In total, common fruits take five to six months to mature, depending on the variety and environmental conditions. In this study, there was little increase in mass or volume of young fruit, which is called the lag phase or lag period. After wintering, common loquat fruits expanded rapidly and the fruit growth rate accelerated. Fruit growth tended to be stable after breaker stage . The fruit development and ripening of DWX loquat fitted a classic single sigmoid curve as previously reported in loquats . Bangal loquat was the male parent of CH loquat . Although it can bloom in Sichuan Province, it cannot bear fruit in this area based on our more than ten years of observation. Therefore, the OA dynamic changes of bangal loquat were not investigated in this study. CH loquat blooms in spring, and its fruit growth escaped chilling injury in winter. There was no lag phase between the fruitlet and expansion stages. Therefore, the development and ripening of CH loquat fruit exhibited a nonclassical single-sigmoid pattern . 4.2. Organic Acid Accumulation in Dawuxing Loquat and Its Interspecific Hybrid Loquat fruits have received constantly increasing attention from the consumers and growers for the nutritional properties and unusual phenology . Fruit acidity is among the most important quality attributes and largely depends on the accumulation of OAs, such as malic, citric, tartaric, and succinic acids . The compositions and contents of OAs are important factors directly influencing taste and organoleptic characteristics, namely sourness and flavor . OA composition varies widely in the pulp of different fruit species; however, it is generally accepted that malic and citric acids are the predominant OAs in most ripe fruits . For example, malic acid is the most predominant OA and contributes significantly to the favorability and palatability of apple , peach , and loquat , while citric acid is the major OA in citrus and passion fruit . In the present study, the malic acid content accounted for 77.55% and 48.59% of the total acid of DWX and CH loquats at harvest, respectively . At harvest, succinic acid (11.22%) and tartaric acid (21.79%) had the second largest proportion in DWX and CH loquats, respectively (Table 1), while the rest, belonging to other OAs, were present in negligible amounts . Similar compositions of malic acid representing 70-80% of the total acid were found in the Jiefangzhong loquat . Variety differences might lead to differences in OA compositions and contents . In this study, all trees were grown under identical natural conditions and received the same horticultural management. Therefore, we demonstrated in our study that the main difference in OA compositions and contents is closely related to the loquat cultivar. Our results showed that malic acid was not always the predominant OA compound throughout the loquat fruit development and ripening. For example, a high concentration of tartaric acid was observed in the early development stages . OA accumulation is accompanied by the synthesis and degradation processes . Because OAs share the same precursor, the phosphoenolpyruvate , we could hypothesize that phosphoenolpyruvate is preferentially used for other OA synthesis early in loquat fruit development and then for malic acid synthesis later. This reflected the predominance of malic acid as loquat fruits developed and matured. OA accumulated at the early stages of loquat fruit development and decreased during the later stages , which was similar to most studies . 4.3. Organic Acid Synthesis, Degradation, and Transport-Related Enzyme Activity and Gene Expression in Dawuxing Loquat and Its Interspecific Hybrid To elucidate the molecular mechanism underlying the difference of OA metabolism in the two loquat cultivars, correlation analyses between OA accumulation and enzyme activity and relative gene expression were performed and results were divided into positive and negative correlations. OA accumulation in fruits is determined by the balance of biosynthesis, degradation, and vacuolar storage and is strongly connected to the activities of multiple metabolic enzymes . In the two loquat cultivars, malic acid accumulation was significantly positively correlated with the enzyme activities of PEPC and NAD-MDH (Table 3). Significantly higher (p <= 0.05) activities of PEPC and NAD-MDH were observed across almost all stages in DWX loquat compared to low activities of them in CH loquat . In addition, malic acid content was positively correlated with the expressions of PEPC and NAD-MDH in the two cultivars (Table 4). Malic acid is mainly synthesized in the cytosol and is catalyzed by PEPC and NAD-MDH, and cytosolic NADP-ME has been suggested to participate in malic acid degradation . In addition, the results agreed that the decreases in these enzyme activities reduced the rate of malic acid synthesis along with fruit maturation . These results here demonstrated that PEPC and NAD-MDH are key enzymes that participate in malic acid metabolism in loquat and the low activities of PEPC and NAD-MDH was one of important reasons for the low malic acid content in CH loquat. In the first step of the tricarboxylic acid (TCA) cycle, citric acid is synthesized through the condensation of acetyl-CoA with oxaloacetate, which is catalyzed by CS . Overall, citric acid of the two cultivars accumulated in young loquat fruits and decreased along with fruit ripening . The changes of citric acid content in CH loquat were partly consistent with the activity of CS, because two unique peaks at 80 and 94 DAFB were observed . Citric acid dynamics in DWX loquat were significantly positively correlated with CS activity (Table 3), demonstrating the contribution of CS enzyme in citric acid biosynthesis in DWX loquat. These differences in the OA content between the two cultivars may be attributable to the difference in activities of multiple enzymes (Table 3). Citric acid degradation is first catalyzed by ACO into isocitrate via the intermediate product cis-aconitate and then metabolized into 2-oxoglutarate by NADP-IDH . NADP-ME has been suggested to be involved OA degradation during fruit ripening of several species . A few studies reported the promoting role of NAD-IDH in citric acid decomposition . Citric acid changes during fruit development, and ripening of Actinidia eriantha had no contrary trends and correlations with the NAD-IDH . A positive correlation occurred between ME activity and citric acid content in melon fruit development and ripening and ME activity increased over time . In this study, a significantly negative correlation between citric acid and NAD-IDH and NADP-ME (Table 3) supported that they are key enzymes for citric acid decomposition in loquat. Additionally, NAD-IDH and NADP-ME activities were significantly positively correlated with a-ketoglutaric acid accumulation (Table 4). Total acid content was significantly highly positively (p <= 0.01) correlated with the expressions of PEPC, PEPC2, NAD-MDH, ATP-CS, ATP-CS a1, VHA-C, ALMT1, ALMT12, and ALMT14 and negatively (p <= 0.01) correlated with the expressions of NADP-ME2, ALMT3, and ALMT 11 in the two cultivars (Table 4). VHA-C, and VHA-F belonged to the vacuolar H+-ATPase family and had the capability of maintaining the acid pH by a proton pump and participating in transportation across the tonoplast . ALMTs are aluminum-activated malate transporters and involved in diverse physiological processes . In summary, the difference in DWX loquat and its interspecific hybrid could be attributed to the coordinated regulation of multiple genes and enzymes associated with distinct stages of OA metabolism. 5. Conclusions Fruit acid is a critical contributor to fruit quality. In this study, the dynamic changes in fruit OA content during the fruit development and ripening stages of DWX loquat and its interspecific hybrid were compared, as well as the corresponding enzyme activity and gene expression. OA accumulated at the early stages of loquat fruit development and decreased during the later ripening stages. TA was significantly lower (p <= 0.01) in CH loquat than in DWX loquat. Malic acid was the predominant OA compound at fruit ripening stages, followed by succinic acid and tartaric acid in DWX and CH loquats, respectively. PEPC and NAD-MDH are key enzymes that participate in malic acid metabolism in loquat, and the low activities of PEPC and NAD-MDH was one of the important reasons for the low malic acid content in CH loquat. The difference in DWX and its interspecific hybrid could be attributed to the coordinated regulation of multiple genes and enzymes associated with distinct stages of OA metabolism. The data obtained here serves as an important foundation for future genetic improvements or cultural practices. Supplementary Materials The following supporting information can be downloaded at Figure S1: Dynamic changes in expressions of forty genes related to organic acid metabolism during different stages of fruit development and ripening in Dawuxing and its interspecific hybrid. The stages on the x-axis correspond to those presented in Figure 1. Values are means +- SD of three biological replicates. Figure S2: Figure S1 continued. Table S1. Primers used for quantitative real-time polymerase chain reaction in this study. Table S2. Authentic standard organic acid compounds used in HPLC analysis and their equations of standard curves. Click here for additional data file. Author Contributions Conceptualization, Q.D.; methodology, H.D., X.L. (Xuelian Li), Y.W., Q.M., Y.Z., Y.X. and M.C.; software, X.L. (Xuelian Li), H.Z., H.X., D.L., X.L. (Xiulan Lv) and J.W.; writing--original draft preparation, H.D.; writing--review and editing, H.D. and Q.D.; supervision, Q.D. and X.L. (Xuelian Li) is co-first author of this paper and contributed equally with H.D. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data and materials supporting the conclusions of this study are included within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The current known metabolic pathways for organic acids in fleshy fruits. Abbreviations: acetyl coenzyme A, Ac-CoA; aconitase, ACO; coenzyme A, CoSAH; citrate synthase, CS; 3-deoxy--heptulosonate 7-phosphate, DAHP; dehydroquinate dehydratase, DHD; 3-dehydroquinate synthase, DQS; DAHP synthase, DS; erythrose-4-phosphate, E4P; fumarase, FUM; isocitrate lyase, ICL; isocitrate dehydrogenase, IDH; acid dehydrogenase complex, KGDC; malate dehydrogenase, MDH; malic enzyme, ME; malate synthase, MS; oxaloacetic acid, OAA; pyruvate dehydrogenation complex, PDC; phosphoenolpyruvate, PEP; PEP carboxylase, PEPC; PEP carboxykinase, PEPCK; pyruvate kinase, PK; quinate dehydrogenase, QDH; succinate dehydrogenase, SDH; shikimate dehydrogenase, SKD; succinate thiokinase, STK; vacuolar-type H+-ATPase, VHA; vacuolar-type H+-Ppase, VHP. Dashed arrows indicate organic acid transport. Figure 2 Fruit phenotype (A), weight (B), shape index (C), and color changes (D-F) during fruit development and ripening of Dawuxing and Chunhua loquats. The x axis in (A) presents days after full bloom (DAFB) and the longitudinal section of fruits corresponding to each DAFB are shown in (A). The x axes in (B-F) represent different developmental stages of loquat fruits. The asterisks in the line charts indicate significant differences (*: p <= 0.05; **: p <= 0.01). Figure 3 Dynamic changes of titratable acid (A), total acid (B), malic acid (C), tartaric acid (D), succinic acid (E), oxalic acid (F), citric acid (G), and a-ketoglutaric acid (H) contents at different stages during fruit development and ripening of Dawuxing and Chunhua loquats. The stages on the x-axis corresponded to those presented in Figure 1. The asterisks in the line charts indicate significant differences (*: p <= 0.05; **: p <= 0.01). Figure 4 Dynamic changes of (A) phosphoenolpyruvate carboxykinase (PEPC), (B) NAD-malate dehydrogenase (NAD-MDH), (C) NAD-malic enzyme (NAD-ME), (D) citrate synthase (CS), (E) aconitase (ACO), (F) NADP-isocitrate dehydrogenase (NAD-IDH) enzyme activities at different stages during fruit development and ripening of Dawuxing and Chunhua loquats. The stages on the x-axis corresponded to those presented in Figure 1. The enzyme activities were expressed as units of activity per g fresh weight. The asterisks in the line charts indicate significant differences (*: p <= 0.05; **: p <= 0.01). foods-12-00911-t001_Table 1 Table 1 The proportions of organic acids at different stages of fruit development and ripening of Dawuxing and Chunhua loquats. Stage a Oxalic Acid Tartaric Acid Malic Acid a-Ketoglutaric Acid Citric Acid Succinic Acid DWX CH DWX CH DWX CH DWX CH DWX CH DWX CH S1 15.21 12.43 26.52 57.37 20.23 6.41 0.82 0.61 18.17 3.64 19.05 19.55 S2 12.06 43.64 11.52 0.91 15.06 16.81 S3 10.28 9.37 46.91 51.58 10.83 16.08 1.14 0.77 14.83 2.80 16.01 19.41 S4 8.61 3.75 58.00 34.06 7.17 40.60 1.15 0.70 10.50 1.81 14.57 19.07 S5 4.16 2.40 28.64 24.01 56.57 47.16 0.89 0.59 2.02 1.55 7.70 24.28 S6 2.19 3.05 11.17 18.54 80.48 60.98 0.70 0.90 1.09 1.60 4.37 14.93 S7 2.20 4.16 2.93 11.36 81.92 57.64 1.70 2.58 1.96 3.16 9.29 21.09 S8 3.57 7.17 2.02 17.97 82.48 56.03 2.73 4.55 2.61 4.76 6.59 9.52 S9 3.33 8.13 1.99 21.79 77.51 48.59 2.99 5.75 3.42 4.52 10.76 11.22 Note: a The stage numbers in this column corresponded to those presented in Figure 1A. Abbreviations: Dawuxing, DWX; Chunhua, CH. foods-12-00911-t002_Table 2 Table 2 Correlations between the titratable acid, total acid, and organic acids. Index Titratable Acid Total Acid Dawuxing Chunhua Dawuxing Chunhua titratable acid 1 1 0.883 ** 0.940 ** oxalic acid -0.269 0.093 0.160 0.383 tartaric acid 0.005 0.457 * 0.390 * 0.714 ** malic acid 0.948 ** 0.886 ** 0.789 ** 0.704 ** a-ketoglutaric acid 0.703 ** -0.366 0.437 * -0.612 ** critic acid -0.456 * 0.348 -0.054 0.616 ** succinic acid -0.087 0.866 ** 0.301 0.950 ** Note: * and ** indicate that the correlation coefficients are significant at 0.05 and 0.01 levels, respectively. The values without asterisks denote p > 0.05. foods-12-00911-t003_Table 3 Table 3 Correlation analysis of organic acids with related enzyme activities. Index PEPC NAD-MDH NADP-ME CS ACO NAD-IDH malic acid DWX 0.676 ** 0.808 ** 0.167 -0.308 0.369 0.169 CH 0.570 ** 0.756 ** 0.251 -0.247 0.224 0.793 ** a-ketoglutaric acid DWX 0.298 0.405 * 0.423 * -0.642 ** 0.228 0.287 CH -0.177 -0.225 0.908 ** -0.105 -0.420 * 0.907 ** citric acid DWX -0.020 -0.176 -0.817 ** 0.751 ** 0.234 -0.805 ** CH 0.098 0.414 * -0.770 ** 0.159 0.200 -0.766 ** total acid DWX 0.947 ** 0.960 ** -0.435 * 0.200 0.794 ** -0.314 CH 0.693 ** 0.872 ** -0.505 ** 0.202 0.730 ** -0.731 ** Note: * and ** indicate that the correlation coefficients are significant at 0.05 and 0.01 levels, respectively. The values without asterisks denote p > 0.05. foods-12-00911-t004_Table 4 Table 4 Correlation analysis of organic acids with related genes expression. Genes Malic Acid a-Ketoglutaric Acid Citric Acid Total Acid DWX CH DWX CH DWX CH DWX CH PEPC 0.865 ** 0.753 ** 0.532 ** -0.019 -0.567 ** 0.178 0.647 ** 0.657 ** PEPC2 0.275 0.198 -0.189 -0.685 ** 0.478 * 0.624 ** 0.726 ** 0.692 ** NAD-MDH 0.792 ** 0.578 ** 0.545 ** -0.453 * -0.262 0.499 * 0.707 ** 0.820 ** NADP-ME 0.235 -0.215 0.568 ** -0.536 ** -0.540 ** 0.458 * -0.002 0.283 NADP-ME2 -0.186 -0.495 * -0.303 0.664 ** -0.486 * -0.742 ** -0.623 ** -0.925 ** NADP-ME4 0.376 -0.176 0.765 ** -0.205 -0.637 ** -0.046 0.109 -0.051 CS -0.271 0.769 ** -0.126 -0.315 0.675 ** 0.199 0.152 0.801 ** ATP-CS a1 0.711 ** 0.557 ** 0.355 -0.194 -0.229 0.160 0.873 ** 0.497 * ATP-CS a2-1 0.477 * -0.030 0.825 ** 0.321 -0.468 * -0.189 0.187 -0.219 ATP-CS b2 0.388 * 0.442 * 0.322 -0.208 -0.055 0.199 0.591 ** 0.402 ACO 0.300 0.457 * 0.675 ** -0.767 ** -0.596 ** 0.616 ** -0.097 0.858 ** NAD-IDH1 0.707 ** -0.053 0.874 ** -0.380 -0.547 ** 0.421 * 0.490 ** 0.299 NAD-IDH5 0.436 * 0.228 0.793 ** 0.360 -0.454 * -0.027 0.124 0.070 tDT2 0.014 -0.383 -0.259 0.616 ** 0.394 * -0.250 0.108 -0.601 ** VHA-A 0.188 0.094 0.520 ** 0.021 0.019 0.201 0.371 0.186 VHA-A3 0.823 ** -0.556 ** 0.624 ** -0.515 * -0.380 0.628 ** 0.681 ** -0.012 VHA-B2-1 0.501 ** 0.226 0.843 ** -0.080 -0.510 ** 0.171 0.240 0.338 VHA-B2-2 -0.420 * 0.119 -0.480 * 0.301 -0.035 -0.224 -0.556 ** -0.119 VHA-C -0.073 -0.104 -0.138 -0.630 ** 0.633 ** 0.766 ** 0.456 * 0.462 * VHA-D2 0.491 ** -0.242 0.766 ** -0.364 -0.435 * -0.043 0.194 -0.061 VHA-E1 -0.288 -0.275 0.323 -0.171 0.163 0.369 -0.334 0.108 VHA-F -0.306 -0.451 * -0.103 -0.498 * 0.618 ** 0.569 ** 0.174 0.104 VHP1 0.259 -0.584 ** 0.315 0.254 -0.815 ** -0.181 -0.285 -0.633 ** ALMT1 0.159 0.027 0.175 -0.824 ** 0.148 0.778 ** 0.571 ** 0.673 ** ALMT2 -0.483 * -0.347 -0.097 -0.286 0.574 ** 0.123 -0.137 -0.051 ALMT3 -0.150 -0.473 * 0.295 0.472 * -0.375 -0.486 * -0.567 ** -0.735 ** ALMT4 -0.588 ** -0.251 -0.477 * -0.348 0.748 ** 0.367 -0.140 0.165 ALMT5 0.056 -0.242 -0.374 -0.366 0.509 ** 0.383 0.298 0.167 ALMT6 0.183 -0.800 ** 0.081 -0.127 0.011 0.261 0.019 -0.460 * ALMT7 0.444 * 0.352 0.572 ** -0.216 -0.715 ** 0.120 0.096 0.473 * ALMT8 0.700 ** -0.405 * 0.855 ** -0.001 -0.652 ** -0.466 * 0.338 -0.513 * ALMT9 -0.078 -0.489 * 0.283 -0.683 ** 0.233 0.818 ** 0.121 0.208 ALMT10 0.580 ** -0.345 0.089 -0.736 ** 0.233 0.896 ** 0.771 ** 0.335 ALMT11 0.003 -0.469 * 0.471 * 0.745 ** -0.533 ** -0.775 ** -0.474 * -0.940 ** ALMT12 -0.070 0.072 0.117 -0.830 ** 0.605 ** 0.786 ** 0.416 * 0.684 ** ALMT13 -0.193 -0.220 -0.032 -0.805 ** 0.573 ** 0.827 ** 0.223 0.481 * ALMT14 0.405 * -0.088 0.068 -0.857 ** 0.331 0.873 ** 0.619 ** 0.631 ** ALMT15 0.401 * -0.243 0.806 ** -0.332 -0.398 * 0.322 0.138 0.130 ALMT16 0.338 -0.398 -0.131 -0.686 ** 0.267 0.847 ** 0.623 ** 0.245 ALMT17 -0.351 -0.579 ** -0.654 ** 0.429 * 0.493 ** -0.423 * -0.233 -0.775 ** Note: * and ** indicate that the correlation coefficients are significant at 0.05 and 0.01 levels, respectively. 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PMC10000457 | We aim to evaluate the potential protective role of intravesical Bacillus Calmette-Guerin (BCG) against SARS-CoV-2 in patients with non-muscle invasive bladder cancer (NMIBC). Patients treated with intravesical adjuvant therapy for NMIBC between January 2018 and December 2019 at two Italian referral centers were divided into two groups based on the received intravesical treatment regimen (BCG vs. chemotherapy). The study's primary endpoint was evaluating SARS-CoV-2 disease incidence and severity among patients treated with intravesical BCG compared to the control group. The study's secondary endpoint was the evaluation of SARS-CoV-2 infection (estimated with serology testing) in the study groups. Overall, 340 patients treated with BCG and 166 treated with intravesical chemotherapy were included in the study. Among patients treated with BCG, 165 (49%) experienced BCG-related adverse events, and serious adverse events occurred in 33 (10%) patients. Receiving BCG or experiencing systemic BCG-related adverse events were not associated with symptomatic proven SARS-CoV-2 infection (p = 0.9) nor with a positive serology test (p = 0.5). The main limitations are related to the retrospective nature of the study. In this multicenter observational trial, a protective role of intravesical BCG against SARS-CoV-2 could not be demonstrated. These results may be used for decision-making regarding ongoing and future trials. non-muscle invasive bladder cancer Bacillus Calmette-Guerin SARS-CoV-2 infection This research received no external funding. pmc1. Introduction The emergence of a novel coronavirus in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly turned into a dramatic global pandemic. However, the recent advent of effective vaccines against SARS-CoV-2 seems to have mitigated the effects of the pandemic. Bacillus Calmette-Guerin (BCG) is a vaccine that was developed in 1921 to provide immunity against tuberculosis, a bacterial infection that primarily affects the lungs. The vaccine is produced by attenuating a strain of Mycobacterium bovis, which is a bacterium closely related to the one that causes tuberculosis. The attenuated bacteria used in BCG are weakened to the point that they cannot cause disease, but are still able to stimulate the immune system to produce a response against tuberculosis . Since its introduction, BCG has become one of the most widely used vaccines worldwide, especially in countries with high tuberculosis rates. One of the remarkable benefits of the BCG vaccine is that it not only protects against tuberculosis, but also against other infectious diseases. This has been observed since the beginning of the last century, when studies showed that BCG vaccination was associated with a significant reduction in infant mortality rates . The reason for this more general protection has yet to be fully understood, but it is believed that the immune response triggered by the BCG vaccine provides a level of non-specific protection against other infectious agents. This is thought to occur because the BCG vaccine induces a robust activation of the immune system, leading to the production of cytokines and other immune mediators that enhance the ability of the immune system to combat a wide range of pathogens . In summary, the BCG vaccine has been shown to be highly effective in preventing tuberculosis, and also provides a level of non-specific protection against other infectious diseases. This has made the BCG vaccine a valuable tool in public health, particularly in regions with highly prevalent infectious diseases . Indeed, evidence from the beginning of the last century demonstrates that BCG vaccination could reduce infant mortality by up to 50%, not only as a direct consequence of the induced immune response against Mycobacterium tuberculosis, but also due to more general protection against unrelated infectious agents . Since then, the cross-reactivity of BCG has been further investigated. BCG has been shown to reduce the level of yellow fever vaccine viremia after vaccination through the induction of cytokine responses, with a crucial role for IL-1B . Moreover, BCG vaccination before influenza vaccination resulted in a more pronounced increase and accelerated induction of immune response against the H1N1 vaccine strain . The phase III ACTIVATE trial aimed to assess the efficacy of the BCG vaccine in diminishing the incidence of new infections in the elderly ; the interim analysis revealed a 53% decrease in new infections and an 80% decrease in respiratory tract infections in the BCG group. Based on these considerations and on the observation that an inverse correlation between BCG vaccination coverage and SARS-CoV-2-associated morbidity and mortality has been reported in countries such as Japan , several trials assessing the potential protective role of BCG vaccination against SARS-CoV-2 have been initiated. Intravesical BCG represents the standard treatment for high-risk and selected intermediate-risk non-muscle invasive bladder cancer (NMIBC) patients . Unfortunately, side effects during BCG treatment are not unusual. While most patients experience none or mild events such as symptoms of cystitis, hematuria and general malaise with transient fever, a small percentage of patients develop severe adverse events (mainly persistent high-grade fever, arthralgia and arthritis) as a consequence of BCG hematogenous dissemination. Therefore, we hypothesized that intravesical BCG might be protective against symptomatic SARS-CoV-2 infection, especially in those patients who experienced systemic adverse events during BCG treatment. We tested our hypothesis in a large multicenter cohort of NMIBC patients treated with adjuvant intravesical BCG in the year preceding the first and second waves of the SARS-CoV-2 pandemic at two tertiary urological centers in Northern Italy. 2. Materials and Methods 2.1. Study Population and Study Design We report results from a multicenter observational review board-approved study (00174/2020). Consecutive patients treated with intravesical adjuvant therapy for NMIBC between January 2018 and December 2019 at two Italian referral centers were included in the study. Enrolled patients were divided into two groups based on the received intravesical treatment regimen: those treated with intravesical BCG (BCG seed RIVM (Medac(r), D-20354 Hamburg, Germany; 2 x 108-3 x 109 CFU) (study group) and those treated with intravesical chemotherapy, this latter group serving as the control. The choice to select the control group among the bladder cancer population was made to minimize the risk of selection bias and retrieve as homogeneous a study population as possible (concerning median age, gender and lifestyle). According to international guidelines and recommendations, intravesical BCG was administered to high-risk and some intermediate-risk patients. In addition, intravesical adjuvant chemotherapy was administered in case of intermediate-risk disease, while single postoperative instillation of chemotherapy was given to low-risk patients. Variables collected included baseline demographic characteristics and those inherent to BCG treatments (number of instillations, maintenance scheme and tolerability profile). The study was conducted in three different steps:A phone interview was conducted among the study population between May 2020 and September 2020 (after the so-called "first SARS-CoV-2 wave"). Patients were asked to answer an ad hoc survey regarding SARS-CoV-2 infection previously built by the Infectious Disease Team (TL, SC and FDR). A serology test to highlight the presence of direct antibodies against COVID-19 (meaning, therefore, previous exposure to the virus) was offered to all patients who tested negative (molecular test) or had never tested for SARS-CoV-2 infection. Due to the occurrence of a second wave (greater than the first) of disease spread in Italy during autumn and winter 2020, all patients were again reached by phone and their profile of exposure to SARS-CoV-2 was updated. Patients who did not answer the survey were excluded from the study. 2.2. Endpoints The study's primary endpoint was the evaluation of SARS-CoV-2 disease incidence and severity among patients treated with intravesical BCG compared to the control group. The study's secondary endpoint was the evaluation of SARS-CoV-2 infection (estimated with serology testing) among the study groups. 2.3. Statistical Analysis Absolute numbers and proportions were used to describe categorical variables, while median and interquartile ranges (IQR) were used for continuous variables. Chi-square, Fisher exact and Kruskal-Wallis tests were used when appropriate to compare the populations. Logistic regression models were built to evaluate the predictive role of intravesical BCG in preventing SARS-CoV-2 disease and infection. Statistical analyses were performed using STATA 16 (Stata Corp., College Station, TX, USA). All tests were two-sided, and p < 0.05 was considered statistically significant. 3. Results Patients' baseline characteristics are listed in Table 1. Overall, 506 patients with NMIBC treated with adjuvant intravesical therapy were included in the study. Of these, 340 (67%) received intravesical BCG while 166 (33%) were treated with intravesical chemotherapy. Among the 340 patients treated with BCG, 165 (49%) experienced BCG-related adverse events (Table 2). The most-frequently reported adverse events were symptoms of cystitis, fever/general malaise and hematuria. Serious adverse events, possible expression of BCG dissemination, such as arthritis and high-grade persistent fever occurred in 19 (6%) and 14 (4%) patients, respectively. Among the patients treated with BCG, 185 (54%) reported symptoms consistent with possible SARS-CoV-2 infection (mainly flu-like symptoms and fever); however, this was confirmed with a positive molecular test in only 8 patients (2%). Similarly, 73 patients (44%) treated with intravesical chemotherapy experienced SARS-CoV-2-like symptoms and a SARS-CoV-2 infection was confirmed in 4 (2%) of them (Table 3). Overall, 320 patients (67%) underwent a serology test to highlight the presence of direct antibodies against SARS-CoV-2. Of these, 214 were treated with BCG and 104 with intravesical chemotherapy. A positive serology test was found in 15 patients (7%) of the BCG group and in 9 patients (9%) of the chemotherapy group (p = 0.6). Receiving BCG or experiencing systemic BCG-related adverse events were not associated with symptomatic proven SARS-CoV-2 infection (OR 0.98, 95% CI 0.29-3.29, p = 0.9) nor with a positive serology test (OR 0.77, 95% CI 0.37-1.61, p = 0.5). 4. Discussion The outbreak of the COVID-19 epidemic had a tremendous influence on the management of cancer . The BCG is a live attenuated vaccine that represents the most widely used vaccine in the world, assuring over 50% protection against lung respiratory diseases and over 80% protection against tuberculosis . Numerous studies have documented the BCG vaccine's cross-protective benefits against diseases unrelated to tuberculosis . The hypothesis of a protective role of BCG towards SARS-CoV-2 comes from multiple sources of evidence. First, the BCG vaccine has been shown to induce non-specific effects on the immune system, thus protecting against a wide range of infections other than tuberculosis. In three randomized controlled trials in Guinea-Bissau, the BCG vaccine was administered to low-weight neonates to reduce infant mortality rates, with an observed beneficial effect in the neonatal period . A meta-analysis of the three trials showed that BCG reduced mortality by 38% within the neonatal period and 16% by the age of 12 months, mainly due to reduced infectious disease mortality . Second, the BCG vaccine reduced yellow fever vaccine viremia (a single-stranded positive-sense RNA virus such as SARS-CoV-2) by 71% in humans and reduced the severity of mengovirus infection in mice . The ability of BCG to enhance the protection against unrelated infectious agents calls into question multiple mechanisms, such as the molecular similarity between BCG antigens and some viral antigens, the so-called heterologous immunity leading to the activation of bystander B and T cells, and the trained immunity resulting in an increasingly active immune response . Early evidence from the current SARS-CoV-2 pandemic highlighted different incidences and severities of disease across different countries, probably due to differences in genetic susceptibility, cultural behaviors, mitigation norms and healthcare systems. However, it has been proposed that a partial explanation of these differences may rely on different national policies regarding BCG vaccination . According to several epidemiological studies, the incidence of SARS-CoV-2 is four times higher in countries without universal BCG vaccination than those with this policy . However, as correctly highlighted by Desouky , observation/correlation does not mean causation. To fill this gap, several studies aiming to test the efficacy of BCG vaccination against SARS-CoV-2 in different populations such as healthcare workers or the elderly population have been recently published. In a retrospective study, BCG revaccination was shown to be protective against COVID-19 infections in high-risk healthcare workers. Specifically, none of the patients who received the BCG booster vaccination developed COVID-19 infection, compared to 8.6% in the unvaccinated group . In contrast, the results from a large cohort of Israeli adults who chose or chose not to receive the BCG vaccination in childhood did not show differences in the incidence of COVID-19 , Several randomized trials investigating the protective effect of BCG vaccination against SARS-CoV-2 were registered . The BADAS trial (NCT04348370), initiated in April 2020, aimed to randomize 1800 healthcare workers to receive BCG vaccination or placebo. The primary endpoint of the study was the incidence of SARS-CoV-2 infection and disease severity. The ACTIVATE-2 study was a multicenter, double-blind trial that randomized 301 volunteers aged >50 to receive vaccination with BCG versus placebo. The primary end points were the incidence of COVID-19 and the presence of anti-SARS-CoV-2 antibodies. At 6 months, individuals vaccinated with BCG showed a lower incidence of COVID-19 (OR 0.32 95% CI 0.13-0.79, p = 0.014) . In contrast, in a unicentric randomized phase II clinical trial, Dos Anjos et al. did not find a statistically significant lower rate of incidence of COVID-19 positivity in healthcare workers revaccinated with M. bovis BCG Moscow . Similarly, a Dutch multicentric randomized trial compared the number of days of unplanned absenteeism for any reason during the COVID-19 pandemic in healthcare workers randomized to receive BCG vaccination or placebo. Again, no protective role of BCG vaccination emerged . A third randomized double-blind placebo-controlled trial enrolling healthcare workers found that BCG vaccination did not have a protective role against COVID19 infection or symptoms . Lastly, the protective role of the genetically modified BCG vaccine VPM1002 was evaluated in a phase III randomized double-blind placebo-controlled multicenter clinical trial. VPM1002 is a modified BCG vaccine with improved immunogenicity and safety profile. However, although the authors reported a lower number of days with severe RTI in the elderly vaccinated with VPM1002, they did not find a statistically significant difference between groups . It should be considered the cited trials only focused on the role of BCG vaccination. The urological community has been using intravesical BCG as standard adjuvant treatment for patients with high-risk NMIBC since 1970 . Despite the intravesical administration of BCG, some is absorbed and is able to induce systemic effects. Within 2-8 h of intravesical BCG instillation, a peak of cytokines and chemokines leading to the recruitment of immune cells to the bladder can be observed. Moreover, intravesical BCG stimulates the humoral immune response by increasing IgG levels against tuberculin and mycobacterial heat shock proteins . Finally, more than 40% of patients receiving intravesical BCG experience conversion of a previously negative tuberculin skin test . Therefore, there is evidence to support the systemic immunological impact of intravesical BCG. Patients treated with intravesical BCG showed a lower fatality rate (death/cases with respect to overall population) in a small retrospective Chilean study. However, the results are limited by the weak study design . Contrastingly, Karabay et al. compared the incidence of SARS-CoV-2 infection in bladder cancer patients treated with or without intravesical BCG; in this study, no differences emerged between groups . Finally, no evidence of BCG's protective effect was shown in a recent retrospective study that included 2803 patients treated with intravesical BCG in an Italian region . In recent years, several vaccines targeting the SARS-CoV-2 virus have been developed . Although these vaccines have demonstrated high efficacy and have had a substantial positive impact on mitigating the pandemic, the durability of their protective effect over the long term remains uncertain. Investigating the potential adjunctive role of BCG enhancing the immune response to COVID-19 vaccination may be an area of interest for future research. In this multicenter observational trial, a protective role of intravesical BCG against SARS-CoV-2 infection and disease could not be demonstrated. However, we found that patients treated with intravesical BCG for NMIBC harbor the same risk of contracting the SARS-CoV-2 infection and developing symptomatic disease as patients who did not receive intravesical immunotherapy. These findings were also confirmed in the subgroup of patients who experienced severe BCG-related adverse events due to a hematogenous BCG dissemination. These findings may be used to guide decision-making regarding ongoing and future trials aiming to explore the role of BCG in the prevention of SARS-CoV-2 infection. Despite the novelty and significance of our study, it is important to note that it is not without limitations. Perhaps the most significant of these limitations is the inherent observational nature of the study design, which prevents us from drawing causal conclusions about the relationships we observe between intravesical BCG and SARS-CoV-2. Another limitation of our study is related to the testing for SARS-CoV-2. First, we were not able to test all included patients for SARS-CoV-2, as the choice to undergo a serology test was left to the discretion of the patients. This introduces a potential selection bias. Furthermore, it is important to note that the serology tests were performed after the so-called "first wave" of the pandemic. As a result, it is possible that a higher number of patients may have contracted SARS-CoV-2 in an asymptomatic form during the second and third waves of the pandemic, with a possible impact on the results of the study. This temporal limitation may have led to an underestimation of the true prevalence of SARS-CoV-2 infection in the studied population, which could affect the accuracy of our findings. Despite these limitations, our study provides valuable insights into the potential role of intravesical BCG and the risk of SARS-CoV-2 infection. However, it is important to acknowledge these limitations and the need for additional studies to further elucidate the relationship between these variables and SARS-CoV-2 infection. 5. Conclusions In this multicenter observational trial, which aimed to investigate the potential protective effect of intravesical BCG against SARS-CoV-2, the data did not demonstrate a significant protective effect. While the results are not definitive, they suggest that intravesical BCG is unlikely to be a reliable strategy for preventing SARS-CoV-2 infection. These results may have implications for decision-making regarding ongoing trials and future studies that might explore the adjunctive role of BCG in enhancing the immune response to COVID-19 vaccination. However, it is important to note that additional studies are needed to fully elucidate the potential of BCG and other agents in this regard. Author Contributions Conceptualization, F.S., R.H., F.G.D.R., A.M.K. and P.G. Data collection or management, R.C., P.P.A., P.C., M.L., V.B., S.M. (Stefano Mancon), S.M. (Simone Mazzoli), G.P., M.D.B., M.R., S.L., T.L., S.C., N.M.B. and B.L. Data analysis F.S. Writing/original draft, F.S., R.H. and P.G. Writing/review and editing, All authors. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethical Committee Citta della Salute e della Scienza di Torino (00174/2020). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. cancers-15-01618-t001_Table 1 Table 1 Descriptive characteristics for the cohort of 506 patients with non-muscle invasive bladder cancer treated with adjuvant intravesical therapy between January 2018 and December 2019. Variables Total Type of Intravesical Treatment p-Value BCG Chemotherapy Number of patients, n (%) 506 340 (67) 166 (33) Median age (IQR), years 73 (67-79) 74 (68-80) 72 (64-78) 0.05 Gender, n (%) Female Male 87 (17) 419 (83) 51 (15) 289 (85) 36 (22) 130 (78) 0.06 Median number of BCG induction instillations (IQR) - 6 (6-6) - - Type of adjuvant chemotherapy treatment, n (%) - Induction cycle - - 138 (83) Single postoperative instillation - - 28 (17) cancers-15-01618-t002_Table 2 Table 2 Adverse events reported during intravesical treatment with Bacillus Calmette-Guerin among the study group (n = 340). Symptoms Frequency, n (%) None 175 (51) Cystitis 112 (33) Hematuria 63 (19) Epididymitis 9 (3) Fever/general malaise 81 (24) Arthralgia/arthrititis 19 (6) High-grade persistent fever 14 (4) Symptoms requiring treatment 88 (26) cancers-15-01618-t003_Table 3 Table 3 SARS-CoV-2-like symptoms and SARS-CoV-2 disease characteristics among the study population. Symptoms are not exclusive; a patient may have developed more than one symptom. SARS-CoV-2-like Symptoms, n (%) BCG (n = 340) Chemotherapy (n = 166) p Value Flu-like symptoms in the last 90 days 53 (16) 24 (15) 0.8 Fever 30 (9) 8 (5) 0.1 Cough 26 (8) 10 (6) 0.5 Dry cough 9 (3) 8 (5) 0.2 Shortness of breath 7 (2) 2 (1) 0.5 Asthenia 17 (5) 6 (4) 0.4 Myalgia/arthralgia 8 (2) 5 (3) 0.7 Headache 4 (1) 3 (2) 0.6 Diarrhoea 7 (2) 1 (1) 0.2 Nausea/vomiting 7 (2) 3 (2) 0.6 Symptoms requiring hospitalization 4 (1) 1 (1) 0.6 Symptoms requiring medical examination 13 (4) 2 (1) 0.1 SARS-CoV-2 Disease, n (%) BCG (n = 340) Chemotherapy (n = 166) p value Contact with SARS-CoV-2-positive patients Molecular test for suspected SARS-CoV-2 infection Positive molecular test SARS-CoV-2 disease requiring hospitalization Length of stay, days SARS-CoV-2 pneumonia SARS-CoV-2 requiring intensive care unit 16 (5) 23 (7) 8 (2) 1 (0) 10 1 (0) 0 12 (7) 14 (8) 4 (2) 1 (1) 10 1 (1) 0 0.2 0.5 0.9 0.6 0.9 0.6 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000458 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050978 diagnostics-13-00978 Review [18F]FDG PET/CT in the Evaluation of Melanoma Patients Treated with Immunotherapy Mangas Losada Maria 1 Romero Robles Leonardo 1 Mendoza Melero Alejandro 1 Garcia Megias Irene 1 Villanueva Torres Amos 1 Garrastachu Zumaran Puy 1 Boulvard Chollet Xavier 1 Lopci Egesta 2 Ramirez Lasanta Rafael 1 Delgado Bolton Roberto C. 1* Vinjamuri Sobhan Academic Editor Pant Vineet Academic Editor 1 Department of Diagnostic Imaging (Radiology) and Nuclear Medicine, University Hospital San Pedro and Centre for Biomedical Research of La Rioja (CIBIR), 26006 Logrono, Spain 2 Nuclear Medicine, IRCCS Humanitas Research Hospital, 20089 Rozzano, Italy * Correspondence: [email protected] 04 3 2023 3 2023 13 5 97802 2 2023 25 2 2023 01 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Immunotherapy is based on manipulation of the immune system in order to act against tumour cells, with growing evidence especially in melanoma patients. The challenges faced by this new therapeutic tool are (i) finding valid evaluation criteria for response assessment; (ii) knowing and distinguishing between "atypical" response patterns; (iii) using PET biomarkers as predictive and response evaluation parameters and (iv) diagnosis and management of immunorelated adverse effects. This review is focused on melanoma patients analysing (a) the role of [18F]FDG PET/CT in the mentioned challenges; (b) the evidence of its efficacy. For this purpose, we performed a review of the literature, including original and review articles. In summary, although there are no clearly established or globally accepted criteria, modified response criteria are potentially appropriate for evaluation of immunotherapy benefit. In this context, [18F]FDG PET/CT biomarkers appear to be promising parameters in prediction and assessment of response to immunotherapy. Moreover, immunorelated adverse effects are recognized as predictors of early response to immunotherapy and may be associated with better prognosis and clinical benefit. FDG PET/CT immunotherapy melanoma response evaluation adverse events This research received no external funding. pmc1. Introduction Melanoma is one of the most aggressive tumours, presenting the highest global growth rate worldwide. The incidence of skin melanoma has increased consistently in fair-skinned people over the past 40 years. It is a challenging tumour that requires a multidisciplinary approach, in which nuclear medicine has a relevant role, including sentinel node biopsy and [18F]FDG PET/CT as part of the standard of care . Regarding [18F]FDG PET/CT, there is extensive evidence showing its efficacy in staging melanoma patients with advanced disease . [18F]FDG PET/CT has very high efficacy for detecting distant metastases, but it has limitations when evaluating the presence of microscopic disease in lymph nodes. Therefore, in the initial stages, [18F]FDG PET/CT is not useful for lymph node staging, but, in advanced disease with increased tumour burden, [18F]FDG PET/CT does detect lymphatic spread . On the other hand, immunotherapy, which is based on regulation of the immune system, has been a great advancement in recent decades in the field of oncological diseases. Given the immunogenic nature of melanoma, it is one of the tumours in which immunotherapy is proving more useful. Due to the relatively recent discovery of immunotherapy, there are still challenges that must be clarified, such as (a) finding valid evaluation criteria for response assessment; (b) knowing and distinguishing between "atypical" response patterns; (c) using PET biomarkers as predictive and response evaluation parameters as well as diagnosis and management of immunorelated adverse effects . For all, [18F]FDG PET/CT seems to be a useful tool given its ability to study metabolism of lesions and provide information that would not be obtained if based exclusively on morphological changes. However, these processes present as metabolic patterns not evidenced with conventional treatments. High-quality evidence is required to validate the role of [18F]FDG PET/CT in this setting and, for this, harmonization of the procedure is needed in order to make results comparable between centres and in different time points . The recently published guidelines on recommended use of [18F]FDG PET/CT in solid tumours undergoing immunotherapy have, therefore, become a valuable tool for adequate integration and reporting of this imaging modality in melanoma patients . The aim of this review is to analyse the role of [18F]FDG PET/CT in the evaluation of melanoma patients treated with immunotherapy, focusing on the main challenges, such as response assessment interpretation criteria, differentiating between "atypical" response patterns and the role of PET biomarkers in this setting. 2. Materials and Methods This is a non-systematic review of articles focusing on the utility of [18F]FDG PET/CT in melanoma patients treated with immunotherapy. The inclusion criteria were (a) original and review articles on [18F]FDG PET/CT in melanoma patients treated with immunotherapy; (b) published in scientific journals written in English and (c) including at least 20 melanoma patients. Exclusion criteria were (a) full article not available in English and (b) case reports and conference abstracts were not included. One of the selected articles is a recent meta-analysis on this topic, published in 2020 . The articles included in this meta-analysis were included in our systematic review, updating the literature search until the end of 2022. A flow chart of study selection is presented in Figure 1. 3. Evaluation Criteria for Response Assessment Traditionally, since [18F]FDG PET/CT for assessment of response in solid tumours has been implemented, multiple clearly defined parameters have been created with good clinical correlation and in terms of overall survival. The need to standardize the evaluation criteria in order to be able to apply them in clinical practice has fuelled in the last 20 years the development of a harmonized and reproducible approach to response evaluation, with the proposal of several new criteria for evaluation and interpretation issues, such as EORTC (European Organization for Research and Treatment of Cancer) and PERCIST (Positron Emission tomography Response Criteria in Solid Tumors) , which are commented on in more detail below. Regarding evaluation of response to immunotherapy, it presents different imaging characteristics compared to conventional chemotherapy, and, therefore, with its implementation in clinical practice, there was a need to standardize the evaluation criteria in order to be able to apply them in clinical practice. The most relevant criteria are summarized below. In 1999, EORTC established four criteria to report the observed results for evaluation of metabolic response that served as the basis for subsequent evaluations after initiation of treatment with a good clinical correlation. These criteria were (a) progressive metabolic disease (PMD) is classified as an increase in [18F]FDG tumour SUV greater than 25% within the defined tumour region in the initial scan, visible increase in the extent of [18F]FDG tumour uptake (20% in longest dimension) or new [18F]FDG uptake in metastatic lesions. (b) Stable metabolic disease (SMD) is classified as an increase in tumour [18F]FDG SUV of less than 25% or a decrease of less than 15% and no visible increase in [18F]FDG uptake tumour extent (20% in longest dimension). (c) Partial metabolic response (PMR) is classified as a reduction of a minimum of 15 +- 25% in tumour [18F]FDG SUV after one cycle of chemotherapy and greater than 25% after more than one treatment cycle. (d) Complete metabolic response (CMR) is classified as complete resolution of [18F]FDG uptake within the tumour volume so that it was indistinguishable from surrounding normal tissue . In 2009, PERCIST criteria published by Wahl et al., also included four metabolic categories. EORTC and PERCIST showed high agreement in different types of cancers despite the different approaches of each one. One of the main differences with the EORTC criteria is that PERCIST recommends using SUL instead of SUV, considering lean body mass instead of weight for the calculation. PERCIST criteria establish four categories: (a) CMR defined as disappearance of all metabolically active lesions; (b) PMR is considered for SULpeak reduction >=30% in the hottest target lesions; (c) SMD is applied when it is neither PMD nor PMR/CMR and (d) PMD is applied when SULpeak increases >=30% in the hottest target lesion and apparition of new lesions . These two evaluation criteria guidelines, EORTC and PERCIST, serve as the basis upon which the following evaluation criteria have been developed. In 2017, the PECRIT criteria (PET/CT Criteria for early prediction of Response to Immune checkpoint inhibitor Therapy) were published, focusing on the combination of both morphologic (contemplating a change in the sum of diameters of target lesions according to RECIST 1.1) and metabolic response (i.e., a reduction in the SULpeak >15.5% for the hottest lesion on PET) to assess the clinical benefit of immunotherapy. Clinical benefit includes (a) CR as per RECIST 1.1 (disappearance of all target lesions; reduction in short axis of target lymph nodes to <1 cm; no new lesions); (b) PR as per RECIST 1.1 (decrease in target lesion diameter sum >30%) and (c) SD: Does not meet other criteria plus change in SUL peak of the hottest lesion of <=15%. No clinical benefit is considered for cases with PMD that include change in SUL peak of the hottest lesion >15% and PD as per RECIST 1.1 (increase in target lesion diameter sum of >20% and at least 5 mm or new lesions) . Last, in 2018, PERCIMT (PET Response Evaluation Criteria for Immunotherapy) was introduced in 2018 for melanoma. The most remarkable change in these criteria is that the appearance of up to four new lesions, depending on their size, can be tolerated to obtain clinical benefit (CB) and support treatment continuation . The categories are (a) CMR: disappearance of all metabolically active lesions; (b) PMR: disappearance of some but not all metabolic lesions and no new lesions; (c) SMD: neither PMD nor PMR/CMR and (d) PMD: 4 or more new lesions (<1 cm in diameter), 3 or more new lesions (>1 cm), 2 or more new lesions (>1.5 cm in diameter). More recently, other alternative approaches to PERCIST have been used, including iPERCIST and immunotherapy-modified PERCIST5 (imPERCIST) . In the first case, for the iPERCIST criteria, introduction of the immune unconfirmed metabolic progressive disease (iuPMD) acts similarly to iRECIST , where subsequent scanning 4-8 weeks is required to confirm or discharge progression. As for imPERCIST criteria, the definition of PMD is reassigned to cases having an increase >30% in the sum of SULpeak of the target lesions (up to 5). 4. Distinguishing between "Atypical" Response Patterns Irruption of immunotherapy in clinical practice has opened very interesting treatment possibilities for oncological patients, but it has, in consequence, meant a new challenge in the field of medical imaging. As mentioned previously, new standardized criteria are needed to evaluate the response to these innovative therapies as their effects on the tumours differ to those conventionally observed with traditional cytotoxic treatments. Response criteria for evaluation of solid tumours treated with traditional cytotoxic treatments are focused on reduction or regression of tumour size/burden or decrease in its metabolic volume to categorise a response as favourable. However, immunotherapy causes non-conventional patterns of response. Four new atypical patterns have been described and should be recognized in order to better assess/evaluate a tumour's response. 4.1. Pseudoprogressive Disease (PPD) Initial enlargement in total tumour volume or onset of new lesions after initiating treatment followed by reduction in tumour burden should be considered pseudoprogression . It is important to highlight that this phenomenon is a reflection of stimulation of the immune response, not linked with real or true progression of a disease. It is caused by infiltration of the tumour environment by the host's immune activated cells, accompanied by a certain component of oedema, necrosis and haemorrhage . PPD normally takes place within the 4-6 weeks after treatment and can be classified as early or delayed based on time of advent (before or after 12 weeks of therapy). PPD was first described in melanoma patients during their treatment with Ipilimumab . In fact, the rate of pseudoprogression is higher in melanoma cases, with up to 10-15% of patients treated with anti-CTLA4 compared to less than 10% of incidence in those treated with anti-PD1 . Its appearance should also be considered in other entities, such as non-small cell lung cancer (NSCLC), renal cancer (RCC), urothelial carcinoma and head and neck squamous cell cancer (HNSCC) among others, although the rate is below 5%. This variance in incidence of pseudoprogression could be related to the idiosyncratic features of the different neoplasms and patients and distinct agents used. There are also publications referring to some particular locations of pseudoprogression and pseudoprogression occurring at different stages of treatment, not just at the beginning. At this point, it is important to distinguish when we are facing pseudoprogression instead of real progression. The key point should be to check the clinical condition of the patient: clinical improvement should lead to consider pseudoprogression over progression. The checklist proposed by the new guidelines is to be considered a useful help in interpretation and reporting of [18F]FDG PET/CT, particularly in case of atypical responses during immunotherapy. 4.2. Hyperprogressive Disease (HPD) Hyperprogression is defined as a considerable and early enlargement of tumour burden following introduction of immunotherapy. An example of hyperprogression is presented in Figure 2. Champiat et al. were the first group to describe this phenomenon in a subset of patients undergoing treatment with anti-PD-1 and anti-PD-L1 . Frequency of hyperprogression varies depending on tumour type and agent used, with rates of incidence within 4-29% in different studies and publications. Nowadays, there is not an established specific criterion to determine recognition of HPD. Consequently, it might be underdiagnosed. It is crucial to diagnose early this abnormal tumour expansion due to its importance in the clinical approach. This scenario leads to readjustment regarding therapy being necessary, including suspension of the active treatment and change to a second line of therapy. In general, it worsens prognoses, with lower global survival rates, and must be considered in patients with high-risk factors, such as elderly, numerous metastatic lesions and history of prior irradiation as well as certain mutations (such as murine double minute 2/4 proto-oncogene (MDM2/4) family amplification or epidermal growth factor receptor (EFGR) aberrations) . 4.3. Dissociated Response (DR) Growth of certain lesions accompanied by the paradoxical shrinkage in baseline lesions should be classified as a dissociated response. An example of dissociated response is presented in Figure 3. It could also be reported as mixed response or disproportional response . This is not really a novel pattern, having already been identified with traditional treatments (as platinum-based chemotherapy). DR has been described in different studies, with a rate not overcoming 10% overall . Interestingly, onset of DR has showed a potential association with favourable prognosis in comparison with patients developing a homogeneous progression. This subset of patients might obtain a benefit better by not discontinuing initial immunotherapy treatment. In addition, it is relevant to identify oligometastatic patients who may benefit from local therapies . 4.4. Sustained Response (SR) Immunotherapeutic agents are superior to conventional drugs due to their ability to induce enduring responses despite having completed the treatment. This manifestation has been observed in 10-25% of metastatic patients. According to classical criteria (RECIST or WHO criteria), the lack of either partial or complete radiological response was to be classified as treatment failure, with subsequent categorization of those patients as non-responders . Pons-Tostivint et al. demonstrated superiority of immune checkpoint inhibitors over other systemic treatments in terms of durable responses and overall survival. They also identified a major proportion of sustained response in the group of patients treated with anti-PD-1/PD-L1 agents . 5. Application of PET Biomarkers as Predictive and Response Evaluation Parameters Application of PET biomarkers as predictive and response evaluation parameters in evaluation of melanoma patients treated with immunotherapy has been studied in recent publications. [18F]FDG PET/CT imaging biomarkers can be classified based on three aspects: tumour burden, tumour glucose uptake and nontumoral hematopoietic tissue metabolism. The first group (tumour burden) includes three measures: metabolic tumour volume (MTV), total MTV (TMTV) and total lesion glycolysis (TLG). The second group (tumour glucose uptake) includes three measures: maximum standard uptake value (SUVmax), standardized uptake value corrected for lean body mass (SUL) and heterogeneity index of SUV (HISUV). The third group (nontumoral hematopoietic tissue metabolism) includes parameters focusing on medullary and extra-medullary haematopoiesis, such as spleen-to-liver maximum standard uptake value ratio (SLR) and bone marrow-to-liver maximum standard uptake value ratio (BLR) . A recent meta-analysis by Ayati et al. analysed patients with metastatic melanoma treated with immunotherapy, investigating the role of [18F]FDG PET/CT for predicting and monitoring immunotherapy response regardless of the kind of immunotherapy employed. This meta-analysis included 24 articles published between October 2014 and June 2020. They concluded that three of the parameters most used in PET, being MTV, TLG and SUL/SUV peak, could be a convenient tool to predict response in patients with metastatic melanoma. Regarding their analysis of [18F]FDG PET biomarkers, Ayati et al. divided the selected articles into two groups: one centred on the baseline [18F]FDG PET/CT parameters and the other focused on the metabolic changes between baseline and follow-up [18F]FDG PET/CT. In the first group that analysed baseline [18F]FDG PET/CT parameters for prediction of outcomes, the studies included found that MTV and TLG were associated with overall survival (OS) and progression-free survival (PFS) rates in most studies. The second group analysed the value of interval changes in baseline and late [18F]FDG PET/CT parameters as predictor of outcomes, taking into account clinically oriented indexes. The studies included reported that changes in SUVmax were not associated with differences in the outcomes. However, one study found that the absolute number of new focal hypermetabolic lesions was a better marker than changes in SUVmax. Regarding the individual studies published in this field, we have summarised the main findings of 13 original articles published since 2017 in Table 1 , presenting their main characteristics, endpoint and results. Most articles focus on the baseline [18F]FDG PET/CT and just a few articles focus on the interval changes between the baseline and follow-up [18F]FDG PET/CT. 5.1. Analysis Focused on the Baseline [18F]FDG PET/CT This first group, which analysed baseline [18F]-FDG PET/CT parameters for prediction of outcomes, included thirteen studies . The [18F]FDG PET/CT parameters analysed were MTV, BLR, SLR, SUVmax, SUVpeak, TLG and tumour heterogeneity index. Up to now, MTV is the main parameter showing prognostic value. Ito et al. found a significant correlation of MTV and TLG with OS as well as concluding that TMTV may be a strong independent prognostic factor. These same parameters were analysed in the study by Nakamoto et al. published in 2020, which reported a significant correlation with OS. In the study by Seban et al. published in 2019 , MTV also correlated with OS, concluding that a low tumour burden correlated with survival and objective response. They also evaluated nontumoral hematopoietic tissue metabolism, finding that not only TMTV but also BLR had significant and independent prognostic value, correlating inversely with OS and PFS. A possible explanation for the fact that increased metabolism in bone marrow can correlate with worse outcomes is that the bone marrow has cells relevant to some tumour formation mechanisms, such as neovascularization and priming of metastases . The study published in 2021 by Nakamoto et al. reported that BLR was an independent prognostic biomarker for OS and PFS. A stratified analysis, combining BLR with independent clinical factors with three categories, found a worse OS in the group with higher BLR and unfavourable clinical risk factors. Regarding BLR and MTV, there was a weak (0, 34) positive correlation between both. As in previous studies , MTV was associated with OS. Flavus et al. , who reported a correlation between MTV with OS, additionally analysed textural PET parameters using the radiomics with the same purpose of predicting outcomes. Forty-one image biomarker standardization initiative (IBSI)-compliant parameters were studied and only long zone emphasis (LZE) correlated with shorter OS, the same as MTV. Both parameters, MTV and LZE, were used to perform a prognostic score in which patients were categorized into three groups. On the contrary, Sanli et al. did not find correlation between MTV and OS. However, SUVmax, SUVpeak and TLG were associated with OS. Another parameter analysed, intratumoral metabolic heterogeneity, measured using the tumour heterogeneity (TH) index, also showed significant association with OS. Furthermore, SLR, a nontumoral hematopoietic tissue metabolism parameter, was analysed by Wong et al. and Seban et al. . Wong et al. reported that an SLR greater than 1.1 is associated with a poor outcome (OS and PFS) after ipilimumab but not after PDL-1. On the contrary, Seban et al. , did not find a significant association between SLR and OS. Regarding other parameters, Wong et al. reported that SUVmax was not associated with OS or PFS, whereas MTV was only significantly associated with OS when it was analysed as a continuous variable. Another study analysing SLR, by Sachpekidis et al. , differed from the previous ones described in that it evaluated early disease progression and immune activation related to confirmed progressive metabolic disease versus pseudoprogression instead of survival rates. Patients categorised as confirmed progressive metabolic disease showed higher SLRmean after the first two cycles of immunotherapy than those catalogued as pseudoprogression. In the analysis of SLRmean and SLRmax in baseline PET, there were no significant differences between patients classified as confirmed progressive metabolic disease and those classified as pseudoprogression. These results suggest that a higher SLR may be associated with a poor clinical outcome, as Wong et al. had also highlighted. Nobashi et al. analysed patients not only with melanoma but also with malignant lymphoma and renal cell carcinoma, finding no statistical differences between patients with and without clinical benefit and baseline SUVmax, MTV and TLG. On the other hand, in patients with clinical benefit, a significant decrease in PET parameters (SUVmax, MTV and TLG) of the first restaging PET/CT was observed, but not in patients with no clinical benefit. Finally, Schweighofer-Zwink et al. reported that metabolic parameters and tumour-to-background ratios (TBRs) were correlated with OS, not only in the baseline [18F]FDG PET/CT but also in the two follow-up [18F]FDG PET/CT scans, performed 3 and 6 months after immunotherapy. In the baseline [18F]FDG PET/CT, SULmax and SULpeak as well as most of TBRs were predictive for 3-year and 5-year OS rates. In the follow-up studies, MTV, TLG and most of the TBRs were predictive. On the other hand, changes in values of MTV, TLG and most of the TBRs from the baseline PET to the follow-up studies were prognostic. 5.2. Analysis Focused on the Interval Changes between Baseline and Follow-Up [18F]FDG PET/CT The second group, which analysed the value of interval changes in baseline and late [18F]FDG PET/CT parameters as predictor of outcomes, took into account clinically oriented indexes. Two articles evaluated changes between baseline [18F]FDG PET/CT and after starting immunotherapy using patients' clinical response as reference. These studies, by Cho et al. and Anwar et al. , were used as the basis to propose the PECRIT and PERCIMT, respectively. Regarding changes in SUVmax, no correlation with clinical response was observed, as described by Anwar et al. , who concluded that number of new lesions in PET may be a good response marker. When considering follow-up in patients undergoing treatment with checkpoint inhibitors for one year , use of metabolic information enabled better prediction of long-term benefit regardless of partial responses on morphological imaging. Moreover, five years after the 1-year PET in melanoma treated with anti-PD-1 therapy , [18F]FDG PET/CT could still predict progression better than CT, especially in those patients with residual disease on CT. In summary, [18F]FDG PET/CT biomarkers could be a promising parameter to predict outcome and assess response in these patients. Earlier prediction would provide the information necessary to adapt the treatment, while later assessment before ceasing treatment can help discontinue more safely immunotherapy. Therefore, in the near future, further evidence may support personalising patient management based on these biomarkers. 6. Diagnosis and Management of Immunorelated Adverse Effects Checkpoint inhibitors used in immunotherapy can cause inflammation of any tissue or organ, being responsible for immune-related adverse events (irAEs). With the increasing use of immunotherapy in clinical practice, irAEs are increasing as well. Immune-related toxicities vary in terms of their time of onset, severity, underlying biology and the way of use, either in monotherapy or combined therapy, which are often used in advanced or higher risk diseases . Severity of irAEs is characterized by grades , ranging from grade 1 to 5: (a) Grade 1-2: Include situations with very manageable symptoms, which can be treated just with corticosteroids. (b) Grade 3: Cases with moderate/severe symptoms, which will need to stop immunotherapy treatment and undergo hospitalization to be controlled and treated. (c) Grade 4: Life-threatening situations that, although rare, are more common with anti-PD-1/PDL-1 treatments and in combination therapy than in monotherapy. It is important for clinicians to be aware of these life-threatening adverse events in order to start early treatment. (d) Grade 5: Fatal irAEs include neurotoxicity, cardiotoxicity and pulmonary toxicity. A summary of the categorization of immune-related adverse events (irAEs) based on severity is presented in Table 2. The main characteristics of irAEs are (a) typical onset is within 2-16 weeks but can occur at any time after receiving immunotherapy treatment (from days to even after a year); (b) each irAE can become serious if not diagnosed early and appropriately treated; (c) most symptomatic irAEs, except those involving the endocrine system, are managed by withdrawal of the treatment, if needed, plus several weeks of glucocorticoid treatment. Most irAEs resolve with no further actions, but some require chronic therapy (hormonal supplementation, immunosuppression treatment, etc.). Those that affect the endocrine system should be studied with serum markers. Patients may be asymptomatic but may still require modifications of their treatment or steroid therapy . What is the role of [18F]FDG PET/CT in diagnosis and management of immunorelated adverse effects? [18F]FDG PET/CT is a great tool in clinical practice to detect early signs of irAEs, such as tissue inflammation, which will enable a clinician to intervene even before the symptoms appear. Nuclear medicine physicians must be aware of these potential artefacts and the spectrum of potential non-malignant inflammatory changes in patients with immunotherapy treatment to avoid diagnostic mistakes . Below are described the most common irAEs known in melanoma treatment with immunotherapy. Another potential role of [18F]FDG PET/CT in this setting its predictive value when iRAEs are detected. However, up to now, the available evidence is non-conclusive . For example, in one study, they found significant correlation of irAEs with therapy response for some irAEs, such as hypophysitis, hepatitis, skin rash, pruritus, fever and ocular muscle inflammation (p < 0.05), but, on the contrary, they did not find any significant correlation between PET-related colitis or diarrhoea and response to therapy (p > 0.05) . It has been observed that presence of irAEs, particularly severe irAEs, correlates with response to immunotherapy, disease control and good long-term survival . However, patients without any irAEs or only mild irAEs also reached similar outcomes, Because of this, presence of irAEs should not be considered an essential condition for achieving clinical benefit . In this regard, occurrence or severity of irAEs should not be the basis of decisions to continue or cease immunotherapy . Other aspects to be considered regarding irAEs are that there are sex-specific differences (i.e., endocrinological IRAEs more often in women) and potential differences in survival between males and females . Finally, management of IRAEs during treatment might also be challenging, specifically regarding the decision of discontinuation of treatment with immunotherapy . 6.1. Nodal Activation and Sarcoid-like Reaction The differential diagnosis of lymphadenopathies is very long. In the context of melanoma's immunotherapy, lymphadenopathies located in the draining basins from the site of the tumour can be a challenging issue as it is difficult to differentiate between reactive nodes from metastatic disease. Some of the signs that allow clinician to differentiate between both diagnoses are (a) the size and shape of the nodes; those that are round with a short to long axes ratio (S/L ratio) greater than 0.5) are suggestive of malignant disease, while reactive or benign lymph nodes are elliptical in shape (S/L ratio <0.5); (b) preservation of the nodal fatty hilar structure preserved, low-mild [18F]FDG metabolism, symmetrical [18F]FDG uptake are highly suggestive of benign lesions . On the other hand, sarcoid-like reactions have been related with PD-1 anti-neoplastic immunotherapy against melanoma. This irAE mimics this multisystem granulomatous disease, appearing as a systemic granulomatous reaction that is indistinguishable from sarcoidosis. Some signs that enable a clinician to identify it as a sarcoid-like reaction is that it typically appears after initiation of treatment and it improves or resolves after withdrawal of treatment. [18F]-FDG PET/CT shows symmetrical multiple foci uptake observed in the mediastinal and bilateral hilar nodes, but it can also be seen in retrocrural and abdominal para-aortic nodes. However, to distinguish between sarcoidosis occurring in an oncologic patient and sarcoid reactions is difficult unless a pathology study is performed (granulomas in sarcoid reactions are B-cell positive, whereas those in sarcoidosis are B-cell negative) . An example is presented in Figure 4. 6.2. Reactive Bone Marrow This may happen when the oxygen content in the body tissues is low, if there is loss of blood or anaemia or if the number of red blood cells decreases, but it also may happen as a reaction to immunotherapy agents that work as activators of the immune system. It may involve any bone, but the predominant sites include the vertebral column, ribs, skull, pelvis, etc. Diffuse homogeneous [18F]-FDG uptake is observed on [18F]FDG PET/CT, which reflects hyperplastic bone marrow and an activated immune system . 6.3. Splenic Activity It indicates activation of reticuloendothelial system promoted by immunotherapy agents. High diffuse [18F]FDG uptake is observed in splenic tissue, which is higher than the liver uptake (as inversion of the usual liver-to-spleen uptake ratio) regardless of whether or not there is splenomegaly . 6.4. Thyroiditis The clinical manifestations can range from hypothyroidism to hyperthyroidism. To achieve proper diagnosis, correlation with clinical and hormonal analysis will be needed. These irAEs are much more frequent when related to PD-1 immunotherapy against melanoma. Diffuse uptake of [18F]FDG in the thyroid gland is observed on [18F]FDG PET/CT, commonly related to benign processes . 6.5. Pneumonitis Pneumonitis is a rare but severe immune-related adverse event. It is considered a stage 4-degree severity, so clinicians that evaluate these patients must be aware and initiate an evaluation for pneumonitis when the first signs or symptoms appear, such as cough, fever, dyspnoea or chest pain, and, once the diagnosis is confirmed, pulmonary function should be monitored serially to evaluate for progression or resolution of pneumonitis. It presents four distinct patterns: organizing pneumonia (OP); nonspecific interstitial pneumonia (NSIP); hypersensitivity pneumonitis (HP); diffuse alveolar damage (DAD) . 6.6. Colitis It is described as diarrhoea that requires steroid/infliximab therapy for resolution and/or with endoscopic/histological confirmation (colonoscopy and biopsy are the gold standard for diagnosis in this situation). There is a significantly higher risk of developing colitis with combined immunotherapy treatment. Disease severity can range from grade 1 to 4 depending on its symptoms, which are summarised in Table 3. Parched uptake with moderate to high [18F]FDG uptake is shown in the colon on [18F]FDG PET. It should be noted that use of metformin can result in important increased uptake of [18F]FDG and should be ceased at least 48 h prior to [18F]FDG PET/CT . 6.7. Hepatitis It is a potentially serious complication of checkpoint blockade. Hepatitis is most commonly a low-grade toxicity, but grade 3 and 4 hepatotoxicity does occur; its incidence is especially high for combined immunotherapy. An increase in liver markers is a sign for imminent severe disease (although level of transaminases does not always correlate with histologic extent of injury). Signs of severe liver injury should be evaluated (asterixis, ascites, caput medusa, hepatomegaly, jaundice, scleral icterus) although hepatitis from immunotherapy agents is not usually detectable in physical examination. Generally, [18F]FDG PET/CT does not show significant metabolic alterations in the liver . 6.8. Pancreatitis The incidence of pancreatitis with either of the inhibitors is low. It is generally associated with a rise in serum amylase but may be clinically asymptomatic, showing a decrease in endocrine and exocrine pancreatic function, which result in metabolic and nutritional disorders. Signs that must alarm the clinician towards pancreas injury are hyperglycaemia, abdominal pain and steatorrhea. On [18F]FDG PET/CT, the pancreas may present diffuse [18F]FDG uptake of moderate to high intensity in addition to focal or diffuse pancreatic enlargement without a focal lesion suspicious for metastasis . 6.9. Hypophysitis It is predominantly a complication of CTLA-4 inhibitors, although the mechanism by which hypophysitis occurs after CTLA-4 inhibitors exposure is not clear. Most patients remain on glucocorticoid replacement despite efforts to withdraw therapy and few patients fully recover pituitary-adrenal axis function. Men are more prone to developing immunorelated hypophysitis than women. Clinicians should expect notable increases in incidence and prevalence of hypopituitarism secondary to hypophysitis after immune checkpoint inhibitor. On [18F]FDG PET/CT, hypophysitis is shown as a discernible focal new [18F]FDG uptake in the pituitary fossa . 6.10. Skin and Soft Tissue This is the most common of all irAEs, especially with combined therapy. Clinical manifestations range from pruritus and mild dermatoses to severe reactions, including Stevens-Johnson syndrome and toxic epidermal necrolysis. On [18F]FDG PET/CT, skin manifestations are generally not visualized, but subcutaneous tissue or panniculitis can be visualized as nodules with moderate [18F]FDG avidity within areas of subcutaneous fat . 7. Discussion This review is focused on melanoma patients, analysing (a) the role of [18F]FDG PET/CT in the above mentioned challenges; (b) the available evidence on its efficacy. For this purpose, we performed a review of the literature, focusing on original and review articles. Immunotherapy is based on manipulation of the immune system in order to act against tumour cells, with growing evidence especially in melanoma patients. The available evidence suggests that [18F]FDG PET/CT has prognostic value in melanoma patients treated with immunotherapy. The first challenge faced by this new therapeutic tool is finding valid evaluation criteria for response assessment. To standardize the evaluation criteria in order to be able to apply them in clinical practice for evaluation of response to immunotherapy, new evaluation criteria have been published. In summary, although there are no clearly established or globally accepted criteria, modified response criteria are potentially an appropriate method for evaluation of immunotherapy benefit. These modified response criteria, focusing on the metabolic response, are potentially appropriate for evaluation of response to immunotherapy. These criteria consider the fact that immunotherapy can cause non-conventional patterns of response and must be considered for precise evaluation. The second challenge is distinguishing between "atypical" response patterns. In this regard, immunotherapy causes non-conventional patterns of response. Four new atypical patterns have been described and should be recognized in order to better assess/evaluate a tumour's response. The third challenge is using PET biomarkers as predictive and response evaluation parameters, divided into two categories: those obtained from the baseline study and those that result from interval changes. In this context, [18F]FDG PET/CT biomarkers appear to be promising parameters in prediction and assessment of response to immunotherapy. The fourth and last challenge is diagnosis and management of immunorelated adverse effects. Immunorelated adverse effects are recognized as predictors of early response to immunotherapy and may be associated with better prognosis and clinical benefit. The main limitation of this study is it is not a systematic review. However, a recent meta-analysis was updated with studies published since the literature search was completed. The main findings of our review are in line with those of the systematic review. The available evidence suggests that [18F]FDG PET/CT has a prognostic tool in melanoma patients treated with immunotherapy. However, there are no globally accepted response criteria yet and the evidence is scarce. Therefore, new studies are warranted in order to obtain high-quality evidence. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flow chart of study selection. Figure 2 77-year-old man being followed because of an adenocarcinoma in a sigma polyp. He presented an incidental finding of a lung mass located in the superior left lobe, later confirmed as a lung adenocarcinoma with evidence of loco-regional lymphadenopathic infiltration. (A) Third [18F]FDG PET/CT showing radiological stability after chemotherapy. (B) Oligometastatic progression in liver parenchyma with solitary lesion after chemotherapy and radiotherapy. (C) After initiating immunotherapy (three cycles of Atezolimumab), [18F]FDG PET/CT evidenced progression of the primary tumour and the liver lesion with countless liver, adrenal and bone lytic lesions as well as peritoneal implants, consistent with hyperprogression. The patient died one month later. Figure 3 48-year-old man with right temporal melanoma operated in 2016. (A) Tumoral progression in laterocervical lymphadenopathies and intraparotid adenopathy in the right side. (B) [18F]FDG PET/CT 3 months later, under treatment with Dabrafenib and Trimetinib, shows a complete response in the right side with lymphadenopathic progression on the left side, where a new conglomerate is identified. (C) Control after one month shows lymphadenopathic progression and two new lesions in lumbar spine and pubis. (D) After 4 cycles of Nivolumab and Ipilimumab, there is improvement in cervical lymph node involvement, while bone progression is observed in pelvis. This evolution suggests dissociated response. Figure 4 73-year-old man with dorsal melanoma under treatment with Nivolumab and granulomatous reaction sarcoid-like as well as acute gastritis. [18F]FDG PET/CT MIP (A) and axial fusion slices (B,C) are presented. Treatment was discontinued. diagnostics-13-00978-t001_Table 1 Table 1 Characteristics of the articles included and main findings. Author Year Design Sample Size Type of Immunotherapy PET Parameters Summary Main Findings Cho et al. 2017 Pros. * 20 Ipilimumab nivolumab SUV No statistically significant differences between SUVmax in basal and late PET Anwar et al. 2018 Pros. * 41 Ipilimumab SUV No statistically significant differences between SUVmax in basal and late PET Ito et al. 2019 Retr. # 142 Ipilimumab MTV, TLG TMTV was a strong independent prognostic factor Sanli et al. 2019 Retr. # 34 Anti-PD1 SUV, MTV, TLG, TH index Analysis showed that SUVmax, SUVpeak, gradient-based TLG and gradient-based TH index had a significant association with OS. There was no correlation between MTV and OS Seban et al. 2019 Retr. # 55 Anti-PD1 SUV, MTV, TLG, HISUV, BLR, SLR Low tumour burden (MTV) correlates with survival and objective response. Hematopoietic tissue metabolism (BLR) correlates inversely with survival Nobashi et al. 2019 Retr. # 40 Ipilimumab, pembrolizumab, nivolumab SUV, MTV, TLG There was no statistical difference for baseline SUVmax, MTV nor TLG between patients with and without clinical benefit Nakamoto et al. 2020 Retr. # 85 Ipilimumab, pembrolizumab, nivolumab MTV, TLG, SUV TMTV was a strong prognostic indicator of OS in melanoma patients Seban et al. 2020 Retr. # 56 PD-1, CTLA-4 SUV, MTV, TLG, HISUV, BLR, SLR For mucosal melanoma patients, the only prognostic imaging biomarker was SUVmax, whereas, for cutaneous melanoma patients, MTV, TLG and BLR were negatively correlated to ICI response duration Wong et al. 2020 Retr. # 90 Ipilimumab or anti-PD1 SUV, MTV, SLR Pre-treatment SLR > 1, 1 was associated with poor outcome after ipilimumab Flavus et al. 2021 Retr. # 56 Ipilimumab, pembrolizumab SUV, MTV, LZE Total MTV and LZE correlated with shorter OS Nakamoto et al. 2021 Retr. # 92 Ipilimumab, pembrolizumab SUV, MTV, TLG, BLR BLR was an independent prognostic biomarker for OS and PFS; high BLR was associated with poor progression-free and overall survival Sachpekidis et al. 2021 Retr. # 31 Ipilimumab, nivolumab SLR Patients catalogued as confirmed progressive metabolic disease had higher SLRmean after 2 cycles of treatment than those catalogued as pseudoprogression Schweighofer-Zwink et al. 2021 Retr. # 51 Ipilimumab, pembrolizumab, nivolumab SUL, MTV, TLG, TBR of SUL On baseline, PET, SULmax and SULpeak as well as most TBRs were predictive for 5-year OS rates. MTV, TLG and most of the TBRs were predictive on both follow-up studies (3 and 6 months after therapy). Changes in values of MTV, TLG and most of the TBRs from the baseline to the follow-up studies were prognostic * Prospective design; # Retrospective design. BLR: Bone marrow-to-liver maximum standard uptake value ratio; HISUV: Heterogeneity index of SUV; ICI: Immune checkpoint inhibitor; LZE: Long zone emphasis; MTV: Metabolic tumour volume; SLR: Spleen-to-liver maximum standard uptake value ratio; SLRmean: Mean spleen-to-liver maximum standard uptake value ratio; SUL: Standardized uptake value corrected for lean body mass; SULmax: Maximum standardized uptake value corrected for lean body mass; SULpeak: Peak standardized uptake value corrected for lean body mass; SUV: Standard uptake value; SUVmax: Maximum standard uptake value; SUVpeak: Peak standard uptake value; TBR: Tumour-to-background ratio; TH index: Tumour heterogeneity index; TLG: Total lesion glycolysis; TMTV: Total MTV. diagnostics-13-00978-t002_Table 2 Table 2 Categorization of immune-related adverse events (irAEs) based on severity. Grade Definition Grade 1 Mild Grade 2 Moderate Grade 3 Severe or requiring hospitalization but not life-threatening Grade 4 Life-threatening Grade 5 Death diagnostics-13-00978-t003_Table 3 Table 3 Symptoms and management of colitis according to grade. Table adapted from Som A. et al. . Severity Symptoms Management Grade 1 Asymptomatic Close monitoring immunotherapy. Loperamida/Difenoxilato/atropine Grade 2 Abdominal pain, mucus, blood in stool Systemic steroids (if no response in 2-3 days, consider adding infliximab within 2 weeks) Grade 3 Severe abdominal pain, peritoneal signs Require hospitalization for supportive care:- IV corticosteroids. - If no response in 2 days, strongly consider adding infliximab or vedolizumab within 2 weeks. Grade 4 Severe and persistent abdominal pain, fever, ileus, life-threatening complications, such as perforation and peritonitis. 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PMC10000459 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050766 cells-12-00766 Article Low Gut Microbial Diversity Augments Estrogen-Driven Pulmonary Fibrosis in Female-Predominant Interstitial Lung Disease Chioma Ozioma S. Writing - original draft 1 Mallott Elizabeth Formal analysis Investigation Writing - review & editing 2 Shah-Gandhi Binal Investigation 1 Wiggins ZaDarreyal Investigation 1 Langford Madison Investigation 1 Lancaster Andrew William Investigation 1 Gelbard Alexander Writing - review & editing 3 Wu Hongmei Investigation 3 Johnson Joyce E. Formal analysis 4 Lancaster Lisa Investigation 1 Wilfong Erin M. Methodology Resources 1 Crofford Leslie J. Supervision Funding acquisition 12 Montgomery Courtney G. Formal analysis Investigation 5 Van Kaer Luc Conceptualization Writing - review & editing 4 Bordenstein Seth Formal analysis Writing - review & editing 6 Newcomb Dawn C. Conceptualization Investigation Writing - review & editing 14 Drake Wonder Puryear Conceptualization Resources Writing - review & editing Supervision Project administration Funding acquisition 14* Kundu Parag Academic Editor 1 Departments of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232, USA 2 Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA 3 Otolaryngology-Head and Neck Surgery, Vanderbilt University School of Medicine, Nashville, TN 37232, USA 4 Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA 5 Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA 6 Department of Biology and Entomology, Pennsylvania State University, College Station, PA 16801, USA * Correspondence: [email protected] 28 2 2023 3 2023 12 5 76620 1 2023 19 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Although profibrotic cytokines, such as IL-17A and TGF-b1, have been implicated in the pathogenesis of interstitial lung disease (ILD), the interactions between gut dysbiosis, gonadotrophic hormones and molecular mediators of profibrotic cytokine expression, such as the phosphorylation of STAT3, have not been defined. Here, through chromatin immunoprecipitation sequencing (ChIP-seq) analysis of primary human CD4+ T cells, we show that regions within the STAT3 locus are significantly enriched for binding by the transcription factor estrogen receptor alpha (ERa). Using the murine model of bleomycin-induced pulmonary fibrosis, we found significantly increased regulatory T cells compared to Th17 cells in the female lung. The genetic absence of ESR1 or ovariectomy in mice significantly increased pSTAT3 and IL-17A expression in pulmonary CD4+ T cells, which was reduced after the repletion of female hormones. Remarkably, there was no significant reduction in lung fibrosis under either condition, suggesting that factors outside of ovarian hormones also contribute. An assessment of lung fibrosis among menstruating females in different rearing environments revealed that environments favoring gut dysbiosis augment fibrosis. Furthermore, hormone repletion following ovariectomy further augmented lung fibrosis, suggesting pathologic interactions between gonadal hormones and gut microbiota in relation to lung fibrosis severity. An analysis of female sarcoidosis patients revealed a significant reduction in pSTAT3 and IL-17A levels and a concomitant increase in TGF-b1 levels in CD4+ T cells compared to male sarcoidosis patients. These studies reveal that estrogen is profibrotic in females and that gut dysbiosis in menstruating females augments lung fibrosis severity, supporting a critical interaction between gonadal hormones and gut flora in lung fibrosis pathogenesis. estrogen gut microbiome lung fibrosis sarcoidosis Th17 cells Foundation for Sarcoidosis Research (FSR) FellowshipT32 AR059039-10 Ellen Dreiling Research Fund Endowment and the Vanderbilt Microbiome InitiativeFSR 19-505-SGP HL117074 K24 HL127301 K24 HL127301-1S 5 T32 HL094296 NHLBI R01HL113326-06 NIGMS P30 GM110766-01 R01 HL122554 R01 AI139046 T32HL087738 T32GM007347 O.S.C.: Foundation for Sarcoidosis Research (FSR) Fellowship Program 17-904, T32 AR059039-10; W.P.D.: Ellen Dreiling Research Fund Endowment and the Vanderbilt Microbiome Initiative, FSR 19-505-SGP, HL117074, K24 HL127301 and K24 HL127301-1S; Z.W.: 5 T32 HL094296; C.G.M.: NHLBI R01HL113326-06, NIGMS P30 GM110766-01; D.C.N.: R01 HL122554; L.V.K.: R01 AI139046; E.M.W.: T32HL087738; N.C.: T32GM007347. pmc1. Introduction An ever-growing synergy of human and animal investigations supports the important role of sex hormone regulation relating to immunity in the pathophysiology of chronic lung diseases . IL-17 signaling has been implicated in numerous chronic lung diseases, such as idiopathic pulmonary fibrosis (IPF), lung cancer and pulmonary sarcoidosis . Moreover, striking clinical disparities according to sex are observed in Th17 cell-mediated diseases. For example, although the incidence of IPF is higher in men, being of the female sex is predictive of better IPF clinical outcomes . Among patients with pulmonary arterial hypertension, female patients have better survival than males . These observations support the urgent need to identify relevant sex-specific mechanisms in chronic pulmonary inflammation. Independent reports demonstrate that profibrotic signaling pathways converge on STAT3, an important molecular checkpoint for tissue fibrosis . Immune cells, including CD4+ T cells, produce IL-6, which enhances collagen production through the induction of JAK/STAT3/IL-17A or JAK/ERK/TGF-b1 signaling in local and systemic environments . Distinctions in clinical outcomes by sex support an investigation of the interplay of female gonadotrophic hormones with the STAT3-dependent induction of profibrotic cytokine expression. The interactions of the alpha subunit of the estrogen receptor (ERa) and STAT3 protein, both transcription factors, have been reported in breast cancers of epithelial origin, noting enhanced epithelial-mesenchymal transition (EMT) as well as augmented tumor metastasis . However, the immunologic consequences of ERa binding to the STAT3 gene in CD4+ T cells of patients with lung fibrosis remain unexplored. The observed disparate clinical outcomes in chronic lung diseases by sex support the investigation of the impact of gonadotrophic hormones on STAT3 signaling, specifically in the context of the profibrotic cytokines, IL-17A and TGF-b1. Here, we report that human females experiencing a loss of lung function due to progressive fibrosis, as well as female murine models of bleomycin-induced lung fibrosis, demonstrate increased T regulatory cells with TGF-b1 expression (immunosuppressive) in the fibrotic lung microenvironment. Lower estrogen states, such as those found in males and ovariectomized female mice, reveal increased IL-17A expression due to elevated percentages of pulmonary Th17 cells (pro-inflammatory). Moreover, the investigation of this estrogen-adaptive immunity interplay in distinct environments reveals that low gut microbial diversity further increases estrogen-induced lung fibrosis. These data demonstrate a distinct sex-specific role for STAT3 signaling in CD4+ T cells, thus paving the way for developing personalized (e.g., sex-based) immunotherapeutic strategies for chronic lung inflammation. 2. Materials and Methods 2.1. Human Study Approval To participate in this study, all of the human subjects signed a written informed consent form, and the patients were enrolled at Vanderbilt University Medical Center. All of the human studies were approved by the appropriate institutional review board (VUMC 040187). 2.2. Study Population For inclusion in this study, the clinical and radiographic criteria used to define sarcoidosis were applied . IPF subjects were defined according to recent American Thoracic Society (ATS) guidelines , and systemic sclerosis patients were defined according to the 2013 American College of Rheumatology criteria . Clinical lung progression was defined as previously described . Pulmonary function testing was performed as clinically indicated. FVC decline was defined as a relative reduction of >=10% in the percent of predicted FVC. There were four human cohorts in this study: 25 healthy controls (7 males and 18 females), 31 sarcoidosis patients (11 males and 20 females), idiopathic pulmonary fibrosis (IPF) patients (36 males and 9 females), and scleroderma patients (5 males and 6 females). Information related to the demographics of the study subjects is provided in Table 1. 2.3. Peripheral Blood Mononuclear Cells Isolation and Storage The Ficoll-Hypaque density gradient centrifugation method was used to isolate peripheral blood mononuclear cells (PBMCs) from the whole blood of all four human cohorts in this study: healthy controls, sarcoidosis, IPF, and scleroderma patients, as previously described . The PBMCs were then stored in fetal bovine serum containing 10% dimethyl sulfoxide (DMSO) at a concentration of 10 x 106 cells/mL in a -80 degC freezer before being transferred to liquid nitrogen for prolonged storage or before use. 2.4. Chromatin Immunoprecipitation Sequencing (ChIP-Seq) Library Preparation Primary CD4+ T cells were negatively selected using immunomagnetic bead separation (STEMCELL, EasySep #17951). Approximately 1 to 2.5 million total T cells were obtained from 5 to 10 million PBMCs. The T cells were first incubated with 2 mM disuccinimidyl glutarate for 35 min at room temperature; then, formaldehyde was added to a final concentration of 1%, and the cells were incubated for another 10 min at room temperature . The nuclei were isolated using the Covaris truChIP Chromatin Shearing Kit and fragmented by sonication. Immunoprecipitation was performed using an anti-ERa antibody (Cell Signaling #8644) and protein A+G magnetic beads. The chromatins were de-crosslinked and purified using AMPure XP beads. ChIP-seq libraries were prepared according to Illumina protocols and were sequenced using 75 bp paired-end sequencing on an Illumina NextSeq, producing an average of 135,924,844 reads per library. 2.5. Sequencing Alignment and Peak Calling The ChIP-seq reads were examined for technical artifacts using FastQC. No aberrant technical behavior was identified. The reads were trimmed for adapter sequences and decontaminated for sequencing artifacts by using bbduk. The trimming options were set to ktrim = right trimming, mink = 11, hdist = 1, qin = 33, tpe and tbo options enabled. BBDuk's list of Illumina sequencing adapters was used to perform adapter trimming. Decontamination was performed against phiX adapters and bbduk's database of sequencing artifacts. The decontaminated reads were aligned to version GRCh38 of the human reference genome using BWA-mem , with the following options: -L 100 -k 8 -O 5. Following the alignment, the peaks were called with respect to the input chromatin library using MACS2 , with the following options: -nomodel -shift -100 -extsize 200 g hs -q 0.05 -f BAMPE -keep-dup all -broad. 2.6. Murine Model of Pulmonary Fibrosis All of the murine procedures were performed according to the protocol approved by the Institutional Animal Care and Use Committee at Vanderbilt University Medical Center (protocol #M1700043). For the murine model of bleomycin-induced pulmonary fibrosis, 8-week-old mice weighing approximately 17-22 g were used. The mice were anesthetized with an intraperitoneal injection of 80 mL of 20 mg/mL Ketamine/1.8 mg/mL Xylazine solution. Then, 75 mL containing 0.04 units of bleomycin (Novaplus Lake Forest IL) in saline or an equal volume of saline (0.9% sodium chloride) (Hospira Inc., Lake Forest IL), used as a control, was administrated intranasally to wild-type or ESR-1-/- mice, as previously described . The lungs were harvested for histology, flow cytometry, or single-cell isolation, as previously described . The mouse strains used are described in Table S1. 2.7. Ashcroft Scoring The degree of fibrosis in the murine lung tissue was assessed using Ashcroft scoring, as previously described . 2.8. Sircol Assay The collagen content was determined using a Sircol Collagen Assay kit (Biocolor, Newtown Abbey, UK), as previously described . 2.9. Flow Cytometry Both murine and human flow cytometry experiments were conducted with an LSR-II flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA), and the information related to all the antibodies used in this study is listed in Table S2. Live cells were gated based on the forward and side scatter properties, and the surface staining of cells was performed as previously described . Th17 cells were identified by flow cytometry using key transcriptional factors, such as STAT3, as previously described . The cells were gated on singlets, live CD3+ and CD4+ cells. Data analysis was performed using FlowJo software (Tree Star, Ashland, OR, USA). A minimum of 50,000 events were acquired per sample. 2.10. In Vivo Implantation of Hormone Pellets to Ovariectomized Mice Ovariectomy or sham surgeries were conducted at three weeks of age by the Jackson Laboratory, and the experiments were carried out when the ovariectomized or sham-operated mice were 6 weeks old. At 6 weeks of age, 60-day slow-release pellets (Innovate Research of America, Sarasota, FL, USA) containing 0.1 mg (E2), progesterone 25 mg (P4) or a combination of 17b-E2 (0.1 mg) and P4 (25 mg) were surgically placed subcutaneously into ovariectomized C57BL/6J mice, as previously described . As a control, 25.1 mg of vehicle pellets (Innovative Research of America) was surgically placed into the sham-operated females or ovariectomized female mice. Three weeks (21 days) after the pellets were implanted, the mice were challenged with intranasal bleomycin (0.04 Units) and sacrificed 14 days later, as previously described . Studies involving large and independent experimental cohorts of mice were performed at least twice. 2.11. Metagenomic Sequencing and Analysis of Gut Microbiota Fecal pellets were collected from female mice at Day 14 in each housing cohort, and genomic DNA (gDNA) was extracted with the Qiagen DNAeasy extraction kit (Qiagen, Valencia, CA, USA), according to the manufacturer's instructions. The gDNA concentration and quality were confirmed using the Bioanalyzer 2100 system (Agilent, Santa Clara, CA, USA). The metagenomic sequencing and analysis of fecal pellets was conducted as previously described . The sequences of gut microbiota have been deposited into BioProject ID PRJNA899808. Wilcoxon Rank Sum tests in R were used to examine differences in Shannon diversity and evenness between the ABSL-1 and ABSL-2 environments. The code for all of the analyses can be found at (accessed on 19 January 2023) . 2.12. Statistics When comparing different experimental groups, we used an unpaired two-tailed Student's t-test. Multiple-group comparisons were performed using a one-way analysis of variance (ANOVA) with Tukey's post hoc test. Statistical analysis for all figures was carried out using Prism version 7.02 (GraphPad Software, San Diego, CA, USA). For a result to be considered statistically significant, a p-value of less than 0.05 was used. 3. Results 3.1. The Nuclear Transcription Factor, Estrogen Receptor Alpha Subunit, Interacts with the STAT3 Gene Locus in CD4+ T Cells The estrogen receptor alpha subunit (ERa) is not only a receptor but also serves as a transcription factor. To identify factors that may modulate STAT3 expression during lung fibrosis, we interrogated ChIP-seq datasets in the ENCODE 3 repository . In five human cell lines, including cancers and EBV-transformed B lymphocytes, a significant enrichment of ERa binding was demonstrated within the STAT3 locus. Representative tracks among the technical replicates for each cell line were visualized in the WashU Epigenome Browser . The numbers of starting reads, decontaminated reads, alignment successes, and enriched peaks are given in Table S3. These findings in the Chip-seq datasets confirmed previous reports indicating that ERa, which is encoded by the ESR1 gene, and STAT3 are important in breast and ovarian cancer , supporting the hypothesis that the STAT3 gene locus is a frequent target of ERa activity in various cell types. The targeting of ERa to the STAT3 gene locus in T cells has not been previously described. To determine whether ERa interacts with the STAT3 locus in CD4+ T cells through DNA binding activity, we performed genome-wide ChIP-seq for Era-bound regions. Primary CD4+ T cells were derived from the PBMCs of six healthy individuals with varying demographics (Table S4). Of the six ChIP libraries (four females and two males), sample p1035928-8, which corresponds to a female, identified an over sixfold greater number of ERa-enriched regions relative to any other sample. We used the GREAT algorithm to perform ontology-based functional enrichment analyses on that sample. ERa-enriched sites were statistically significantly enriched in genes related to T-cell function and development (Table S5), suggesting that the peaks obtained from this ChIP capture are specific to CD4+ T-cell function and are not randomly organized across the genome. Finally, we examined the STAT3 locus in detail. We found that sample p1035928-8 contains six ERa-binding regions within or proximal to the STAT3 genomic locus, including two in its promoter region . Overlaying chromatin accessibility data from the ENCODE project , we noted that each of these regions exhibits DNase hypersensitivity in at least one ENCODE cell line. Three of these regions also displayed evidence of estrogen-related receptor alpha (ESRRA) binding in other cell lines (K562, GM12878). Taken together, these results demonstrate that ERa binds the STAT3 locus in CD4+ T cells, specifically at known regions of chromatin accessibility shared with various cell types. 3.2. Loss of the ESR-1 Subunit Represses IL-6 Expression but Augments pSTAT3 and IL-17A Expression in CD4+ T Cells Because transcription factor ESR-1 (alpha subunit of ESR) was identified as binding to the STAT3 gene in CD4+ T cells, we investigated the role of the ERa subunit in profibrotic cytokine expression using a murine model of bleomycin-induced lung fibrosis in WT and ESR-1 knockout (ESR-1-/-) mice. Both murine cohorts were challenged intranasally with bleomycin and harvested on day 14. ESR-1-/- mice contain supernormal estrogen levels in their serum due to the loss of the ESR-1 signaling-mediated negative feedback loop . We observed that female ESR-1-/- mice lost significantly less weight and had the same mortality compared to their WT counterparts . Male ESR-1-/- mice also demonstrated reduced weight loss but had significantly increased survival compared to WT males . We used flow cytometry to examine profibrotic cytokine expression in pulmonary CD4+ T cells of the murine cohorts. The levels of IL-6 and IL-23R, key mediators of Th17 cell differentiation, were significantly reduced in the lung CD4+ T cells of female ESR-1-/- mice compared to their WT counterparts . Remarkably, the levels of pSTAT3 and IL-17A were increased in ESR-1-/- compared with WT mice . These data demonstrate that ESR-1 has a key role in the induction of IL-6 and IL-23R expression in CD4+ T cells, as well as the repression of pSTAT3 and IL-17A expression in CD4+ T cells during the pulmonary fibrosis of females. 3.3. Loss of Gonadotrophic Hormones through Ovariectomy Reduces IL-6 Production and Augments pSTAT3 and IL-17A Expression from CD4+ T Cells To further delineate the contribution of female gonadotrophic hormonal signaling to the progression of proinflammatory cytokine expression in the lung, we used female C57BL/6J mice that were ovariectomized or sham-operated at three weeks of age. Slow-release pellets containing either 17b-estradiol (17b-E2, 0.1 mg), progesterone (P4, 25 mg), the combination of 17b-E2 (0.1 mg) and P4 (25 mg) or a vehicle (25.1 mg) were subcutaneously implanted into adult ovariectomized female C57BL/6J mice at six weeks of age. At nine weeks of age, all groups were challenged with bleomycin, and the lungs were harvested 14 days later. There was no significant difference in weight loss or survival across the hormone treatment groups compared to the ovariectomized mice implanted with placebo pellets . We performed flow cytometric analysis of single-cell lung suspensions (SCLS) to assess alterations of CD4+ T cell populations. TGF-b and IL-17A are profibrotic cytokines that are expressed by regulatory T cells and Th17 cells, respectively. We began by comparing regulatory T and Th17 cell populations in sham-operated, menstruating female mice. We noted a significantly higher population of regulatory T cells compared to Th17 cells in the sham-operated mice . We then assessed for IL-17A cytokine expression in response to the loss of female hormones. Ovariectomized mice displayed decreased CD4+IL-6+ T cells compared to the sham-operated mice; supplementation with both 17b-E2 and P4 in ovariectomized mice normalized IL-6 expression. Neither hormone individually restored IL-6 expression by CD4+T cells to the same levels as the sham-operated mice . The same trends held for the IL-6 co-receptor GP130 . Remarkably, and akin to our observation in ESR-1-/- mice, the levels of pSTAT3 were increased in the CD4+ T cells of ovariectomized mice compared to sham-operated animals, again returning to sham levels in ovariectomized mice by the addition of female hormones . In accordance with an increase in pSTAT3, we also observed heightened CD4+IL-17A+ T cells in ovariectomized mice compared to sham-operated animals. The addition of 17b-E2, P4 or both to ovariectomized mice decreased IL-17A expression compared to the placebo . A representative FACS plot is provided . Overall, these findings reveal that female hormones repress inflammatory profibrotic cytokine expression by inhibiting pSTAT3 signaling and IL-17A expression in murine pulmonary CD4+ T cells following bleomycin administration. 3.4. Lung Quantification following the Loss of ESR-1 or Ovariectomy Reveals Reduced Collagen Content To determine the physiologic significance of estrogen signaling for profibrotic cytokine expression, we performed histologic analysis and collagen quantification of the lung using the Sircol assay. Analysis of lung histology using trichrome staining noted significantly less fibrosis in ovariectomized mice without hormone replacement compared to the sham-operated mice or ovariectomized mice given dual estrogen (17b-E2)/progesterone (P4) hormone pellets . Ashcroft scoring and the quantification of collagen content revealed a nonsignificant decrease in collagen levels in ovariectomized mice compared to mice that underwent sham ovariectomy surgeries. The replacement of female hormones with a combination of estrogen and progesterone pellets increased fibrosis compared to the ovariectomized placebo group . Similarly, a nonsignificant decrease in pulmonary collagen content was observed in ESR-1-/- mice compared to wild-type mice. The observation of a nonsignificant decline in the pulmonary lung content following the loss of estrogen signaling suggests that additional factors contribute to pathogenesis. We recently reported that the gut microbiota play an important role in lung fibrosis severity. ABSL-1 housing conditions favor gut microbiota diversity, whereas ABSL-2 conditions favor reduced gut microbiota diversity . Using linear discriminant analysis (LDA) to examine species-level differences in the gut microbiota, 10 taxa were overrepresented in ABSL-1 mice, and five taxa were overrepresented in ABSL-2 mice. The overrepresented taxa in ABSL-2 mice included Lachnospiraceae bacterium A2, Lachnospiraceae bacterium 28-4, Firmicutes bacterium ASF500 and Romboutsia ilealis . A higher relative abundance of Firmicutes in the lung microbiota of bleomycin-treated mice with fibrosis has been reported . The species overrepresented in ABSL-1 mice included Staphylococcus nepalensis, Dubosiella newyorkensis, Acetatifactor muris, Lactobacillus animalis, Lactobacillus murinus and Acutalibacter muris . No distinctions in the lung microbiota are present in these mice regarding the housing condition. Specifically, rearing environments that favor low gut microbiota diversity, such as ABSL-2 housing conditions, induce severe lung disease compared to ABSL-1 conditions. To confirm if gut microbiota impact female ILD severity, we began by assessing the lung collagen content in wild-type female mice who received intranasal bleomycin while housed in different environments: germ-free, ABSL-1 or ABSL-2 conditions. We noted significant distinctions in lung collagen content among wild-type females according to the rearing environment, with ABSL-2 female mice demonstrating the most severe disease compared to germ-free or ABSL-1 mice . To determine the impact of estrogen signaling and gut microbiota on lung fibrosis severity, we assessed the lung collagen content among ovariectomized mice, as well as those ovariectomized with estrogen replacement, while housed under either ABSL-1 or ABSL-2 conditions. Remarkably, we noted that ovariectomized mice housed under ABSL-1 or ABSL-2 conditions did not demonstrate a change in the collagen content . Equally noteworthy was the observation that a significant increase in lung fibrosis was noted among ovariectomized mice who received estrogen replacement and were housed in ABSL-2 conditions compared to those housed in ABSL-1 conditions. These findings reveal a synergistic relationship between estrogen signaling and gut dysbiosis regarding lung fibrosis severity . 3.5. Female Gut Microbiota Demonstrate Significantly Less Diversity in ABSL-2 Housing Conditions To investigate the hypothesis that the gut microbiota is an important contributor to the differences in fibrosis severity between female mice housed under ABSL-1 and ABSL-2 conditions, we performed metagenomic analysis on fecal pellets from female mice in each housing cohort. We did not detect microorganisms in the stool of female germ-free mice by sequencing and culture, as expected. Shannon alpha diversity, a measure of species richness and evenness, was considerably higher in female ABSL-1 mice compared with female ABSL-2 mice using a Wilcoxon rank sum test . Additionally, Pielou's evenness was higher in ABSL-1 compared with ABSL-2 female mice, but species richness did not differ significantly (Shannon diversity: Wilcoxon, W = 108, p = 0.015; Pielou's evenness: Wilcoxon, W = 106, p = 0.021; Species richness: Wilcoxon, W = 80.5, p = 0.450). The female mice housed under ABSL-1 and ABSL-2 conditions differed significantly in their gut microbiome composition using Jaccard but not Bray-Curtis dissimilarities (PERMANOVA, Bray-Curtis: F1,22 = 2.392, R2 = 0.098, p = 0.079; Jaccard: F1,22 = 8.369, R2 = 0.276, p < 0.001). A similar investigation in male mice revealed that the ABSL-1 and ABSL-2 microbiomes were significantly different using both metrics (PERMANOVA, Bray-Curtis: F1,24 = 4.728, R2 = 0.165, p = 0.004; Jaccard: F1,24 = 6.519, R2 = 0.214, p < 0.001) . Alpha diversity did not differ significantly between floors for male individuals (all p > 0.05). A comparison of female and male gut microbiota diversity according to the housing conditions reveals significantly greater gut diversity among females compared to males under ABSL-1 housing conditions , whereas only greater species richness was noted among females under ABSL-2 housing conditions . Beta diversity differences between ABSL-1 and ABSL-2 microbiota compositions also differed significantly when an analysis was conducted using both the Bray-Curtis dissimilarity metric index and the Jaccard index , which account for the presence/absence of taxa and taxon abundance variation, respectively (PERMANOVA, ABSL-1 mice: Bray-Curtis: F1,17 = 4.424, R2 = 0.206, p = 0.014; Jaccard: F1,17 = 2.408, R2 = 0.124, p = 0.053; ABSL-2 mice: Bray-Curtis: F1,29 = 1.952, R2 = 0.063, p = 0.160; Jaccard: F1,29 = 7.944, R2 = 0.215, p < 0.001). These findings support the hypothesis that the female gut microbiome changes according to the rearing environment. 3.6. Patients with Progressive Fibrotic Lung Disease Display Sex-Specific Profibrotic Cytokine Profiles Because of the role of female gonadotrophic hormones in reducing the CD4+ T cell-mediated proinflammatory and profibrotic environment in mouse models of lung fibrosis, we probed samples from human patients with fibrotic lung diseases for sex-associated differences. Consistent with the murine model of lung fibrosis, we observed higher levels of STAT3 mRNA and pSTAT3 protein in CD4+ T cells from the male compared to the female sarcoidosis patients . We noted similarly increased mRNA and protein expression of the master transcription factor regulating IL-17A production, RORC, in CD4+ T cells from the male compared to the female sarcoidosis patients . Additionally, among sarcoidosis patients experiencing disease progression, females expressed significantly higher IL-6 levels in their CD4+ T cells compared to males . We also assessed IL-17A and TGF-b1 production by sex, as CD4+ T cells promote pulmonary fibrosis through the STAT3-medicated production of IL-17A and TGF-b1 . We observed higher IL-17A mRNA and protein expression in CD4+ T cells from male compared to female sarcoidosis patients . CD4+ T cells from female sarcoidosis patients expressed significantly higher free TGF-b1 than males and the healthy female controls . There were no distinctions in the TGF-b1 precursor protein, latency-associated peptide-TGF-b, among males compared to females . These findings demonstrate the differential immune modulation of STAT3 signaling pathways in human CD4+ T cells of males (increased) and females (reduced) with fibrotic lung disease. Consequently, CD4+ T cells from males exhibit higher proinflammatory cytokine expression due to enhanced IL-17A production, whereas CD4+ T cells from females exhibit increased immunosuppressive cytokines due to greater TGF-b1 expression. We assessed for a possible contribution of female hormones to other fibrotic diseases, including IPF and Systemic Sclerosis (SSc), by quantifying the serum 17b-E2 levels in age-matched patients and healthy controls. Serum 17b-E2 was greater in male SSc and IPF patients compared to age-matched male healthy controls . These findings demonstrate the positive interplay of female gonadotrophic hormones in female-predominant fibrotic lung diseases. 4. Discussion This original report reveals the "ying-yang" effects of estrogen-induced lung fibrosis in female interstitial lung disease. Estrogen clearly augments the development of lung fibrosis ; yet, the binding of ERa to the STAT3 promoter shifts profibrotic cytokine expression away from proinflammatory phenotypes mediated by IL-17A to immunosuppressive phenotypes mediated by TGF-b1 . Human cytokine expression confirmed reduced pSTAT3 expression in females, leading to increased TGF-b1 production, whereas males display higher IL-17A levels. The beneficial effects of estrogen were apparent. Although ESR-1-/- mice and surgical ovariectomy confirm estrogen's profibrotic capacity in lung fibrosis, it is worth noting that Th17 cell differentiation is reduced due to the transcription factor ERa's ability in relation to the STAT3 promoter . The loss of STAT3 signaling has been shown to shift the IL-6-JAK2-STAT3 induction of IL-17A to sustained IL-6-ERK-TGF-b1 expression in local and systemic CD4+ T cells . This is the most likely explanation for the increased regulatory T cells noted in females and the increased STAT3 signaling and IL-17A production following ovariectomy . Both ovariectomized and ESR-1-/- mice revealed significantly lower IL-6 and GP130 levels than sham-treated animals but increased pSTAT3 and IL-17A levels in CD4+ T cells . Higher estrogen states augment IL-6 production, but instead of inducing a proinflammatory state supported by increased CD4+ IL-17A levels, estrogen concomitantly inhibits STAT3 signaling. These immune alterations are likely relevant to other IL-17A-mediated diseases in the postmenopausal state, such as myocardial infarctions and osteoporosis . Enhanced TGF-b1 expression protects against osteoporosis . The pathologic effects of estrogen were also determined. A prior study noted increased ESR-1 expression in human IPF lung samples and that the chemical inhibition of ESR-1 results in reductions in bleomycin-induced pulmonary fibrosis in male mice . The genetic and surgical ablation of estrogen-dependent signaling resulted in reductions in the pulmonary collagen content, which confirms the profibrotic nature of estrogen in female-predominant ILD . Remarkably, the observed reductions were not statistically significant, suggesting that other factors contribute to lung fibrosis severity in females. The induction of lung fibrosis in females under distinct housing conditions unveiled the role of the gut microbiome in lung fibrosis severity. Wild-type female mice treated with intranasal bleomycin demonstrate the greatest lung severity under ABSL-2 conditions and minimal fibrosis under germ-free conditions, thus confirming the important contribution of gut flora to female lung fibrosis . Conditions that favor the loss of female gut microbial diversity, such as ABSL-2 housing conditions, lead to greater lung fibrosis compared to ABSL-1 conditions . Equally noteworthy is the observation that fibrosis is synergistic between estrogen signaling and gut dysbiosis, suggesting that the profibrotic nature of estrogen is heavily influenced by gut microbiota and that the capacity of gut microbiota to induce fibrosis is influenced by the host hormone status. A growing body of literature supports crucial interactions between gut microbiota and estrogens . The conjugation of glucuronic acid (GlcA) to a compound, such as estrogen, marks it for elimination via the GI or urinary tract. b-glucuronidase, an enzyme that deconjugates estrogen, mediates estrogen release into the serum in its active form . Gut microbiota can inhibit or induce b-glucuronidase activity. In addition, it was previously noted that ABSL-2 stool contains reduced lactobacilli within the microbial community. Lactobacillus spp, which were elevated in ABSL-1 stool, can reduce fecal b-glucuronidase activity ; future studies that assess the capacity of lactobacilli to enhance urinary estrogen excretion and lower its serum levels are needed. Future studies defining the mechanisms by which ABSL-2 gut flora augment the estrogen induction of lung fibrosis are also warranted. Considering of the hormone status of the host, as well as defining the gut microbiome, is necessary to explain the clinical observations in females with ILD. TGF-b1 is the master regulator of fibrosis. Figure 6 demonstrates that TGF-b1 is most predominant in female sarcoidosis patients. In Figure 4, we see that gut dysbiosis augments lung fibrosis. When IL-6 induction occurs, downstream signaling can lead to either IL-17A or TGF-B1 expression. IL-17A expression leads to pulmonary inflammation. Estrogen signaling provides protection against proinflammatory fibrosis due to the capacity of the ERa to bind to the STAT3 promoter . This reduction in lung inflammation improves the prognosis. In menopausal females, the gut microbiome continues to drive lung fibrosis, but due to the reduced estrogen state, there is no inhibition of STAT3 expression and Th17 cell development. Lung fibrosis can now be mediated by IL-17A, which likely explains the increased symptoms after menopause. There are some limitations that should be noted. This investigation focused on female ILD; investigations of the role of testosterone in lung fibrosis are needed. There are also reports indicating that estrogen drives Th17 cell differentiation in chronic lung diseases, such as asthma . Concomitant immune-gut microbiome investigations of asthma models with ILD models are warranted, including an inquiry into the interplay of gonadal hormones. Additionally, asthma pathogenesis is very distinct from ILD, which may also impact T cell differentiation. Another consideration is that the gut microbiome is influenced by diet. The mice in the murine model had the same diet; future studies assessing the impact of food consumption on the gut microbial community, metabolomic syndromes and inflammation are warranted . An investigation into the impact of gut dysbiosis on estrogen signaling or of estrogen signaling on gut microbial communities is warranted. Finally, we observed Th17 cell populations increasing following the gavage of ABSL-2 stool into germ-free mice compared to the gavaging of ABSL-1 stool. Future analysis definitively identifying the microorganism(s) responsible for Th17 cell differentiation is warranted, followed by an assessment of their presence in the stool of murine asthma models, as well as asthmatic patients and ILD patients. 5. Conclusions Taken together, this investigation demonstrates that female gonadotrophic hormones are profibrotic yet, through the ERa binding of the STAT3 locus, reduce the inflammation induced by IL-17A expression in CD4+ T cells. The consequent reduction in inflammation is a likely contributor to the mortality benefit observed in premenopausal females with ILD. This study introduces another key contributor to lung fibrosis severity: gut dysbiosis. The synergistic impact of gut dysbiosis and estrogen on lung fibrosis supports a multi-pronged approach to the treatment of female-predominant lung fibrosis . Acknowledgments We gratefully acknowledge the sarcoidosis, IPF and Ssc patients for their willingness to participate in this research study, as well as the clinical providers, including Robert P. Baughman, who helped identify patients. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Loss of estrogen receptor alpha subunit (ESR-1) improves male survival and augments fibrosis. Figure S2. Ovariectomized mice display decreased lung fibrosis. Table S1. Mouse strains used in this study. Table S2. Flow cytometric antibodies used in this study. Table S3. Genomic regions demonstrating ERa binding in T-cells in the locus of STAT3. Chromosome positions are given in hg38 coordinates. Statistics are calculated by MACS2. Table S4. Sample demographics of ChIP-seq donors and resulting data. Remaining reads count the number of trimmed, decontaminated reads following FASTQ preprocessing. The percentage of properly paired, aligned reads is given, as is the number of peaks identified by MACS2 for each sample relative to the input sample. Table S5. Significantly enriched functional categories for genes associated with ERa binding regions by GREAT. Significantly enriched categories met a binomial FDR Q-value threshold of 5%. Click here for additional data file. Author Contributions Conceptualization, L.V.K., D.C.N. and W.P.D.; Methodology, E.M.W.; Formal analysis, E.M., J.E.J., C.G.M. and S.B.; Investigation, E.M., B.S.-G., Z.W., M.L., A.W.L., H.W., L.L., C.G.M. and D.C.N.; Resources, E.M.W. and W.P.D.; Writing-original draft, O.S.C.; Writing-review & editing, E.M., A.G., L.V.K., S.B., D.C.N. and W.P.D.; Supervision, L.J.C. and W.P.D.; Project administration, W.P.D.; Funding acquisition, L.J.C. and W.P.D. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Vanderbilt University Medical Center. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement All of the sequences obtained from the lung and gut microbiome analysis of germ-free ABSL-1 and ABSL-2 mice have been deposited into BioProject ID, Accession number PRJNA899808. Conflicts of Interest L.V.K. is a member of the scientific advisory board of Isu Abxis Co., Ltd. (South Korea). The other authors have declared that there are no existing conflicts of interest. Code Availability Statement The code for all of the analyses can be found at github.com/emallott/PulmonaryFibrosisMicrobiota. Figure 1 Genomic visualization of ESR1 or ESRRA binding activity at the STAT3 gene locus. (A) Gene annotations indicate the position of STAT3, its exons (thick bars) and introns (connecting arrows showing the direction of translation). Blue tracks indicate the enrichment of the ChIP-seq signal for ESR1 or ESRRA binding over the background input for five cell lines. Sharp, prominent peaks provide evidence for the ability of these transcription factors to bind STAT3, demonstrating their interaction in these cell types. (B) Track visualization of ERa ChIP-seq for the STAT3 locus. Primary CD4+ T-cell ERa ChIP enrichment signal (red) is depicted against the input chromatin signal (black). Rectangular regions above the ChIP track indicate regions significantly enriched with ERa binding. Top: Additional tracks indicate positions of ESR1 or ESRRA binding activity in ChIP-seq data from the ENCODE project. Note that ERa binding events are not typically shared from experiment to experiment, even when cell lines are identical. Bottom: DNase and H3K27ac signal from the ENCODE project, indicating regions of strong enhancer activity in general cell lines. ERa-binding regions in T-cells occur in areas with known chromatin accessibility. Figure 2 Loss of estrogen receptor alpha subunit (ESR-1) improves survival and ameliorates fibrosis in female mice. WT and ESR-/- mice were treated with bleomycin and monitored for 14 days. (A) Body weights of mice at day 8 compared to day 0; (B) Murine mortality across 14 days. Kaplan-Meier survival analysis with a log-rank test was used to determine differences between groups. Flow cytometric analysis of T cells from single-cell lung suspensions at day 14 for (C) IL-6, (D) IL-23R, (E) pSTAT3Y705 and (F) IL-17A. Comparisons between cohorts were performed using one-way ANOVA with Tukey's post hoc test. * p < 0.05, ** p < 0.01, *** p < 0.001; **** p < 0.0001; ns: no significance. Bars are the mean +- SD; each symbol represents an individual mouse. WT: Wild-type, ESR-1-/- estrogen receptor alpha knockout mice. N = 4-15. Figure 3 In vivo administration of female hormones increases profibrotic cytokine expression in ovariectomized mice. Hormone-containing or placebo pellets were implanted into ovariectomized C57BL/6 female mice for 21 days, followed by bleomycin administration and monitoring for an additional 14 days. (A) Body weights of mice at day 8 after bleomycin administration; (B) Murine mortality across 14 days; (C) Flow cytometric analysis of T cells from single-cell lung suspensions for (D) IL-6, (E) GP130, (F) pSTAT3Y705 and (G) IL-17A. (H) Representative FACS plots illustrating CD4+ percentage in bleomycin-treated murine cohorts. Comparisons between cohorts were performed using one-way ANOVA with Tukey's post hoc test. * p < 0.05, ** p< 0.01, **** p < 0.0001. ns: no significance; RLL: right lower lobe. Bars are the mean +- SD; each dot represents an individual mouse. N = 3-12 per cohort. Figure 4 Quantification of bleomycin-induced pulmonary collagen with various hormone deletion or repletion conditions in distinct housing environments. (A) Representative H&E and trichrome histologic stains of lungs at day 14 under various hormone conditions; (B) Pulmonary collagen quantification of the lung under baseline, hormone depletion and hormone repletion conditions. (C) Pulmonary collagen quantification of the lung under wild-type (WT) and ESR1 null conditions; (D) Pulmonary collagen quantification in menstruating female mice housed in germ-free, ABSL-1 and ABSL-2 environments; (E) Pulmonary collagen quantification of ovariectomized and estrogen-repleted mice in ABSL-1 and ABSL-2 environments. Comparisons between cohorts were performed using one-way ANOVA with Tukey's post hoc test. * p < 0.05, *** p< 0.001, **** p < 0.0001. ns: no significance; RLL: right lower lobe. Bars are the mean +- SD; each dot represents an individual mouse. N = 5-14. Figure 5 Murine female gut microbial diversity is modified by housing environment. (A) Shannon diversity index, Pielou's evenness and species richness scores for female mice housed in ABSL-1 and ABSL-2 facilities following bleomycin inoculation (N= 9-14 mice per cohort). The boxes show the median, as well as the 25th and 75th quartiles. The whiskers extend to 1.5*IQR. Each dot represents one mouse. (B,C) Comparison of female and male Shannon diversity index, Pielou's evenness and species richness scores for female mice housed in ABSL-1 and ABSL-2 facilities following bleomycin inoculation (n =14-16 mice per cohort). (D) Nonlinear multidimensional scaling (MDS) plot showing differences in microbial taxonomic composition based on Jaccard dissimilarities. (E) Nonmetric multidimensional scaling plot based on Bray-Curtis and Jaccard dissimilarities showing the gut microbiome by gender of murine communities housed on ABSL1 and ABSL2 floors. Figure 6 Male and female sarcoidosis patients display distinct profibrotic cytokine profiles. Purified CD4+ T cells from the peripheral blood of healthy controls and sarcoidosis patients were anti- anti-CD28 TCR-stimulated and cultured for 24 h, followed by real time-PCR for (A) STAT3, (C) RORC, (F) IL-17A; flow cytometry for (B) pSTAT3Y705, (D) RORC, (G) IL-17A, (I) LAP/TGF-b1; (E) cytokine bead array for IL-6 and (H) enzyme-linked immunosorbent assay for free TGF-b1 analysis. (J) Estradiol levels in serum of healthy controls, IPF and scleroderma male patients. Comparisons between cohorts were performed using one-way ANOVA with Tukey's post hoc test. Bars are the mean +- SD; each dot is an individual patient. * p < 0.05, ** p < 0.01, *** p > 0.001, **** p < 0.0001. ns: no significance, HC: healthy controls, S: sarcoidosis, Ssc: systemic sclerosis, IFP: idiopathic pulmonary fibrosis. Figure 7 Graphical abstract of the interaction of gonadal hormones and gut dysbiosis in lung fibrosis. (A) IL-6 induces profibrotic cytokine expression through IL-17A and TGF-b1 expression. IL-17A drives inflammation in fibrotic lung tissue. (B) The alpha subunit of the estrogen receptor (ERa) serves as a transcription factor and physically binds to the STAT3 promoter, thus inhibiting the Th17 cell-mediated inflammation associated with fibrosis. (C) The presence of estrogen and gut dysbiosis augments lung fibrosis through TGF-b1 expression, thus demonstrating that multiple factors contribute to lung fibrosis pathophysiology. cells-12-00766-t001_Table 1 Table 1 Demographic information of the sarcoidosis, IPF, and scleroderma patients and the healthy control subjects used in this study. 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PMC10000460 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050843 diagnostics-13-00843 Systematic Review Systemic Immune-Inflammation Index and Mortality in Testicular Cancer: A Systematic Review and Meta-Analysis Salazar-Valdivia Farley E. 12 Valdez-Cornejo Valeria A. 12 Ulloque-Badaracco Juan R. 1 Hernandez-Bustamante Enrique A. 34 Alarcon-Braga Esteban A. 12 Mosquera-Rojas Melany D. 12 Garrido-Matta Diana P. 1 Herrera-Anazco Percy 56 Benites-Zapata Vicente A. 7* Hernandez Adrian V. 89 Neuhaus Jochen Academic Editor 1 Escuela de Medicina, Universidad Peruana de Ciencias Aplicadas, Lima 15023, Peru 2 Sociedad Cientifica de Estudiantes de Medicina de la Universidad Peruana de Ciencias Aplicadas, Lima 15023, Peru 3 Sociedad Cientifica de Estudiantes de Medicina de la Universidad Nacional de Trujillo, Trujillo 13011, Peru 4 Grupo Peruano de Investigacion Epidemiologica, Unidad para la Generacion y Sintesis de Evidencias en Salud, Universidad San Ignacio de Loyola, Lima 15012, Peru 5 Escuela de Medicina, Universidad Privada San Juan Bautista, Lima 15067, Peru 6 Universidad Privada del Norte, Trujillo 13011, Peru 7 Unidad de Investigacion para la Generacion y Sintesis de Evidencias en Salud, Vicerrectorado de Investigacion, Universidad San Ignacio de Loyola, Lima 14072, Peru 8 Unidad de Revisiones Sistematicas y Meta-analisis, Guias de Practica Clinica y Evaluaciones de Tecnologia Sanitaria, Vicerrectorado de Investigacion, Universidad San Ignacio de Loyola, Lima 15012, Peru 9 Health Outcomes, Policy, and Evidence Synthesis Group, University of Connecticut School of Pharmacy, Mansfield, CT 06269, USA * Correspondence: [email protected]; Tel.: +51-1-3171000 22 2 2023 3 2023 13 5 84310 11 2022 19 1 2023 26 1 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The systemic immune-inflammation index (SIII) is a marker studied in multiple types of urologic cancer. This systematic review evaluates the association between SIII values with overall survival (OS) and progression-free survival (PFS) in testicular cancer. We searched observational studies in five databases. The quantitative synthesis was performed using a random-effects model. The risk of bias was assessed using the Newcastle-Ottawa Scale (NOS). The only measure of the effect was the hazard ratio (HR). A sensitivity analysis was performed according to the risk of bias in the studies. There were 833 participants in a total of 6 cohorts. We found that high SIII values were associated with worse OS (HR = 3.28; 95% CI 1.3-8.9; p < 0.001; I2 = 78) and PFS (HR = 3.9; 95% CI 2.53-6.02; p < 0.001; I2 = 0). No indication of small study effects was found in the association between SIII values and OS (p = 0.5301). High SIII values were associated with worse OS and PFS. However, further primary studies are suggested to enhance the effect of this marker in different outcomes of testicular cancer patients. testicular cancer meta-analysis overall survival progression free survival systemic immune-inflammation index This research received no external funding. pmc1. Introduction According to GLOBOCAN, 74,458 new testicular cancer cases and 9334 deaths were estimated in 2020, of which 33.7% were in Europe and 27.7% were in Asia. However, Asia has a wide advantage regarding mortality, with a rate of 42.8% . The worldwide incidence of these tumors has more than doubled in the last 40 years . By 2025, an increase in incidence is anticipated for Europe, Latin America, some parts of Asia, and even in areas where the incidence is relatively low . This type of cancer is the most common in young adult men between the ages of 15 and 34 years, representing 1.5% of male neoplasms and 5% of urological tumors, in general. Testicular cancer can be classified, according to histopathology, into germ cell tumors and non-germ cell tumors, of which germ cell tumors account for 98% . The former, in turn, are classified as seminomas, which are the most common in adults and patients with cryptorchidism or non-seminomas . Genetic and environmental factors will influence the increase in incidence. Various diseases, including Down syndrome and testicular dysgenesis syndrome, are linked to an increased risk of testicular cancer . Thanks to the substantial advances in the treatment of testicular cancer in recent decades, this is the most curable solid malignancy . The literature reports various risk factors related to a poor prognosis in testicular cancer. Among the most studied factors, age over 35 years, serum alpha-fetoprotein above 1000 Ku/L before chemotherapy, and human chorionic gonadotropin above 5000 IU/L stand out . Likewise, an interval between orchiectomy and the start of chemotherapy of fewer than three weeks, high-volume metastatic load, and the treatment site are reported . Recently, the association between a poor cancer prognosis and different inflammatory markers has been described. A study using systemic inflammatory markers, based on preoperative complete blood count, found that neutrophils, the neutrophils to lymphocytes ratio (NLR), and the mean red blood cell distribution width were significantly higher in the tumor group. In contrast, the mean volumes of platelets and lymphocytes were significantly higher in the cancer-free group . As well as these markers, the NLR, the platelets to lymphocytes ratio (PLR), the monocytes to lymphocytes ratio (MLR), and the preoperative albumin to globulin ratio have been identified . In 2014, the systemic immune-inflammation index (SIII), defined as SIII = P x N/L, was used for the first time, using lymphocyte (L), neutrophil (N), and platelet (P) counts, thus providing a strong predictive factor for the prognosis of patients with hepatocellular carcinoma . Its use in various cancers is currently being investigated; however, regarding its use in testicular cancer, it is believed that SIII can obtain more robust data than routine markers on staging and cancer prognosis, knowing that a high SIII reflects a worse prognosis . Due to the evidence for the use of SIII in testicular cancer, these results should be combined to provide clinicians with a more reliable tool. This study aimed to evaluate the association between SIII and survival outcomes in testicular cancer. 2. Methods 2.1. Research Question and Study Design We used the PECO strategy: population (P), exposure (E), comparison (C), and outcome (O) to guide the main objective of this systematic review. Based on the PECO strategy, we ask the following question: Do patients with testicular cancer (P) and high values of SIII (E) have worse overall survival and progression-free survival (O) than patients with testicular cancer and low values of SIII (C)? 2.2. Register and Report Guideline We registered the study protocol on the International Prospective Register of Systematic Reviews (PROSPERO). The register code is CRD 42021281533. Likewise, we used the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement (see the PRISMA checklist in Supplementary Table S1) and the Cochrane Handbook of Systematic Reviews . 2.3. Search Strategy and Data Sources A comprehensive literature search was performed by searching the following databases: PubMed, Scopus, Web of Science, Embase, and Cochrane Library. In addition, a manual search was performed in pre-print platforms, such as MedRxiv and Scielo preprints, with the purpose of including as many articles as possible within our study related to the studied subject. The search strategy was developed using the Peer Review of Electronic Search Strategies (PRESS) checklist . No language restrictions were applied. 2.4. Eligibility Criteria, Study Selection, and Data Extraction We included studies that: (i) evaluated the association between the systemic immune-inflammation index (SIII) and testicular cancer reporting outcomes, such as progression-free survival (PFS) and overall survival (OS), (ii) included males with a confirmed diagnosis of testicular cancer, and (iii) items that provide a defined cut-off value for the systemic immune-inflammation index (SIII) (see the inclusion and exclusion criteria of the patients for each study in Supplementary Table S2). To manage the data, we used the Rayyan QCRI software (Rayyan Systems Inc.(c), Cambridge, MA, USA) to help in the screening and selection of studies . Four authors (FES-V, VAV-C, JRU-B, and EAH-B) independently screened the titles and abstracts of the retrieved records. The titles and abstracts that met the inclusion/exclusion criteria went on to the next phase of the selection process. Then, we independently assessed the remaining records using the full text of each study. Any conflict in the selection process was resolved by reaching a consensus among all the authors. Finally, all the data from the selected studies were extracted by the authors (FES-V, VAV-C, JRU-B, and EAH-B) with a special data collection card in a standardized file in Microsoft Excel and imported into the Mendeley platform for reference purposes. The entire study selection is shown in the PRISMA flow chart . We collected the following data: author, year, country, median follow-up time, participants' median/mean age, the type of testicular cancer, cut-off values, and associations between systemic immune-inflammation index values and overall survival or progression-free survival (see definitions of the outcomes for each study in Supplementary Table S3). 2.5. Quality Assessment The quality of the study was assessed using the Newcastle-Ottawa Scale (NOS) for case-control/cohort studies, by two authors (FES-V and VAV-C), based on 3 different items: selection, comparability, and outcome/exposure . The maximum that can be achieved in a study is 9 points; a score >=7 points was considered a low risk of bias; otherwise, <=6 points was considered a high risk of bias. Any disagreement was resolved by reaching a consensus among all authors. 2.6. Data Synthesis and Publication Bias The information collected from the selected articles was combined using Review Manager 5.4 (RevMan 5.4) (The Cochrane Collaboration, Copenhagen, Denmark). Hazard ratios (HRs) and 95% confidence intervals (CIs) were the only measures used to obtain a pooled effect. We used a random-effects model (DerSimonian and Laird) for the quantitative analysis. The heterogeneity of the studies was evaluated using Cochran's Q test with a p-value of <0.1 and an I2 statistic with values >70% as a sign of severe heterogeneity. A sensitivity analysis was performed, excluding articles with low methodological quality, to test the robustness of our findings. Egger's test was carried out to assess publication bias; p-values less than 0.1 indicated publication bias . 3. Results 3.1. Research Question and Study Design We identified 72 articles, leaving 50 studies after eliminating duplicates. The screening process evaluating titles and abstracts left 13 studies for full-text review. Likewise, the full-text screening left five studies that met all the selection criteria . Figure 1 summarizes the study selection process. 3.2. Study Characteristics Four studies were included from a total of five cohorts since the study by Chovanec et al. analyzed two cohorts. All cohorts analyzed OS, and only three cohorts analyzed PFS. In addition, two cohorts were conducted in Slovakia, one in Turkey, one in China, and one in Japan. The included studies were conducted between 2017 and 2021. The total number of participants was 833. The age of the participants ranged from 16 to 84 years. The most frequent type of testicular cancer was germ cell tumor, and the median follow-up time ranged between 39.2 and 63.4 months. Four cohorts evaluated the optimal SIII cut-off values for OS and PFS, ranging from 719 to 1428. The details of the included articles are summarized in Table 1. In the quality assessment of the included articles, four cohort studies had a low risk of bias, whereas only one study had a high risk of bias due to problems in cohort comparability on the basis of design or analysis and follow-up that was not long enough for the outcomes to occur (Supplementary Table S4). 3.3. Association between SIII Values and OS in Testicular Cancer The association was assessed in five cohorts (n = 805). However, only four studies were included in the meta-analysis (the study by Frankhauser CD et al. was not included in the meta-analysis because they reported an association HR per 10-fold increase (log10 [HR]: 30.2, 95% CI 3-304; p < 0.05, which could alter and bias our results). In the meta-analysis, we found that testicular cancer patients with high SIII values were associated with worse OS (HR: 3.07; 95% CI 1.1-8.54; p < 0.001; I2 = 83) . Due to the severe heterogeneity, a sensitivity analysis was performed where only studies with a low risk of bias were included, where the association was maintained. (HR: 5.15; 95% CI 3.08-8.6; p < 0.001) but with null heterogeneity (I2 = 0%) . 3.4. Association between SIII Values and PFS in Testicular Cancer The association was assessed in four cohorts (n = 443). We found that testicular cancer patients with high SIII values were associated with worse PFS (HR: 3.68; 95% CI 2.32-5.83; p < 0.001) with null heterogeneity (I2 = 0) . 3.5. Publication Bias Publication bias could not be determined because there were no more than five meta-analyzed studies in any of the outcomes. 4. Discussion Our main results show that a high SIII value is associated with worse OS and PFS in patients with testicular cancer. This reflects the role of inflammation in the genesis and progression of several types of cancer, including urological cancers. In tumor genesis, inflammation mediates the creation of reactive oxygen species and the activation of cell signaling pathways that promote cell proliferation and limit apoptosis . In the progression of malignancy, it influences the cellular components of the immune system, and its chronic state stimulates immunity and is associated with a poor prognosis . In this sense, several studies have demonstrated the importance of some inflammatory markers in the prognosis of cancer patients, such as the lymphocyte/monocyte ratio, which is a prognostic indicator in head and neck cancer , rectal cancer , ovarian cancer and cholangiocarcinoma . We also have the NLR, which is a prognostic indicator in melanoma , endometrial cancer , or solid tumors . Similarly, the PLR can be used in rectal cancer , gastric cancer , cholangiocarcinoma , and head and neck cancer . As a tumor marker, SIII reflects the balance between host inflammation and immune response status . Likewise, it reflects systemic inflammation in a more balanced manner and has a higher predictive value than other inflammatory markers in patients with cancers . Several studies have shown the role of SIII as a prognostic marker in cancers. In this regard, the role of SIII was shown to predict worse OS in patients with colorectal cancer, breast cancer, hepatocellular carcinoma, small cell lung cancer, acral melanoma, and gastric and esophageal cancer . Although the reasons are not entirely clear, it is suggested that it has to do with the individual effect of the SIII components. SIII is based on peripheral neutrophil, platelet, and lymphocyte count. Therefore, high SIII corresponds to high platelet/neutrophil and/or low lymphocyte counts . In the case of neutrophils, their presence is associated with poor prognosis in cancer patients because they can activate endothelial and parenchymal cells that facilitate metastasis of circulating tumor cells . In addition, neutrophils also mediate cancer cell proliferation and metastasis by secreting inflammatory mediators and angiogenic proteins that participate in tumor cell proliferation, migration and invasion, and tumor immunosuppression in the stages of carcinogenesis . On the one hand, platelets can protect circulating tumor cells from the antitumor immune response and promote the angiogenesis and metastasis of cancer cells . In vitro, platelets also release various growth factors that enhance cancer cell proliferation . Likewise, platelets can also recruit and activate granulocytic cells in tumor tissues, and thus, may be essential for generating tumor-associated neutrophils . Moreover, lymphocytes, especially tumor-infiltrating lymphocytes, play a key role in the host's immune response to cancer . They can also induce cell death and inhibit tumor cell proliferation and migration . Lymphocytes are responsible for the adaptive immune response and participate in cancer immunosurveillance and immunoediting . Lymphopenia usually indicates the severity of the disease; it helps cancer cells escape from the immune system of tumor-infiltrating lymphocytes, whose formation is related to the process of lymphocyte migration to the tumor microenvironment, so a decreased level of tumor-infiltrating lymphocytes predicts worse survival in cancer patients . Although no studies have been conducted in this regard, there is no reason why, to date, these mechanisms suggested in cancers, in general, should not also be considered for application to patients with testicular cancer. Several systematic reviews evaluating the prognostic role of SIII in urological cancers have been published. A systematic review of 15 articles found, in subgroup analyses, that high SIII indicated a worse overall survival rate in urinary cancers and hepatocellular carcinoma, gastrointestinal tract cancers, small cell lung cancer, and acral melanoma . Another systematic review of 22 articles showed that SIII over the cutoff value could predict worse overall survival in urinary system cancer, hepatocellular carcinoma, gastric cancer, esophageal squamous cell carcinoma, small cell lung cancer, non-small cell lung cancer, and acral melanoma . From the combined data of 13 papers, it was found that a high pre-treatment SIII indicated markedly worse OS, PFS, and cancer-specific survival . Finally, from the pooled results of 14 studies, it was found that high SIII was associated with worse OS in patients with urologic cancers. Patients with high SIII values also had poorer PFS and cancer-specific survival as well as lower OS than patients with low SIII values. In addition, the subgroup analysis of OS and PFS showed that the prognosis of patients with high SIII was worse than that of patients with low SIII . However, only one included a study of patients with testicular cancer . This systematic review of 12 studies with 2693 patients included the study by Yang J et al. , which is also part of our study and contributed 28 patients to that review. The authors found that a high SIII value was associated with worse OS, PFS, and cancer-specific survival rates in patients with various urological cancers, including bladder, renal cell, and prostate carcinoma . Therefore, our study would be the first systematic review evaluating the association between SIII patients' survival outcomes in testicular cancer. Our results show the potential role of SIII in survival outcomes of patients with testicular cancer and being an easy-to-measure and low-cost marker. However, this biomarker, in comparison with other inflammatory markers used to predict the prognosis of urological cancers, such as NLR , PLR , and C-reactive protein/albumin ratios , contains three types of peripheral blood inflammatory cells, simultaneously . This characteristic is relevant, as it better reflects the balance between inflammation and the body's immune response, so it could be a better marker . This is a hypothesis that needs to be corroborated in further studies. Furthermore, even though it was not explicitly evaluated for testicular cancer, in other systematic reviews, the association between a high SIII value and OS and PFS in patients with urologic cancers did not vary significantly according to tumor subtypes, cancer stages, sample sizes, study types, treatment methods, NOS scores, or a cut-off point defining elevated SIII . This last point is relevant considering the wide range of SIII values in the studies included in our systematic review, like other reviews on the prognostic value of this biomarker in urologic cancers . However, it is necessary to consider the ethnic component in assessing this biomarker since some studies show that the European population is more sensitive to this marker than the Asian population . Additionally, the sensitivity analysis considering only the studies with a low risk of bias, allowed us to reaffirm our results. Finally, the applicability of SIII in clinical practice remains conceptual due to flaws in the design of studies. Most studies are retrospective with different cut-off points, measurement time points, and chosen endpoints, and although many studies adjusted their analysis for various factors, unmeasured confounders cannot be excluded . Regarding meta-analyses that evaluated its usefulness, the retrospective design and the heterogeneity between the studies that make them up, limit the strength of this type of study, and the sensitivity analysis often alters the results obtained in a first evaluation . Consequently, even though it is a promising marker, we cannot state that it is better than others that are available to assess the prognosis of these patients, which merits further studies on this topic. In our study, we found limitations that should be considered. Firstly, due to the small number of studies, it was impossible to perform a correct stratification of results according to the clinical or sociodemographic variables of the patients. Secondly, it was only possible to study the association of SIII values with two clinical outcomes, so it would be necessary for future studies to study the association with other outcomes. Third, high statistical heterogeneity was found due to the methodological and clinical differences between the studies. However, heterogeneity decreased when the sensitivity analysis was performed, which only included a low risk of biased studies. Finally, sensitivity and specificity values of the SIII cut-off points in OS and PFS have not been reported, which could help evaluate the precise prognostic value of this biomarker in testicular cancer. 5. Conclusions High SIII values are associated with worse OS and PFS. However, further primary studies are suggested to enhance the effect of this marker in different outcomes of testicular cancer patients. Supplementary Materials The following supporting information can be downloaded at: Table S1: PRISMA checklist, Table S2. Inclusion and exclusion criteria for patients in the studies, Table S3: Outcome definitions of included studies; Table S4: Newcastle-Ottawa quality assessment scale for included studies. Table S5: Search Strategy. Click here for additional data file. Author Contributions Conceptualization, F.E.S.-V., V.A.V.-C., J.R.U.-B., E.A.A.-B., M.D.M.-R., E.A.H.-B., P.H.-A., V.A.B.-Z. and A.V.H.; data curation, F.E.S.-V., M.D.M.-R., V.A.V.-C. and V.A.B.-Z.; formal analysis, F.E.S.-V., V.A.V.-C., J.R.U.-B., M.D.M.-R., E.A.A.-B., V.A.B.-Z. and A.V.H.; methodology, F.E.S.-V., V.A.V.-C., J.R.U.-B., E.A.A.-B., E.A.H.-B., V.A.B.-Z., D.P.G.-M. and A.V.H.; writing--original draft, F.E.S.-V., V.A.V.-C., J.R.U.-B. and V.A.B.-Z.; writing--review and editing, F.E.S.-V., V.A.V.-C., J.R.U.-B., E.A.A.-B., E.A.H.-B., P.H.-A., D.P.G.-M., A.V.H. and V.A.B.-Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PRISMA flow diagram. Figure 2 (a) Association of SIII values and OS in patients with testicular cancer . (b) Sensitivity analysis according to the risk of bias of the association between SIII values and OS in patients with testicular cancer . Figure 3 Association of SIII values and PFS in patients with testicular cancer . diagnostics-13-00843-t001_Table 1 Table 1 Characteristics of the included studies. Author Year Country Median Follow-Up Time Participants Median/Mean Age (IQR/SD) Type of Testicular Cancer Outcome HR (95% CI), p-Value Cut-Off Emre Y et al. 2021 Turkey 55 months 244 38 (10) Mixed Overall Survival 1.004 (0.5376-1.875), p = 0.99 719 Frankhauser CD et al. 2018 Switzerland 53 months 146 34 (9) Mixed Overall Survival 30.2 (3-304), p < 0.05 a 1428 Yoshinaga Y et al. 2021 Japan 63.4 months 63 35 (16-67) Germ cell tumor Overall Survival 4.87 (0.59-40.47), p = 0.14 NR Progression free-survival 2.49 (0.79-7.85), p = 0.12 Chovanec M (Cohort A) et al. 2017 Slovakia 49 months 171 30 (17-62) Germ cell tumor Overall Survival 6.1 (3.11-11.95), p < 0.05 1003 Progression free-survival 4.48 (2.44-8.23), p < 0.05 Chovanec M (Cohort B) et al. 2017 Slovakia 85 months 181 30 (16-67) Germ cell tumor Overall Survival 6.49 (2.1-20.03), p < 0.05 1003 Progression free-survival 3.03 (1.23-7.46), p < 0.05 NR, not reported; a, After log10 transformation: the HR thus corresponds to a 10-fold increase in the variable. 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PMC10000461 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051032 foods-12-01032 Article Exploring Key Factors Driving Urban Foraging Behavior in Garden and Non-Garden Locations Rombach Meike Conceptualization Resources Writing - original draft Writing - review & editing Project administration 1* Dean David L. Methodology Software Formal analysis Data curation Supervision 2 1 Department of Land Management and Systems, Lincoln University, Lincoln 7647, New Zealand 2 Department of Agribusiness and Markets, Lincoln University, Lincoln 7647, New Zealand * Correspondence: [email protected] 28 2 2023 3 2023 12 5 103231 1 2023 23 2 2023 27 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Since the occurrence of COVID-19 and food price inflation, alternative forms of food procurement increased in popularity. The present study is dedicated to urban foraging and aims to explore key factors driving food foraging behavior in the U.S. Two specific foraging behaviors, namely "leaving food behind" or "taking it all", have been investigated in a gardening and non-gardening location. Leaving food behind is crucial to sustainable foraging practices, as it allows plants and ecosystems to recover and promotes fairness in foraging communities. Data was procured from an online consumer survey and analyzed using SmartPLS 4, which allowed the use of partial least square structural equation modeling (PLS-SEM). PLS-SEM is particularly suitable for complex exploratory studies as it does not require distributional assumptions. Results indicate that nature and food attitudes predict attitudes toward urban foraging. Foraging attitudes, such as food foraging is challenging and food foraging benefits people and the planet, which are the most important drivers for taking or leaving behaviors in both types of locations. These findings are of relevance to managers in municipalities, landscape designers, horticultural businesses, and other stakeholders who create, shape, and govern landscapes used for food foraging. alternative food procurement foraging attitudes urban foraging This research received no external funding. pmc1. Introduction For the past decade, alternative means of food consumption and procurement have been increasing in popularity in the U.S. . These correspond with rises in urban horticulture, green cities, and the establishment of informal initiatives and formal programs to build community gardens or plant trees . Since the occurrence of COVID-19, the trend has broadened to include home gardening, do-it-yourself, and food foraging, which some attribute to regional recessions and food price inflation in the U.S. . Food foraging is a consumer behavior that refers to the self-provisioning of plants found in rural and urban landscapes that are suitable for human consumption . It requires searching, identifying, and collecting wild edible plants, such as fruits, nuts, mushrooms, herbs, and roots . Evidence for the increase in popularity of food foraging includes foraging tours and online and face-to-face classes offered by educational providers in the U.S., with notable offerings from Washington College and Masterclass . Less formal examples include the California-based "ForageFS", which offers tours to learn how to harvest mushrooms, wild plants, and seaweed . Similarly, the "Beacon Food Forest" in Seattle offers environmental education and foraging events. In addition, there are private and governmental web pages that provide advice on foraging locations and practices . For instance, the project "Falling Fruit" displays locations around the US where food foraging is permitted. Small dots pinpoint these foraging locations and provide species information and suggest the appropriate windows to harvest fruit. These information sources provide links to the U.S. Department of Agriculture's (USDA) homepage for further information . Furthermore, food foraging is discussed and organized in social media groups and apps . Food foraging allows U.S. consumers to mitigate some food insecurity while feeling a closer connection to nature . Both aspects are beneficial as COVID-19 brought hardship to many communities, and in its initial stages posed a risk to physical and mental well-being . Since the beginning of the pandemic, well-being, unemployment, reduced available household incomes, and food insecurity were reasons that generated people's interest in home food procurement, including food foraging . Data from the Bureau of Labor Statistics indicates higher unemployment rates from 2020 to 2021 than before the pandemic, and a household survey conducted by the United States Census Bureau reported that 48% of the respondents felt either depressed or anxious. Concerning food insecurity, the Economic Research Service of the USDA emphasizes that over 10% of households were food insecure in 2020 and 2021 . Lockdowns and physical distance limitations led to a decrease in exposure to nature and a reduction in well-being. For many U.S. citizens, contact with nature reduces stress and improves their quality of life . Despite these benefits, some U.S. cities do not permit food foraging and consider it to be illegal . Urban foraging is forbidden in traditional conservation areas, as the activity could threaten specific species or the overall ecosystem stability . Webpages dedicated to individual states, such as "Foraging Texas" outline the legal situation, ethical foraging behavior, and plant species being permitted or forbidden to harvest across locations and times of the year . The best practice recommendation on these web pages aligns with findings from the extant literature . Following Ticktin (2004) and Schunko et al. (2021), food foraging may negatively impact individual plant species' ability to grow and reproduce. This could result in adverse effects on plant populations, plant communities, and on the overall ecosystem . In addition, food foraging can be discouraged, if not actively restricted, in intensively managed parks and greenspaces . The restrictions often allow municipalities to perform maintenance work undisturbed and avoid vandalism, dog exposure, injury, or disrespect towards sites with specific purposes, such as botanic gardens or graveyards . In terms of location and food foraging practice, the recent body of literature addresses best practice recommendations for food foraging. These acknowledge the needs of foragers, ecosystems, and legal frameworks . Consequently, food foragers should be knowledgeable of plant species and responsible selection practices . Various studies emphasize the importance of carefully selecting species and locations . It is considered irresponsible to forage plants susceptible to harvesting pressure or those under protection . Instead, responsible foraging practices include foraging in multiple locations to allow plants to regrow and conscious harvesting to avoid damaging branches or root systems. Overall, plant knowledge and sustainable practice considering ecosystems and other foragers is required . Schunko et al. (2021) discuss seasonal-appropriate foraging times and practices that are considered as best practices . For example, foragers should avoid young plants, which are unripe, and avoid any practice that disturbs maintenance activities in public greenspace . While these practices and food-foraging behavior have been investigated as a social phenomenon, various people and plant disciplines contribute to the body of literature. Anthropological, sociological, ecological, agricultural, and forestry studies are common , but studies dedicated to consumer behavior are relatively scant. The recent body of literature indicates that food foraging takes place in various locations. While Shackleton et al. (2017) indicate that foraging takes place in rural, urban, and semi-urban areas , Landor Yamagata et al. (2018) outline private and public locations, for instance forests, allotment gardens, cemeteries, campuses, sports fields, and roadsides . Building on these studies, Fisher and Kowarik (2020) and Brandner and Schunko (2022) critically discuss that foraging behavior is varying within these locations. Brandner and Schunko (2022) emphasize that specific foraging behavior across locations and factors driving foraging behavior are yet to be explored in more detail . So far, only spatial factors influencing access to foraging behavior have been explored. Hence, this study aims to fill this research gap and contribute a new perspective by focusing on attitudinal and perceptional factors as drivers of foraging behavior. The present study examines critical factors driving U.S. consumers' food foraging behavior in varying locations. More precisely, the study focuses on the garden and non-garden locations with varying degrees of perceived appropriateness and looks specifically into whether U.S. foragers follow best practice recommendations and forage everything available or leave plants behind as an indication of their respect for nature and other foragers. 2. Background of the Study This section comprises a literature review supporting the conceptual model and the corresponding hypotheses . It also includes a description of the survey instrument, the sampling approach, as well as information about data collection and analysis. 2.1. Nature Experience Previous studies indicate that food foragers usually have pro-social and environmental attitudes and consider nature experiences essential to their lifestyle and identity . Nature is often experienced through food-sourcing-related activities, such as hunting and fishing, or recreational activities, such as camping, hiking, sailing, surfing, and boating . For individuals involved in foraging, sourcing food items and natural materials, such as wood or shells, are equally important as the nature experience itself . This is because such experiences allow them to be in contact with nature and feel emotionally and spiritually connected . The importance dedicated to outdoor activities and nature-relatedness is often instilled through family and childhood experiences or religion and value systems . Moreover, as consumers, these individuals consider the effects of their consumption choices on the environment and society . Due to the foraging activities and the strong connection between foragers and nature, foragers tend to have good knowledge about plants, ecosystems, the impact of foraging practices on nature as a whole, specific locations, and matters of legality . Amidst this background, the following multi-part hypothesis is proposed: Hypothesis 1 (H1). The importance that consumers dedicate to going out to experience nature positively impact consumers' food foraging attitudes and perception, such as (a) food foraging benefits societal wellbeing, (b) food foraging benefits people and the planet, (c) local foragers are knowledgeable, and (d) local food foraging is challenging. 2.2. Importance of Tending/Harvesting Nature and Food at Home The recent body of literature emphasizes a close connection between food foraging activities, such as growing plants, gardening, food production, food processing, as well as animal husbandry, as these activities allow for nature experiences, understanding of food production, the processes and resources required to obtain food, as well as self-sufficiency . In U.S. and European metropoles, books, and classes are offered on identifying and cooking with wild plants , which aim to increase the popularity of food foraging and foster connections between home-based and outdoor activities. Further studies emphasize the importance of complementary home-based/foraging activities to mitigate food insecurity and as a means to share knowledge and skills relevant to culture, ethnicity, or religion . As both types of activities impact foragers' attitudes and perceptions of the impact of their actions, the following muti-part hypothesis is proposed: Hypothesis 2 (H2). The importance that consumers dedicate to tending/harvesting nature and food at home positively impact consumers' food foraging attitudes and perception such as (a) food foraging benefits societal wellbeing, (b) food foraging benefits people and the planet, (c) local foragers are knowledgeable, and (d) local food foraging is challenging. 2.3. Foraging Is Good for Society's Well-Being, People, and Planet Previous studies have found that food foraging contributes to society's social well-being and development . Good practices among foragers require solidarity and redistributive justice since it is expected to leave food for other foragers . These values and practices have become even more critical since the occurrence of COVID-19, as various papers outline foraging as a means to mitigate hardship and food insecurity . In this context, Prost et al. (2019) describe food foraging as a participatory activity contributing to an active local food democracy. The authors emphasize the importance of relationships and landscape development . Various studies characterize food foraging as an ethical and sustainable activity arguing from social and economic perspectives. However, ecological studies criticize competitive foraging and selection pressures as drivers of unsustainable behavior . Plant knowledge, food preparation knowledge, good foraging practices, and gentle eco-tourism are crucial to environmental sustainability in a foraging context . Thus, the following hypotheses are proposed: Hypothesis 3 (H3). The importance that consumers dedicate to foraging as an activity that serves the good of societies' well-being impacts (a) consumers' taking or leaving intention in tended/patrolled non-garden locations, (b) consumers' taking or leaving intention in untended/unpatrolled non-garden locations, and (c) consumers' taking or leaving intention in tended/patrolled garden locations. Hypothesis 4 (H4). The importance that consumers dedicate to foraging as an activity that serves the good of people and the planet impacts (a) consumers' taking or leaving intention in tended/patrolled non-garden locations, (b) consumers' taking or leaving intention in untended/unpatrolled non-garden locations, and (c) consumers' taking or leaving intention in tended/patrolled garden locations. 2.4. Foraging Knowledge and Local Foraging Various studies have focused on food foraging knowledge having spoken with consumers in rural and urban areas and municipality officials . These studies emphasized foraging quantities, accessibility of locations, tools, dates, and knowledge of local plants and regulations, but their findings have been divergent . For instance, Garekae and Shackleton (2021) dedicated their work to formal and informal regulations governing food foraging . Their study uncovered that the majority of their survey respondents needed to be more knowledgeable of formal and informal rules governing food foraging and the use of urban landscapes . Similarly, Sardeshpande and Shackleton (2020) reported on the experiences of municipal officials and their stakeholder engagement with food foragers . A general lack of knowledge of wild plants, indigenous species, unsustainable foraging, and toxic soils was considered a reason to discourage foraging in urban areas . Both studies recommend policy, ecological and botanic education, and stakeholder management to improve sustainable foraging knowledge and local foraging practices . Hypothesis 5 (H5). The importance that consumers dedicate to foraging knowledge impact (a) consumers' taking or leaving intention in tended/patrolled non-garden locations, (b) consumers' taking or leaving intention in untended/unpatrolled non-garden locations, and (c) consumers' taking or leaving intention in tended/patrolled garden locations. Hypothesis 6 (H6). The importance that consumers dedicate to foraging as challenging local activity impact (a) consumers' taking or leaving intention in tended/patrolled non-garden locations, (b) consumers' taking or leaving intention in untended/unpatrolled non-garden locations, and (c) consumers' taking or leaving intention in tended/patrolled garden locations. 2.5. Survey Instrument and Sampling Approach The current study uses 34 items from a more extensive 109-item food foraging online survey. The 34 items cover socio-demographic information, attitudes toward nature, food, food foraging, and foraging intention. The data collection utilized Amazon Mechanical Turk (MTurk) in 2022. MTurk is a longstanding crowdsourcing platform used to collect social science data for the last decade . Respondents were screened to include those who were 18 years or older, reside in the U.S., and have some interest and experience with food foraging. A total of 417 responses were returned, and after the data were cleaned, 401 responses were suitable for the Partial Least Square Structural Equation Modeling (PLS-SEM). The ten-times rule was applied to confirm minimum sample size was achieved . The questionnaire items/scales were drawn from the literature. Questions related to going out to experience nature were adapted from Schunko and Brandner (2022) . Questions related to the importance of tending/harvesting nature and food at home were adapted from Fischer and Kowarik (2020) and Byrd and Widmar (2015) . Food foraging attitudes were developed by Sardeshpande and Shackleton (2020) and Schunko and Brandner (2022) . All these attitudinal questions used seven-point Likert-type agreement scales (1 = strongly disagree to 7 = strongly agree). Foraging intentions for a variety of locations were developed by the authors and used a 100-point scale anchored by 0 = leave everything to 100 = take everything. 2.6. Analysis A demographic sample description was generated using SPSS, and the PLS-SEM analysis was performed using SmartPLS in two stages. First the outer model was examined (measurement model assessment), then the inner model (structural model assessment). PLS-SEM is appropriate because it is suitable for the examination of complex theoretical models and can accommodate both multi-item and single measures, smaller samples, and relaxed distributional assumptions, especially when compared with covariance-based approaches to SEM . PLS-SEM first analyzes the outer model, or the relationships between questions and proposed scales (latent variables), then it tests the inner model identifying the significant relationships between latent variables. The outer model tests the factor loadings of questions to their respective scales. Loadings are recommended to be above 0.4 . Item/scale convergence is tested and considered acceptable when the average variance extracted (AVE) is greater than 0.5 . Scale reliability is measured using traditional Chronbach's alphas and the more recent composite reliability and is acceptable if greater than 0.6 . Discriminant validity is verified in two ways: using the traditional Fornell-Larcker criterion greater than the cross-loadings (Fornell and Larcker, 1981) and the more recent heterotrait-monotrait ratio of correlations criterion (HTMT) . HTMT values should be less than 0.9 and HTMT is a preferred method to test discriminant validity . Lastly, multicollinearity is examined via inner model variance inflation factor (VIF) scores and are considered satisfactory if less than 5 . The inner model examinations test the structural fit of the model and the model's explanatory power and predictive relevance. Reporting goodness of fit (GoF) and Normed Fit Indices (NFI) for PLS-SEM models are expected; however, despite higher scores being better, their interpretation is unclear as cautioned by Hair et al. (2022) . Smaller Standardized Root Mean Square Residual (SRMR) indicates a better fit, and the convention is that SRMR values are acceptable if under 0.08 and problematic if over 0.10 . Finally, the model's explanatory power (R2) is considered weak, moderate, or substantial if they are near 0.25, 0.50, and 0.75, respectively. Also, the model's predictive relevance (Stone-Geisser criterion Q2) are considered to have acceptable, medium, and strong predictive relevance if they are greater than 0, 0.25, and 0.50, respectively . Once the inner and outer model analysis criteria are satisfied, the proposed hypotheses are tested. The testing of hypotheses involves examining the direction and statistical significance of the coefficients representing each hypothesized relationship using the PLS-SEM bootstrapping procedures (5000 samples). In many research topics, there is sufficient evidence to hypothesize the positive or negative sign of relationships, but in the absence of such evidence, the hypotheses of the current study do not commit to a sign. To examine the invariance of the model across subsamples, hierarchical clusters (Ward's method) were computed based on the foraging intention questions across all the potential locations. The resultant clusters followed tendencies to harvest heavily, which were named "Takers." Those who tended to balance harvesting and not harvesting were named "balancers", and those who tended toward little or no harvesting were named "leavers." While no hypotheses were offered for these clusters, they represent a useful classification and indicate whether the hypotheses were supported across them. 3. Results and Discussion The overall sample description, sub-sample statistics, and relevent US census statistics are display in Table 1. In the overall sample, the percentage of men and women were 50.4% and 49.6%, respectively. Residents from the Southern (51.6%) and Northeastern (17.0%) regions were over-represented relative to U.S. Census data, and residents from the Midwest (16.0%) and Western (6.2%) region were under-represented. Respondents between 25 and 34 years old (51.1%) were the largest age group, and many of the age groups (25-34, 35-44, and 45-54) were over-represented relative to census statistics. Conversely, the young (18-24) and elderly (55-64 and 65+) were under-represented. Additionally, the respondents were better educated but had lower incomes than census statistics. In other U.S. food foraging studies, there is no consensus concerning the influence of socio-demographic background . Participating in food foraging does not seem to be explicitly tied to consumers with specific income levels, but culture and family traditions are important influences. Hence, there is diversity among urban foragers. Table 2 presents the results from the inner model analysis. Items sufficiently contributed to their respective scales with 0.4 or better factor loadings. Reliabilty criteria was satisfied with all scores above 0.6, and convergent validity was confirmed with all AVE scores above 0.5. Table 3 shows that discriminant validity was confirmed. Specifically, the Fornell-Larcker criterion was satisfied as the square root of the scale's AVE was greater than the cross-loadings. HTMT was also satisfied as the HTMT ratios were less than 0.90. Finally, multicollinearity was not an issue in the data set as demonstrated by the VIF values (max: 2.09 and average: 1.79). Thus, all the requirements for testing the measurement (outer) model have been satisfied and the model is deemed suitable for model structure testing. Model structure analyses indicate a goodness of fit of 0.426, a normed fit index of 0.701, and an SRMS of 0.068, indicating adequate model fit. The model has acceptable explanatory power and acceptable predictive relevance with average R2/Q2 values of 0.262/0.229. Figure 2 shows strong explained variance for two of the seven dependent variables as they were near 50% (R2:0.5), and two were near 25% (R2:0.25) indicating moderate explanatory power. Figure 2 and Table 4 display the result of the hypothesis testing. In general, there was strong support for the hypothesized relationships between the nature/food attitudes and food foraging attitudes but limited support for the influence of food foraging attitudes on taking/leaving intentions. These findings are well in line with previous studies. Nature attitudes and nature contact are closely associated with food-foraging attitudes . However, their translation into behavior cannot be confirmed by previous studies . Hypothesis 1 was not fully supported as the importance of going out to experience nature significantly influenced three of the four food foraging attitudes: goodness for society (H1a), knowledgeability of foragers (H1c), and challenges of foraging (H1d), but was not a driver of goodness to people and planet (H1b). These findings corroborate with Schunko and Brander (2022) and Sardeshpande and Shackleton (2020) who indicate that food foraging is still frowned upon. Social acceptance is hampered by incidences of unsustainable foraging practices with no concern for ecological systems and other societal obstacles towards food foraging , especially those that oppose what is seemingly good for people and the planet. Nature experiences, knowledge, and food foraging as means to counteract hardship and justice in food access have been highlighted by previous studies. Hypothesis 2 also did not receive full support as the importance of tending/harvesting nature and food at home only influenced three of the four food-foraging attitudes: foraging goodness for society (H2a), knowledgeability of foragers (H2c), and goodness for people and planet (H2b), but did not influence challenges of foraging. The importance of tending/harvesting food at home and in gardening is emphasized by Fischer and Kowarik (2020). However, associations with attitudes were not covered in their work . The non-significant finding related to the challenges that are associated with food foraging diverge from Fischer and Kowark and Schunko and Brandner (2022) There was no support for H3 or H4 as neither goodness for society nor knowledgeability of foragers influenced the taking/leaving intention for any of the foraging locations. Some support was found for H5 as good for people and the planet influenced intention towards more harvesting for two of the three locations: tended/patrolled non-garden (H5a) and tended/patrolled garden (H5c). H6 also found partial support as an increased challenge of foraging influenced intention towards more harvesting for both tended/patrolled (H6a) and untended/unpatrolled (H6b) non-garden settings. When examining the relationships across sub-groups, many of the hypothesized relationships found in the overall sample were also found in the sub-groups (Table 4 with green highlight). These relationships could be considered relatively consistent across the sub-groups. Some relationships were significant in the overall sample but not significant for the sub-samples (yellow highlight). For some, this could have been due to the smaller sample size of the sub-groups. The most dynamic were those that were significant in subsamples but were not in the overall sample (red highlight). For example, foraging goodness for people and the planet seemed to be a driver of intention to harvest in untended/unpatrolled non-gardens for takers but an inhibitor to harvesting for leavers. The reasoning for these behavioral differences is yet to be explored but may be explained by plant and ecological knowledge, knowledge of laws and regulations, as well respect for the common good and resources. 4. Conclusions The study aimed to explore the taking or leaving behavior of food foragers in tended and untended garden and non-garden settings. It was found that nature and food attitudes predict foraging attitudes relatively well. Foraging attitudes, such as food foraging is challenging and food foraging benefits people and the planet, are the most important drivers for taking or leaving behavior. The results of the present study are a valuable addition to the recent body of literature on urban food foraging and are of relevance to municipalities and consumers alike. The foraging attitude "Foraging is good for people and planet" as a predictor for taking and leaving behavior in tended/patrolled garden settings is relevant information for municipalities. Given that foragers are willing to expose themselves to a potential risk of punishment or even litigation in both patrolled settings suggests that municipalities must make permitted foraging spaces, laws, and regulations more transparent. In collaboration with the Natural Resources Conservation Service of the USDA, this can be achieved by improving individual state websites presenting maps with areas where foraging is permitted and not permitted to centralize information. The involvement of a governmental body would increase the trustworthiness and credibility of foraging information compared to the currently existing web pages. In addition, information related to species and soil conditions, for instance, the indication of soil toxicity or protected species, would be helpful to present through virtual reality and educational foraging videos. This would make the information more accessible and attractive to a larger audience interested in food foraging. For patrolled places, non-garden places, such as campuses, permitting food foraging in dedicated areas may be an opportunity for student-campus engagement and avoiding food losses. Hands-on foraging activities may be an interesting way to combine botany, plant science, plant identification, or culinary studies. Finally, the data procurement and sampling methods of the present need to be critically reflected upon as the data was obtained from MTurk, a crowdsourcing platform. MTurk samples are not comparable with representative samples of the U.S. population but are superior to convenience samples. However, given that there is so far no consensus on who the food foragers are and their socio-demographic background profiles in the U.S., a diverse sample, such as one stemming from a crowdsourcing platform, is in line with the recent body of literature. Future studies could use opt-in panel providers and quota sampling following the most recent census to obtain more representative information. Further studies could deepen the findings on differences between taking and leaving personalities or study food foraging from an eco-tourism and gastronomy perspective. The perspectives of stakeholders, such as chefs, restaurant owners, and foraging guides, remain largely unexplored. Cross-country comparison with European countries and Australia may be of value given the impacts of COVID-19 and food price inflation. Targeting low-income populations and investigating food foraging on the background of need is of particular interest in recent times. Acknowledgments The Authors acknowledge the discussion and support provided by the Lincoln University Centre of Excellence in Transformative Agribusiness. Author Contributions Conceptualization, M.R. and D.L.D.; methodology, D.L.D.; software, D.L.D.; validation, M.R. and D.L.D.; formal analysis, D.L.D.; investigation, M.R.; resources, M.R. and D.L.D.; data curation, D.L.D. writing--original draft preparation, M.R. and D.L.D.; writing--review and editing, M.R. and D.L.D. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Human Ethics Committee at Lincoln University, New Zealand, in 2022 (HEC2022-40). Informed Consent Statement All participants gave their informed consent for inclusion before they participated in this study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest in the context of this publication. Figure 1 Conceptual Model of Food Foraging Behavior (Taking/Leaving). Figure 2 Conceptual Model Results. foods-12-01032-t001_Table 1 Table 1 Sample Description. Sample or Sub-Sample Overall Balancers Takers Leavers U.S. Census Frequency or Percentage Freq % Freq % Freq % Freq % % Age (StDev: 0.940) 18-24 32 8.0 3 2.8 19 10.3 10 9.1 12.0 25-34 205 51.1 55 51.9 95 51.4 55 50.0 18.0 35-44 70 17.5 24 22.6 31 16.8 15 13.6 16.3 45-54 68 17.0 20 18.9 28 15.1 20 18.2 16.4 55-64 25 6.2 3 2.8 12 6.5 10 9.1 16.7 65+ 1 0.2 1 0.9 0 0.0 0 0.0 20.7 Total 401 100 106 100 185 100 110 100 100 Education (StDev: 0.927) Did not finish high school 3 0.7 2 1.9 0 0.0 1 0.9 11.0 Finished high school 28 7.0 9 8.5 10 5.4 9 8.2 27.0 Attended university 35 8.7 10 9.4 8 4.3 17 15.5 20.0 Bachelor's degree 247 61.6 64 60.4 115 62.2 68 61.8 29.0 Postgraduate degree 88 21.9 21 19.8 52 28.1 15 13.6 13.0 Total 401 100 106 100 185 100 110 100 100 Household Annual Income (StDev: 1.141) $0 to $24,999 23 5.7 7 6.6 9 4.9 7 6.4 18.0 $25,000 to $49,999 98 24.4 41 38.7 32 17.3 25 22.7 20.0 $50,000 to $74,999 165 41.1 33 31.1 79 42.7 53 48.2 18.0 $75,000 to $99,999 94 23.4 20 18.9 54 29.2 20 18.2 13.0 $100,000 or higher 21 5.2 5 4.7 11 5.9 5 4.5 31.0 Total 401 100 106 100 185 100 110 100 100 Gender (StDev: 0.501) Male 202 50.4 52 49.1 103 55.7 47 42.7 49.0 Female 199 49.6 54 50.9 82 44.3 63 57.3 51.0 Total 401 100 106 100 185 100 110 100 100 Region Northeast 105 26.2 23 21.7 53 28.6 29 26.4 17.0 South 207 51.6 58 54.7 91 49.2 58 52.7 38.0 Midwest 64 16.0 19 17.9 30 16.2 15 13.6 21.0 West 25 6.2 6 5.7 11 5.9 8 7.3 24.0 Total 401 100 106 100 185 100 110 100 100 foods-12-01032-t002_Table 2 Table 2 Scale Loadings, Reliabilities, and Convergent Validity for Multi-Item Scales. Scales and Items Takers Balancers Leavers Overall Mean St Dev Mean St Dev Mean St Dev Mean St Dev Loading CRA CR AVE Importance of Going Out to Experience Nature 0.753 0.859 0.670 How important is going hunting/fishing to obtain food 5.751 1.178 5.198 1.185 5.036 1.334 5.409 1.266 0.838 How important is collecting flowers, stones, or shells 5.914 1.140 5.481 1.057 5.227 1.412 5.611 1.237 0.809 How important is going surfing, boating, or sailing 5.703 1.136 5.292 1.149 5.282 1.484 5.479 1.261 0.808 Importance of Tending/Harvesting Nature and Food at Home 0.758 0.838 0.510 How important is growing food and flowers in my own garden 5.903 0.913 5.575 1.081 5.491 1.249 5.703 1.075 0.741 How important is keeping plants in my living and work environment 5.930 0.970 5.547 0.943 5.655 1.179 5.753 1.039 0.752 How important is cooking and food preparation 5.973 0.967 5.840 1.020 5.809 0.958 5.893 0.982 0.616 How important are food processing and preserving 5.843 1.159 5.566 1.073 5.555 1.203 5.691 1.158 0.741 How important is keeping livestock to obtain food 5.870 1.223 5.453 1.318 5.191 1.462 5.574 1.349 0.710 Foraging is Good for Society's Wellbeing 0.774 0.855 0.597 Food foraging contributes to social well-being and the development of society 5.870 0.897 5.538 0.953 5.564 1.049 5.698 0.969 0.759 Food foraging contributes to solidarity 5.865 0.911 5.302 0.953 5.582 1.073 5.638 0.997 0.727 Food foraging contributes to distributive justice 5.741 1.023 5.330 1.114 5.455 1.233 5.554 1.122 0.755 Food foraging is the embodiment of democracy 5.886 0.994 5.613 0.977 5.400 1.356 5.681 1.120 0.844 Local Foragers are Knowledgeable 0.703 0.835 0.628 Where I live, collectors know where to find edible plants 5.838 0.967 5.453 1.047 5.473 1.085 5.636 1.039 0.807 Where I live, residents appreciate the collection of edible plants 5.800 0.957 5.349 0.962 5.455 1.084 5.586 1.015 0.791 Where I live, collectors are careful when collecting edible plants 5.897 1.011 5.613 0.896 5.545 1.101 5.726 1.021 0.779 Foraging is Good for People and the Planet 0.641 0.805 0.580 Food foraging combines personal interests and the common good in our society 5.914 0.884 5.623 0.758 5.500 0.951 5.723 0.891 0.781 Food foraging is ethical 5.935 1.022 5.557 0.942 5.873 0.945 5.818 0.993 0.715 Food foraging is sustainable 5.962 0.903 5.623 0.995 5.745 1.004 5.813 0.967 0.787 Local Foraging is Challenging 0.664 0.813 0.593 Where I live, there are few easily accessible green spaces to collect edible plants. 5.941 0.931 5.396 1.113 5.036 1.272 5.549 1.149 0.798 Where I live, the authorities responsible for public greenspaces do not encourage collecting edible plants 5.578 1.123 5.321 1.314 5.155 1.396 5.394 1.267 0.693 Where I live, most green spaces are too contaminated or polluted to collect edible plants 5.827 1.168 5.226 1.238 5.082 1.508 5.464 1.332 0.813 Take/Leave Tended Patrolled Non-Garden (Cemetery/Campus) 0.799 0.908 0.831 Take all (100) vs. leave all (0) at a cemetery 82.18 14.38 64.72 15.87 42.21 26.06 66.60 24.99 0.893 Take all (100) vs. leave all (0) at a school, institute, or other public grounds 85.05 10.48 66.46 15.92 46.96 23.09 69.69 22.74 0.931 Take/Leave Untended Unpatrolled Non-garden (Abandoned/Roadside/Railroad) 0.910 0.936 0.787 Take all (100) vs. leave all (0) at a former farm or orchard 82.00 11.18 63.49 14.29 43.04 18.62 66.42 21.70 0.825 Take all (100) vs. leave all (0) at an abandoned, foreclosed property 84.50 10.30 58.00 16.71 38.05 21.38 64.75 25.21 0.893 Take all (100) vs. leave all (0) at a parking lot, empty lot, roadside 84.08 9.24 66.75 14.37 32.52 18.24 65.35 25.36 0.907 Take all (100) vs. leave all (0) under freeways or on railroad land 83.41 10.68 59.92 14.68 34.42 19.02 63.76 25.04 0.920 Take/Leave Tended Patrolled Garden (Botanic/Community) 0.821 0.917 0.848 Take all (100) vs. leave all (0) at a park or botanical garden 81.48 12.58 60.49 17.59 47.98 23.77 66.74 22.74 0.909 Take all (100) vs. leave all (0) at a community garden 83.10 10.85 60.75 15.53 49.41 21.01 67.95 21.29 0.932 Note: St Dev = Standard Deviation, CRA = Chronbach's Alpha, CR = Composite Reliability, AVE = Average Variance Extracted. foods-12-01032-t003_Table 3 Table 3 Scale Discriminant Validity. Fornell-Larcker Criterion A B C D E F G H I (A) Foraging is good for people and the planet 0.762 (B) Foraging is good for society's wellbeing 0.568 0.773 (C) Importance of going out to experience nature 0.335 0.568 0.818 (D) Importance of tending/harvesting nature and food at home 0.558 0.657 0.681 0.714 (E) Local foragers are knowledgeable 0.532 0.645 0.607 0.614 0.792 (F) Local foraging is challenging 0.323 0.483 0.587 0.420 0.446 0.770 (G) Take/leave tended patrolled non-garden 0.212 0.123 0.087 0.135 0.133 0.211 0.912 (H) Take/leave tended patrolled garden 0.209 0.135 0.103 0.192 0.137 0.125 0.720 0.921 (I) Take/leave untended, unpatrolled non-garden 0.181 0.221 0.308 0.238 0.246 0.378 0.757 0.687 0.887 Heterotrait-Monotrait Ratio A B C D E F G H I (b) Foraging is good for society's wellbeing 0.800 (C) Importance of going out to experience nature 0.472 0.741 (D) Importance of tending/harvesting nature and food at home 0.806 0.851 0.889 (E) Local foragers are knowledgeable 0.788 0.873 0.831 0.834 (F) Local foraging is challenging 0.473 0.673 0.818 0.570 0.639 (G) Take/leave tended patrolled non-garden 0.287 0.149 0.115 0.175 0.174 0.265 (H) Take/leave tended patrolled garden 0.279 0.168 0.126 0.244 0.176 0.148 0.886 (I) Take/leave untended, unpatrolled non-garden 0.226 0.260 0.368 0.282 0.307 0.458 0.878 0.804 Note: Fornell-Larker criterion units--diagonal: square root of average variance extracted for scale, Others: Correlations between scales. Heterotrait-monotrait ratio units--ratio of correlations between scales. foods-12-01032-t004_Table 4 Table 4 Path Coefficients for Overall Sample and Sub-samples. Sample or Sub-Sample Overall Balancers Takers Leavers Path Coefficient, T Statistic, p Value Coef T Stat p Val Coef T Stat p Val Coef T Stat p Val Coef Tstat p Val Hypothesized Relationship H1a: Importance of going out to experience nature - foraging is good for society's wellbeing 0.225 2.702 0.007 0.414 3.951 0.000 0.142 1.283 0.199 0.170 0.956 0.339 H1c: Importance of going out to experience nature - local foragers are knowledgeable 0.352 5.034 0.000 0.208 1.775 0.076 0.373 3.328 0.001 0.426 3.285 0.001 H1b: Importance of going out to experience nature - foraging is good for people and planet -0.084 1.132 0.258 -0.115 0.986 0.324 0.026 0.206 0.837 -0.296 2.071 0.038 H1d: Importance of going out to experience nature - local foraging is challenging 0.561 8.369 0.000 0.488 4.221 0.000 0.627 6.190 0.000 0.514 3.509 0.000 H2a: Importance of tending/harvesting nature and food at home - foraging is good for society's wellbeing 0.504 6.164 0.000 0.320 3.039 0.002 0.681 8.439 0.000 0.446 2.373 0.018 H2c: Importance of tending/harvesting nature and food at home - local foragers are knowledgeable 0.374 5.054 0.000 0.477 4.373 0.000 0.418 3.876 0.000 0.244 1.646 0.100 H2b: Importance of tending/harvesting nature and food at home - foraging is good for people and the planet 0.615 9.070 0.000 0.552 5.092 0.000 0.613 5.557 0.000 0.722 5.560 0.000 H2d: Importance of tending/harvesting nature and food at home - local foraging is challenging 0.038 0.436 0.663 0.172 1.010 0.312 0.153 1.294 0.196 -0.214 1.309 0.191 H3a: Foraging is good for society's wellbeing - take/leave tended patrolled non-garden -0.075 0.852 0.394 0.102 0.518 0.604 0.019 0.147 0.883 -0.201 1.256 0.209 H3b: Foraging is good for society's well-being - take/leave untended unpatrolled non-garden -0.019 0.227 0.821 0.133 0.607 0.544 0.030 0.248 0.804 0.009 0.067 0.947 H3c: Foraging is good for society's well-being - take/leave tended patrolled garden -0.014 0.157 0.876 -0.014 0.070 0.944 -0.042 0.402 0.688 -0.056 0.312 0.755 H5a: Local foragers are knowledgeable - take/leave tended patrolled non-garden -0.008 0.101 0.919 -0.110 0.783 0.433 0.077 0.537 0.592 -0.246 1.576 0.115 H5b: Local foragers are knowledgeable - take/leave untended unpatrolled non-garden 0.089 1.065 0.287 -0.275 1.181 0.238 0.016 0.113 0.910 0.198 1.762 0.078 H5c: Local foragers are knowledgeable - take/leave tended patrolled garden 0.018 0.194 0.846 -0.044 0.215 0.830 -0.038 0.352 0.725 -0.103 0.401 0.689 H4a: Foraging is good for people and planet - take/leave tended patrolled non-garden 0.199 2.692 0.007 0.336 2.267 0.023 0.305 2.579 0.010 0.239 1.816 0.069 H4b: Foraging is good for people, and planet - take/leave untended unpatrolled non-garden 0.036 0.504 0.614 0.352 1.374 0.170 0.384 2.991 0.003 -0.298 2.636 0.008 H4c: Foraging is good for people and planet - take/leave tended patrolled garden 0.187 2.619 0.009 -0.079 0.463 0.643 0.464 4.801 0.000 0.192 1.578 0.115 H6a: Local foraging is challenging - take/leave tended patrolled non-garden 0.187 2.240 0.025 -0.315 2.203 0.028 -0.048 0.399 0.690 -0.032 0.189 0.850 H6b: Local foraging is challenging - take/leave untended unpatrolled non-garden 0.335 5.093 0.000 -0.050 0.209 0.834 -0.064 0.474 0.636 0.321 3.052 0.002 H6c: Local foraging is challenging - take/leave tended patrolled garden 0.063 0.789 0.430 -0.118 0.505 0.614 -0.097 0.857 0.391 -0.319 2.120 0.034 Bold = p < 0.05, green = significant overall and in sub-group, yellow = significant overall but not in sub-group, red = not significant overall but significant in sub-group. 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PMC10000462 | Non-small cell lung cancer (NSCLC) is still one of the leading causes of death worldwide. This is mostly because the majority of lung cancers are discovered in advanced stages. In the era of conventional chemotherapy, the prognosis of advanced NSCLC was grim. Important results have been reported in thoracic oncology since the discovery of new molecular alterations and of the role of the immune system. The advent of new therapies has radically changed the approach to lung cancer for a subset of patients with advanced NSCLC, and the concept of incurable disease is still changing. In this setting, surgery seems to have developed a role of rescue therapy for some patients. In precision surgery, the decision to perform surgical procedures is tailored to the individual patient; taking into consideration not only clinical stage, but also clinical and molecular features. Multimodality treatments incorporating surgery, immune checkpoint inhibitors, or targeted agents are feasible in high volume centers with good results in terms of pathologic response and patient morbidity. Thanks to a better understanding of tumor biology, precision thoracic surgery will facilitate optimal and individualized patient selection and treatment, with the goal of improving the outcomes of patients affected by NSCLC. NSCLC immunotherapy targeted therapy precision surgery This research received no external funding. pmc1. Introduction Lung cancer still represents one of the most common causes of cancer related death worldwide despite significant advances in research . About 80-85% of lung cancers are represented by non-small cell lung cancer (NSCLC) . NSCLC is a heterogeneous disease and the two main histologic subtypes are represented by adenocarcinoma and squamous cell carcinoma. However, many other NSCLC subtypes exist (e.g., pleomorphic carcinoma, mucoepidermoid carcinoma, sarcomatoid carcinoma). Indeed, the most recent WHO classifications are gaining increasing complexity, and have now included immunohistochemistry and molecular testing, together with morphological analysis, in the NSCLC definition. This has allowed a more precise differentiation of the histologic subtypes of lung cancer, thus leading to improved therapeutic strategies . Surgery is the mainstay of therapy for early-stage NSCLC, leading to cure in the majority of patients. However, despite the recent introduction of lung cancer screening, the majority of tumors are diagnosed at advanced stages, where treatment options are limited. In the era of conventional cytotoxic drugs, the prognosis for this cancer was grim. The discovery of the central role of the immune system and the development of new molecular alterations have radically changed the approach to lung cancers. Recent research in the tumor biology of lung adenocarcinoma and squamous cell carcinoma has shown significant differences in the tumor immune microenvironment . Moreover, in recent years, since the discovery of tumor cells' ability to release macromolecules into the bloodstream, the role of liquid biopsy has gained increasing importance. Indeed, in selected cases, liquid biopsy has replaced tissue sampling when suspecting the onset of resistance to new targeted drugs . With the introduction of new drugs, such as immune checkpoint inhibitors (ICIs) and targeted therapies, the prognosis of some advanced NSCLCs have changed. Moreover, a new age of precision oncology medicine has begun as a result of the development of new diagnostic technology and bioinformatics tools that have added to our understanding of cancer biology. This is based on the idea that each tumor is unique and can be precisely targeted by one of the many targeted drugs reportedly available . In fact, the recommendation of particular therapeutic modalities considers the genetic and environmental influences on therapeutic response . The term "precision medicine" was introduced because diagnostic, prognostic, and therapeutic approaches are meticulously tailored to each patient's needs. These novelties have radically changed the world of surgical oncology and, similar to precision medicine, the new concept of precision surgery is proposed. It was firstly introduced in general surgery, especially related to the different prognoses of colorectal cancer related to different genetic mutations. Nowadays, this concept is growing in thoracic oncology, too, especially with the discovery of the crucial role of molecular alterations in NSCLC. We herein describe the most important molecular alterations and the different clinical trials of targeted therapies for NSCLC, highlighting their implications in thoracic surgery, and we introduce the new concept of precision surgery in lung cancer. 2. Molecular Alterations and TKIs Trials 2.1. Epidermal Growth Factor Receptor-TKIs Trials Nowadays, the ideal management of NSCLC tumors requires the analysis of a series of biomarkers that may aid in determining target therapy sensitivity. Most research on lung adenocarcinoma during the past ten years has concentrated on mutations of the epidermal growth factor receptor (EGFR). EGFR is a member of a family of receptor tyrosine kinases that can set off several signaling cascades that promote cell growth and proliferation. About 20% of patients with lung adenocarcinoma have EGFR mutations, such as exon 19 deletions and exon 21 (L858R) point mutations. Gefitinib and erlotinib are reversible competitive inhibitors of ATP for the tyrosine kinase domain of EGFR and they represent the first generation of EGFR TKIs. On the contrary, the second generation drug afatinib irreversibly inhibits human epidermal growth factor receptor (EGFR) kinases and has more targets than the first generation . Different clinical trials have demonstrated the great advantages of these molecules over standard chemotherapy for advanced NSCLC. In the OPTIMAL, CTONG-0802 trial, patients with histologically confirmed stage IIIB or stage IV NSCLC (according to the 6th edition of TNM) and an activating mutation of EGFR (exon 19 deletion or exon 21 L858R point mutation) were randomly assigned to receive oral erlotinib or up to four cycles of gemcitabine plus carboplatin. Erlotinib patients had considerably longer median progression-free survival (PFS) than chemotherapy patients (13.1 vs. 4.6 months), and chemotherapy was linked to more grade 3 or 4 adverse effects than erlotinib . According to the trials LUX-lung 3 and LUX-Lung 6, afatinib outperformed traditional chemotherapy in stage IIIB or IV (7th edition of TNM) lung cancer adenocarcinoma with del19 EGFR mutation (pemetrexed-cisplatin in LUX-Lung 3 and gemcitabine-cisplatin in LUX-Lung 6, respectively). However, despite much longer PFS in LUX-Lung 3 and LUX-Lung 6, there was no difference in overall survival (OS) . After these studies, both second-generation TKIs were approved for first-line treatment of EGFR mutation-positive advanced non-small-cell lung cancer. Subsequently, patients with stage IIIB or stage IV NSCLC and a common EGFR mutation were enrolled in LUX-Lung 7, which compared the effectiveness and safety of afatinib and gefitinib (in exon 19 deletion or Leu858Arg). The results of this trial showed that afatinib significantly improved outcomes with a manageable tolerability profile in patients with EGFR-mutated NSCLC who had not previously received treatment as compared to gefitinib . Unfortunately, after 10 years of treatment with second-generation EGFR-TKIs, drug resistance developed in the majority of patients, primarily as a result of the exon T790 M mutation (exon 20). Subsequently, osimertinib, a third generation EGFR-TKI, was released. Osimertinib is an irreversible tyrosine kinase inhibitor that inhibits T790M mutations. The AURA series trial examines the effectiveness and security of osimertinib. The phase 3 AURA3 study demonstrated significantly enhanced efficacy of osimertinib in comparison to platinum pemetrexed regimen in NSCLC patients who had gained the T790M resistance mutation after treatment with first generation TKI. The results showed that osimertinib had a considerably greater objective response rate (ORR) than combination chemotherapy (71% vs. 31%; odds ratio for objective response, 5.39; 95% CI, 3.47 to 8.48, p < 0.001) and a longer PFS (10.1 months vs. 4.4 months; hazard ratio (HR) = 0.3, 0.23 to 0.41, p < 0.001). Notably, osimertinib has an intracranial ORR of 70% . On the view of these results, osimertinib was approved as a second-line treatment for advanced lung cancer with the EGFR T790M mutation. In the FLAURA trial, standard first-generation EGFR-TKIs were compared to first-line treatment with osimertinib. Osimertinib was well tolerated and significantly increased PFS (18.9 vs. 10.2 months; HR 0.46). Therefore, osimertinib was approved by the FDA in 2018 as the first-line treatment for patients with metastatic NSCLC who have either an EGFR exon 19 deletion or an exon 21 L858R mutation . All these studies evaluated the role of EGFR-TKIs as the definitive treatment in advanced EGFR-mutated NSCLC. The ADAURA trial evaluated the efficacy of osimertinib in an adjuvant context . This study assessed the efficacy of osimertinib in comparison to standard chemotherapy in patients with resected stage IB-IIIA NSCLC (according to the eighth edition of TNM) and a verified EGFR-activating mutation (exon 19 deletion or exon 21 L858R). Finally, 90% of patients with stage II-IIIA of the osimertinib group were still alive and disease-free at 2 years, as opposed to 44% of patients in the placebo group. The authors concluded that patients with stage IB-IIIA EGFR-mutated NSCLC who received osimertinib had a significantly better disease-free survival (DFS) compared to placebo. 2.2. ALK Translocation and ALK-TKIs Trials The anaplastic lymphoma kinase (ALK) gene was first identified in 1994, when it was found to be fused to nucleophosmin in a subtype of non-Hodgkin lymphoma . The identical ALK gene was discovered in NSCLC a few years later by Soda et al., and this time it was joined to Echinoderm Microtubule-Associated Protein-Like Protein 4 (EML4) . About 3-7% of NSCLC patients have ALK gene rearrangements, frequently discovered without EGFR or KRAS mutations. The FDA has approved the use of three ALK tyrosine kinase inhibitors (TKIs), including crizotinib, ceritinib, alectinib, and brigatinib, for the treatment of NSCLC with an ALK rearrangement. Crizotinib was the first ALK inhibitor to be approved by the FDA. In the Profile 1014 study, crizotinib and chemotherapy were compared as first-line treatments for patients with advanced non-squamous NSCLC with ALK-gene mutation. With crizotinib, progression-free survival was considerably longer than with chemotherapy (median 10.9 months vs. 7.0 months). Unfortunately, after a few months of treatment, acquired resistance to crizotinib will develop. Therefore, second-generation (ceritinib, alectinib, and brigatinib) and third-generation (lorlatinib) ALK inhibitors were introduced. In particular, alectinib has been demonstrated to have a high rate of intracranial efficacy in treating brain metastases. In the phase 3 randomized, open-label ALEX trial, 303 patients with advanced, untreated ALK-positive NSCLC were randomly assigned to receive either alectinib or crizotinib. Alectinib considerably outperformed crizotinib in terms of progression-free survival (12-month event-free survival rate; 68.4% vs. 48.7%). Central nervous system (CNS) progression was one of the secondary endpoints that was significantly lower in the alectinib group . Brigatinib, a second-generation ALK inhibitor, outperformed crizotinib in the ALTA-1 study for PFS and health-related quality of life (QoL) in advanced ALK drug-naive ALK-positive non-small cell lung cancer. As a result of this study, brigatinib was approved as the initial therapy for individuals with advanced ALK-positive NSCLC . First-line lorlatinib was evaluated against crizotinib in a phase 3 randomized trial named CROWN. An objective response was observed in 76% of patients in the lorlatinib group and 58% of those in the crizotinib group. However crizotinib was associated with fewer grade 3 or 4 adverse events . 2.3. EGFR/ALK-TKIs as Neoadjuvant Treatment for NSCLC Following the great results of EGFR and ALK-TKIs in advanced NSCLC in terms of the increase in DFS and OS, different clinical trials are being conducted for these drugs in the neoadjuvant settings. Similarly to the adjuvant protocols, neoadjuvant TKIs may work by removing residual tumor cells or micrometastases created by primary tumor cells (with comparable genotypes and molecules), inducing greater clinical responses. The surgical results of these trials are crucial because they could provide information into the viability and safety of lung resection following these new treatments. Neoadjuvant administration of EGFR and ALK-TKIs in early NSCLC currently has little experience. There are no published phase 3 randomized studies and the majority of the evidence comes from short case series. Neoadjuvant gefitinib was used in six patients with locally advanced lung adenocarcinoma, in a retrospective report by Zang et al. The authors determined that surgery was possible, but no information on pathological response, OS or PFS was provided . Patients with stage IIIA-N2 disease were enrolled in the EMERGING-CTONG 1103 trial, where Zhong et al. compared targeted therapy to conventional neoadjuvant therapy (seventh edition of TNM) and an EGFR mutation. A total of 71 patients were recruited, of whom 37 were randomly assigned to receive erlotinib and 34 received cisplatin plus gemcitabine. Erlotinib-treated patients had a considerably prolonged PFS (21.5 months vs. 11.4 months in the chemotherapy group) . The NeoADAURA trial (NCT04351555) is still ongoing. In this trial, neoadjuvant osimertinib as a monotherapy or in combination with chemotherapy is tested on patients with resectable EGFR-mutated NSCLC . Ning showed that some patients with EGFR-positive advanced NSCLC were eligible for surgery following gefitinib therapy: progression-free survival was 14 months, and overall survival might reach 36 months . In another trial (NCT01217619), the role of neoadjuvant erlotinib in patients with stage IIIA-N2 (according to the seventh edition of TNM) EGFR-mutated NSCLC was analyzed. The study enrolled a total of 19 patients, 14 of which underwent surgery. Pathological downstaging occurred in 21% of cases with a 68% incidence of radical resection . ALK-positive NSCLC often has a worse clinical prognosis than EGFR-mutant NSCLC; in fact, it seems to be more aggressive and resistant to traditional antineoplastic drugs. Targeted therapy in the neoadjuvant and adjuvant settings is being studied in trials with resectable NSCLC that has an ALK mutation (ALCHEMIST, NCT02201992; ALNEO, NCT05015010). Zhang et al. reported 11 patients with locally advanced NSCLC treated with neoadjuvant crizotinib. A full resection was possible since all 11 patients demonstrated a favorable response to induction therapy. Moreover, all patients showed good tolerance to neoadjuvant crizotinib . For the moment, only case reports are available concerning the use of alectinib and the other second-generation ALK-TKIs in the neoadjuvant setting . 3. The PD-1/PD-L1 Pathway and Its Clinical Implications Immunotherapy radically changed treatment options in the oncology world. The immune system works by maintaining a delicate balance between immunological checkpoint-mediated suppression (CTLA-4) and costimulatory mediators (CD28) of T cell activation. Programmed cell death 1 (PD-1) was discovered to be another inhibitory receptor, redefining the significance of immunological checkpoints in ensuring the preservation of T cell tolerance. The discovery that PD-L1 overexpression on a mouse mastocytoma cell line inhibits CD8+ T cell cytolytic function by ligating PD-1, supported the theory that activation of the PD-1/PD-L1 pathway can decrease immune responses for malignancies, allowing increased tumor growth and invasiveness. Through antiapoptotic PD-L1-mediated signals, the PD-1/PD-L1 pathway promotes the survival of cancer cells in the tumor microenvironment . Therapies targeting the immunological checkpoints programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) have been approved for the treatment of a variety of tumor types, including NSCLC. Different drugs are now feasible, on the basis of the type of inhibitor activity. Although PD-L1 expression in tumors has been used to predict treatment response, the method's sensitivity and specificity are very moderate. This is due to the fact that PD-L1 alone cannot fully reflect the heterogeneity of the tumor microenvironment that is involved in the response to immunotherapy. Patients with at least 50% PD-L1 expression, in the Keynote-024 research were randomized to either platinum-based chemotherapy or pembrolizumab, an anti-PD1 medication. In the pembrolizumab group, the median progression-free survival was 10.3 months compared to 6.0 months in the chemotherapy group. Moreover, compared to platinum-based chemotherapy, pembrolizumab was linked to a considerably longer progression-free and overall survival as well as fewer adverse events . The extraordinary findings of the double-blind, placebo-controlled PACIFIC trial demonstrated that durvalumab (an anti-PD-L1) significantly improved PFS and OS in this heterogenous patient population while maintaining favorable safety profiles . This trial represents the birth of the world of the new therapies applied in clinical practice. In the OAK trial, atezolizumab and docetaxel were compared for effectiveness and safety in NSCLC patients with squamous and non-squamous cell histologies . Patients were randomized to receive either atezolizumab or docetaxel every three weeks regardless of PD-L1 expression. In the atezolizumab arm, the median OS was longer (13.8 months vs. 9.6 months), and the effect persisted independently from PD-L1 expression. The patients with the highest levels of PD-L1 expression had the largest OS improvement (20.5 months vs. 8.9 months). Pembrolizumab, an anti-PD-1 drug, is currently authorized for use as second-line therapy in patients with advanced NSCLC whose tumors exhibit PD-L1 expression according to immunohistochemical testing. Atezolizumab (anti-PD-L1) and nivolumab (anti-PD-1) are recommended as second-line therapies independently from PD-L1 expression. . Patients with unresectable stage III NSCLC, whose disease has not progressed despite concomitant platinum-based chemoradiotherapy, are eligible to receive durvalumab (anti-PD-L1) as a maintenance therapy. In the adjuvant setting, Impower010 is the first phase 3 study to demonstrate DFS improvement with adjuvant atezolizumab in completely resected stage IB to IIIA NSCLC (seventh edition of TNM) after platinum-based chemotherapy . This trial was approved by EMA and showed significant DFS benefit in patients in stage II-IIIA whose tumors expressed PD-L1 on 1% or more. Particularly, those with PD-L1 > 50% appeared to gain the most benefit. In patients with totally resected stage IB, stage II, and stage IIIA (seventh edition of TNM), the phase 3 PEARLS/KEYNOTE-091 trial showed DFS improvement with pembrolizumab compared with placebo, followed by adjuvant chemotherapy as recommended by guidelines . Neoadjuvant Immunotherapy or Chemo-Immunotherapy Immune checkpoint inhibitors have been studied as a monotherapy or together with chemotherapy in the neoadjuvant setting. The existence of a macroscopic tumor can offer a greater variety of tumor neoantigens able to activate the immune system in the neoadjuvant scenario, encouraging the earlier elimination of micrometastases. Neoadjuvant chemotherapy results in an increase in PD-L1 positive tumor cells and immune infiltrates, which would support the potential synergy with immunotherapy. This concept justifies the use of combination therapy. Chaft et al., firstly reported their surgical experience in patients with NSCLC previously treated with T cell checkpoint inhibitors . A total of five patients deemed to be unresectable at diagnosis received ICIs treatment. In three patients, chest and PET-CT scans showed a local persistence of disease in the lung and mediastinal lymph nodes. For this reason, they were considered for surgery with debulking intent. The final pathological exam showed a significant response rate on the specimens, demonstrating a discrepancy between the radiologic and pathologic evaluation. The other two patients were oligometastatic because of an isolated adrenal gland and CNS metastasis, respectively. The CNS metastasis was firstly irradiated, then treated with ICIs and, finally, the patient underwent right lower lobectomy with major pathological response (pT1bN0). The other patient was firstly treated with ICIs, then surgically resected both on the adrenal gland (with a laparoscopy approach) and on the lung via a wedge resection (with robotic assisted VATS). The final pathological exams showed a complete pathological response (pT0N0M0) after treatment with ICIs. Two years later, Bott et al. conducted a phase 1 trial of neoadjuvant nivolumab in patients with resectable non-small cell lung cancer (NSCLC). They analyzed perioperative outcomes to assess the safety of this approach . The study finally included 20 patients. They reported no delays to surgery and described a high conversion rate (54%) from a minimally invasive approach (VATS or RATS) to thoracotomy mainly due to hilar inflammation and fibrosis. However, they concluded that surgery after treatment with nivolumab was not associated with unexpected perioperative morbidity or mortality. The NADIM trial analyzed the safety, efficacy and feasibility of immunotherapy (nivolumab) combined with neoadjuvant chemotherapy (paclitaxel plus carboplatin) in patients with locally advanced resectable stage IIIA NSCLC (according to the seventh edition of TNM), followed by adjuvant treatment for 1 year with nivolumab. This study included a total of 46 patients and evaluated PFS at 24 months as the primary goal, while the secondary endpoints consisted of evaluating the toxicity profile of the drugs' combination, the downstaging rate, and the complete resection rate. The PFS was 77.1%, major pathological response (MPR) was 83%, the pathological complete response (pCR) was 63%, and the 1-year OS rate was 97.8%. Treatment-related adverse events during the neoadjuvant treatment occurred in 43 patients (93%), and grade 3 or worse events were found in 14 patients (30%); however, none of these caused surgery delays or deaths . Apart from these objectives, one of the main goals of these studies is to evaluate the safety and feasibility of surgery after this type of treatment. CheckMate-816 is the first phase 3 study to show a benefit of the neoadjuvant immunotherapy plus chemotherapy combination for resectable NSCLC over standard chemotherapy. Neoadjuvant nivolumab plus chemotherapy resulted in a lower rate of pneumonectomies and showed pCR in 24% of patients compared with 2.2% in patients treated with chemotherapy alone . Immunotherapy and chemoimmunotherapy, as expected, caused notable alterations in the tumor microenvironment associated with enhanced pathologic responses and survival. A neoadjuvant treatment for resectable non-small-cell lung cancer using atezolizumab and carboplatin was demonstrated by Shu et al. in an open-label, multicenter, single-arm, phase 2 trial. They noted that a significant number of patients experienced a large pathological response and that any treatment-related toxicities were tolerable and did not impair surgical resection . The main neoadjuvant and adjuvant trials with immunotherapy and/or targeted therapy are shown in Table 1 and Table 2. 4. Precision Surgery and Its Application to Thoracic Oncology 4.1. The Concept of Precision Surgery As a direct result of precision medicine, the idea of precision surgery has been introduced in surgical oncology. Precision medicine is a new method for treating and preventing diseases that considers a person's different genetic makeup, environmental factors, and lifestyle with the final aim of therapy tailored to each individual. With the discovery of targetable molecular alterations and with the concept that cancer is composed of populations of cells with distinct molecular and phenotypic features, this concept has also involved modern oncology and oncological surgery. This branch of surgery is more sophisticated than a mastery of technical maneuvers and involves a deeper understanding of the underlying biological foundation of disease with the final purpose of a targeted, strategic intervention. The first reference to precision surgery dates back to 1996, made by Dr. Blake Cady, who summarizes the concept well, stating that the art of surgical oncology is to apply basic principles flexibly to the individual patient . In general, as reported by Lidsky et al., precision surgery aims to apply surgical therapy to those most likely to benefit, and to avoid surgery in those doomed to fail . An example is the work by Passiglia and colleagues that reported, in a meta-analysis, how KRAS and BRAF mutations predict worse recurrence-free and overall survival in patients undergoing resection of colorectal liver metastasis . In order to identify the patients most likely to benefit from surgical treatment, precision surgery suggests considering the KRAS and BRAF mutational status not only as part of the molecular disease characteristics, but mostly in the context of the clinico-pathological disease features. Concerning the application of precision surgery to thoracic oncology, there are no scientific data or articles reported. Prior to the advent of new molecular therapies, the treatment of NSCLC was well established on the basis of the clinical and/or pathological TNM staging. The advent of effective, targeted therapies for molecularly defined subsets of patients with NSCLC has prompted the need for more extensive genomic characterization, and thoracic oncology and surgery entered an era of therapy co-directed by histology, genotyping, and immunotyping. Recent advancements in the treatment of NSCLC have given patients access to individualized medicines and significant, frequently long-lasting, therapeutic outcomes. As shown before, the definition of the role of surgery in the context of ICIs or targeted therapies is still to be defined, as large-population trials regarding the application of the new therapies as adjuvant or neoadjuvant treatments are ongoing. 4.2. Targeted Therapies or Immunotherapy in Resectable NSCLC: Which Patients? Adjuvant or Neoadjuvant Setting? The decision to perform a systemic treatment in an induction or adjuvant setting is still a matter of debate and this concept may also be considered as an item of precision surgery. For example, recent studies have shown that even for early-stage, radically resected NSCLC, micrometastases may be present before surgery and are considered the main factor causing postoperative local or distant recurrence . This is one of the main arguments in favor of also adopting induction treatments in the early stages. In patients with stage IB to stage IIIA NSCLC, a meta-analysis demonstrated an absolute 5% survival improvement at 5 years with preoperative chemotherapy compared to surgery alone . Neoadjuvant therapy has potential advantages: firstly, in vivo assessment of the response to chemotherapy helps identify patients who will potentially benefit from adjuvant treatment; secondly, it provides an early treatment for any potential micrometastatic disease; and finally, it allows a downstaging of the disease with improved resectability. Potential disadvantages include perioperative complications, delay in local treatment secondary to toxicity, and the risk of progression in patients with chemoresistant disease. In particular, the problem of chemoresistance seems to be predictable in the immunotherapy setting. In fact, the first studies demonstrated a correlation between patient prognosis, response rate to treatment and PD-L1 expression . However, these results are still debatable, as other studies have found that patients with high PD-L1 have worse survival rates . Additional research is necessary to justify its use as a prognostic indicator. However, PD-L1 expression may represent a significant factor as a predictive biomarker in the selection of patients for anti-PD-1/PD-L1 treatment. Although some studies found no correlation, many demonstrated greater response rates in patients with high PD-L1 expression in NSCLC tumors compared to low expression . Adjuvant therapy for early-stage NSCLC has the dual goals of treating micrometastatic disease and preventing recurrence. In fact, according to a meta-analysis, adjuvant chemotherapy improved absolute survival by 4% at 5 years for patients with resected early-stage NSCLC compared to surgery alone . However, it is still debatable whether adjuvant treatment is necessary following radical surgical resection of stage IB NSCLC. The ADAURA trial demonstrated that osimertinib, a third-generation EGFR-TKI, regardless of the use of adjuvant standard chemotherapy, significantly improved DFS with tolerable toxicity in patients with fully resected EGFR mutant NSCLC . As a result, osimertinib has been authorized for the adjuvant treatment of patients with resected NSCLC and EGFR mutations. Different clinical trials (e.g., NCT02273375, CheckMate-816, NCT03968419) evaluating the efficacy of adjuvant and neoadjuvant targeted and immunotherapy in early stages are ongoing, the first results will be ready from January 2024. 4.3. Redefining the Concept and the Management of Oligometastatic Disease Another patient population who may particularly benefit from these new therapeutic agents is that of patients affected by advanced stage disease. Indeed, the conventional treatment for advanced NSCLC has been sequential or concurrent chemo-radiotherapy with a dreadful prognosis. However, with molecular therapies, patients with even advanced metastatic NSCLC, for whom surgery was excluded at diagnosis, may have found a window for "curative" or debulking surgery after years of treatment creating a large "grey area" of potentially resectable lung cancers that may benefit from treatment protocols that include surgery. In this setting, the systemic therapy does not have the role of induction treatment, and surgery seems to develop a role of rescue therapy in patients with acquired resistance to targeted drugs. Without any doubt, the inevitable controversies around these complex cases highlight the key role of multidisciplinary tumor boards, preferentially in high-volume centers. In this sense, the exciting results of the new therapies will allow surgeons to play a greater role in more advanced stages with curative intent in mind. Moreover, especially in metastatic disease, genomic profiling seems to play a fundamental role in routine care. Indeed, in addition to the improved survival observed with targeted therapies against EGFR and ALK mutated patients, other studies have demonstrated great results with targeted therapies against BRAF, RET and MET . Israeli et al. reviewed 101 NSCLC patients with negative EGFR/ALK mutations that were tested by NGS. Finally, they discovered clinically relevant genetic changes in 50% of patients, changing the course of treatment for 43 patients. Above all, NGS also identified EGFR mutations in 15 patients with EGFR wild type at conventional testing . Regarding metastatic disease, stage IV is highly heterogeneous and, according to current data, survival may vary significantly and is strictly related to the location and quantity of metastases . It is particularly important in the concept of oligometastatic disease; in fact, it has been proposed as an intermediate state between localized and systematically metastasized disease. Clinical investigations conducted in this situation have demonstrated improved survival when regular systemic therapy is combined with radical local therapy (especially surgery) . With this new concept, metastatic NSCLC would no more be considered incurable per definition but must be treated using a multidisciplinary approach in order to clarify not only the localized primary and metastatic tumor lesions, but also the eventual disseminated circulating tumor cells. However, there is currently no clear agreement on the number of metastases and the number of affected organs that may constitute an oligometastatic state. Actually, five or fewer metastases in two or fewer organs have been utilized as a threshold for oligometastases in the majority of reported phase 2-4 clinical trials on the treatment of oligometastatic NSCLC. Moreover, there is still a debate on what is better to treat first and on the timing to perform systemic treatment. As described by Berzenji et al., two different types of approach to oligometastatic disease are possible . The first one includes the initial surgical removal of the primary tumor and, subsequently, the local treatment of metastases (surgery or SBRT) associated with systemic therapy (targeted or immunotherapy are advisable) for the control of micrometastatic disease. The second option consists of firstly performing a neoadjuvant treatment followed by a PET-CT scan restaging, and the subsequent resection of the primary tumor and metastatic lesions. The advantage of upfront surgery is that there is no risk of a decline in the performance status of the patient after an induction treatment and, consequently, a possible delay in surgery. However, with the introduction of the new therapies and their positive response, neoadjuvant treatment may be useful because it could eradicate micrometastasis not detected at the clinical evaluation and can achieve a reduction in tumor volume, promoting less invasive resections. The ETOP-CHESS trial will give us more results in this field. This trial is a single-arm, multicenter phase 2 trial evaluating the efficacy of durvalumab, a platinum-based doublet CT associated with radiotherapy and/or surgery in NSCLC with oligometastatic disease. Durvalumab is used as part of a treatment plan that also includes 4-6 cycles of platinum-based doublet CT and SBRT for all oligometastatic lesions. Radical excision or conclusive radiation therapy (RT) of the initial tumor will be used to complete the treatment for patients whose disease has not advanced at the 3-month FDG-PET/CT restaging. Finally, cases where disease progression is observed in one or a few sites while receiving aggressive systemic therapy should deserve careful attention. In this so-called oligoprogressive disease, evidence on the use of local treatments is scarce despite the rising number of clinical trials on oligometastatic NSCLC. Prospective studies evaluating the efficacy of immunotherapy or targeted therapy in an oligometastatic setting are ongoing and will be helpful to understand the correct timing of the different treatments. 4.4. Does Neoadjuvant Immunotherapy Complicate Surgical Resection? Another important concept to keep in mind when facing patients receiving target and/or immunotherapy is the clinical and pathological response of tissues to treatment and its consequences on the surgical approach. In fact, following immunotherapy, several authors have reported an intense inflammatory response in the tumor and in the lymph nodes, with the replacement of tumors by fibrotic scar tissue observed upon pathological analysis. Due to the potential negative effects on surgical viability, the potential use of immunotherapy and targeted therapy as a neoadjuvant treatment has raised a number of concerns. Indeed, inflammatory responses leading to hilar fibrosis could make surgical excision more difficult and technically demanding, thus affecting patients' morbidity and/or mortality. For example, the IoNESCO trial, a phase 2 study that consisted of the administration of durvalumab as a single agent before surgery, was stopped due to the high rate of severe postoperative complications (tracheal fistula, ARDS, severe pneumonia) . On the contrary, in the retrospective cohort study by Bott and colleagues, all 19 patients who were operated after ICIs treatment had a regular postoperative course, without unexpected morbidity or mortality; however, the surgical procedures were challenging, with more than half of the planned minimally invasive resections converted to open surgery due to hilar inflammation . The CheckMate-816 trial reported that the neoadjuvant addition of nivolumab to chemotherapy was tolerable and did not increase post-surgical complications. The surgical outcome analysis demonstrated that the chemoimmunotherapy patients had shorter procedures, needed fewer pneumonectomies, had higher rates of minimally invasive surgery and had fewer conversions to open surgery . Caution should also be exerted in case of severe comorbidities that augment the surgical risk, especially in current smokers. In this setting, the correct planning of the surgical procedure is fundamental. The use of minimally invasive approaches, parenchymal sparing techniques, bronchial and vascular reconstruction techniques and the avoidance of pneumonectomies are all well-known principles to improve postoperative outcomes, and may be considered an inherent part of the concept of precision surgery. Another aspect to consider concerns the increasing evidence that ICIs or targeted therapies administered in the neoadjuvant setting lead to a consistent rate of pathologic complete response after surgery. Therefore, it could be debated whether it is worthwhile to perform surgery with its possible complications on such patients, or if it could be avoided. Probably, at present, the answer remains yes, as we have no preoperative radiological instruments or biomarkers, currently, to confidently identify a patient with no residual disease after treatment. This is certainly an important aspect to investigate, and further studies may help us to answer this question better. 4.5. Evaluating Response to Treatment An additional issue related to the introduction of ICIs or targeted therapies is the definition of response to treatment. Chest-CT scans and PET with FDG are now commonly used to assess tumor response to treatment based on the RECIST criteria. However, in this new contest, even these conventional imaging tools can demonstrate equivocal results. In fact, it is debatable whether changes in tumor size, as revealed by radiological images, are indicative of therapeutic response; this is because tumors, in addition to malignant cells, may also contain stroma and inflammatory cells (such as T cells, fibroblasts, macrophages). In particular, peritumoral inflammation is responsible for a phenomenon called pseudoprogression. This is a particular type of clinical response, where the initial growth of the tumor's size is secondary to the infiltration of inflammatory cells and/or fibrosis due to activation of the immune system. It can appear in patients receiving ICIs or targeted therapies, and it is a significant misleading factor in the evaluation of therapeutic response and efficacy. According to this, Bott et al. firstly described two patients with radiologically stable disease after treatment with two cycles of nivolumab; however, the final pathological exams after surgery reported no residual tumor cells . To overcome these technical difficulties, modified RECIST criteria have been introduced to evaluate the response in patients who receive immunotherapy, the Immune Response Evaluation Criteria in Solid Tumors (iRECIST) introduced in 2017 . The basic principles that define the tumor response evaluation used in RECIST remain the same with iRECIST; however, to define tumor progression a confirmation of tumor enlargement after a minimum of 4 weeks and no later than 8 weeks from the last evaluation is required. Moreover, PET-CT images are fundamental, because by documenting fluorodeoxyglucose uptake (FDG), it is possible to distinguish between pseudoprogression and true progression in some cases . Regarding the pathological evaluation of tumor response, with the advent of new therapies, numerous histologic criteria were reviewed. Firstly the concept of the tumor bed was well-defined, which is the area where the original pre-treatment tumor was located . In this setting, the major three features used for analysis include necrosis, stromal fibrosis and viable tumor. The percent of viable tumors has consistently been shown to be the only prognostically significant histologic indicator. 5. Conclusions Molecular therapies opened a new era in the treatment of NSCLC that is no longer established upon the basis of the clinical and/or pathological TNM staging but is a therapy co-directed by histology, genotyping and immunotyping. This enables patients to receive individualized therapy, resulting in significant and frequently long-lasting treatment outcomes. In this context, the role of surgery is evolving, moving to a concept of precision thoracic surgery that aims to optimize and individualize patient selection and treatment based on a more sophisticated understanding of cancer, with the goal of giving each patient the most personalized and adequate therapeutic intervention available within our armamentarium. Author Contributions Conceptualization, G.C., G.M.C. and M.M.; methodology, G.P., E.F. and G.M.C.; writing--original draft preparation, G.C.; writing--review and editing, G.C., G.M.C., A.D. and M.M.; supervision, A.D., M.S., G.P. and F.R.; project administration, F.R. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. cancers-15-01571-t001_Table 1 Table 1 Neoadjuvant immunotherapy/target therapy trials. Trial Inclusion Criteria Treatment Arms Post-Surgery Therapy EMERGING-CTONG 1103 (NCT01407822) IIIA-N2 with EGFR-mutation Erlotinib vs. Cisplatin + Gemcitabine / CheckMate 77T (NCT04025879) II-IIIB (N2) Standard CT +Nivolumab vs Placebo Nivolumab vs. Placebo NADIM study (NCT03081689) Resectable IIIA NSCLC Paclitaxel + Carboplatin + Nivolumab vs. Placebo Nivolumab/ Observation CheckMate-816 (NCT02998528) Resectable IB (>4 cm)-IIIA Nivolumab + Platinum-based CT vs. Platinum-based CT CT +/- RT IMpower030 (NCT03456063) Resectable stage II-IIIB Atezolizumab + Platinum-based CT vs. Placebo + Platinum based CT Atezolizumab vs. Placebo Keynote 671 (NCT03425643) Stage IIB-IIIA Pembrolizumab + Platinum-based CT vs. placebo + platinum-based CT Pembrolizumab vs. Placebo AEGEAN (NCT03800134) Resectable stage IIA-IIIB Durvalumab + Platinum-based CT vs. Placebo + Platinum-based CT Durvalumab vs. Placebo NeoADAURA (NCT04351555) Resectable stage II-IIIB Osimertinib as single agent or in combination with Platinum-based CT vs.Placebo + Chemotherapy Osimertinib +/- CT cancers-15-01571-t002_Table 2 Table 2 Main adjuvant Immunotherapy/targeted therapy trials. Trial Inclusion Criteria Treatment Arms Primary Endpoints ADAURA (NCT02511106) Resected IB-IIIA NSCLC Osimertinib vs. standard CT DFS in stage II to IIIA disease Impower010 (NCT02486718) IB (4 cm)-IIIA after Adj CT Atezolizumab DFS PEARLS/KEYNOTE-091 (NCT02504372) Resected stage IB-IIIA Pembrolizumab DFS in overall population; DFS in population with PD-L1 > 50% NADIM-ADJUVANT (NCT04564157) Resected stage IB-IIIA CT + Nivolumab, then Nivolumab vs. Platinum-based CT DFS ALINA (NCT03456076) Resected stage IB-IIIA Alectinib vs. Platinum-based CT DFS ALCHEMIST (NCT04267848) Resected stage II-IIIA CT + concomitantPembrolizumab, then Pembrolizumab vs. CT + sequentialPembrolizumab, then Pembrolizumab vs. CT DFS Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000463 | The Coronavirus disease 2019 (COVID-19) outbreak impacted health care. We investigated its impact on the time to referral and diagnosis for symptomatic cancer patients in The Netherlands. We performed a national retrospective cohort study utilizing primary care records linked to The Netherlands Cancer Registry. For patients with symptomatic colorectal, lung, breast, or melanoma cancer, we manually explored free and coded texts to determine the durations of the primary care (IPC) and secondary care (ISC) diagnostic intervals during the first COVID-19 wave and pre-COVID-19. We found that the median IPC duration increased for colorectal cancer from 5 days (Interquartile Range (IQR) 1-29 days) pre-COVID-19 to 44 days (IQR 6-230, p < 0.01) during the first COVID-19 wave, and for lung cancer, the duration increased from 15 days (IQR) 3-47) to 41 days (IQR 7-102, p < 0.01). For breast cancer and melanoma, the change in IPC duration was negligible. The median ISC duration only increased for breast cancer, from 3 (IQR 2-7) to 6 days (IQR 3-9, p < 0.01). For colorectal cancer, lung cancer, and melanoma, the median ISC durations were 17.5 (IQR (9-52), 18 (IQR 7-40), and 9 (IQR 3-44) days, respectively, similar to pre-COVID-19 results. In conclusion, for colorectal and lung cancer, the time to primary care referral was substantially prolonged during the first COVID-19 wave. In such crises, targeted primary care support is needed to maintain effective cancer diagnosis. COVID cancer diagnosis primary care delay ZonMw--The Netherlands Organization for Health Research and Development10430022010014 This work was supported by ZonMw--The Netherlands Organization for Health Research and Development (grant number 10430022010014). The funding sources had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report, and in the decision to submit the article for publication. pmc1. Introduction The Coronavirus disease 2019 (COVID-19) pandemic has had a substantial impact on health care worldwide, altering the manner in which patients accessed care, health professionals provided care, and health care systems functioned . As the first wave of COVID-19 struck Europe in March 2020, health care provision and government policy focused on care for patients with COVID-19 and the prevention of its transmission. Lockdowns were implemented, and usual care processes were interrupted or stopped, producing major impacts on care for patients with non-COVID-19 conditions, such as cancer . This is evident from cancer diagnosis data from March to June 2020, with numbers of cancer diagnoses reportedly decreasing between 25-61% internationally . Delay in recognition, referral, and diagnosis of cancer patients can have a substantial impact on the disease burden and prognosis . Such delay is associated with later stages of cancer at diagnosis, more invasive treatments, greater impacts on patient lives and quality of life, and worse morbidity and mortality . In countries with primary care-based healthcare systems, the diagnosis of cancer largely occurs through the general practitioner (GP), with previous studies demonstrating that over 80% of cancer patients in Western Europe are diagnosed after contact with their GP . The first steps in the diagnostic process are integral for timely diagnosis and treatment; patients first recognize their symptoms, then present to their GP, who details these symptoms, investigates them if needed, and, if indicated, refers the patients to secondary care for diagnosis and treatment . During the first COVID-19 wave, the opportunities to perform face to face consultations and physical examination were restricted and in GP consultations there was a dominant focus on COVID-19, both by patients and GPs . Referral pathways were also affected, because of interruptions in routine investigations and overburdening of secondary care services . Therefore, we hypothesize that the first COVID-19 wave had a substantial impact on the time to recognition, referral, and diagnosis of cancer patients presenting to primary care. To enable the targeted prevention of delay in cancer diagnosis in future pandemics, detailed knowledge about the extent of such delay and its occurrence in specific populations is needed. To achieve this goal, we aim to map the impact of the first wave of the COVID-19 pandemic on the duration of the diagnostic pathway before and after primary care referral for symptomatic cancer patients in The Netherlands. 2. Materials and Methods 2.1. Study Design We performed a retrospective cohort study. To build our cohort, we linked routine primary care data to cancer registry data collected in primary care practices and hospitals in The Netherlands. This study was reported to be in line with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement . This research was reviewed by the institutional review board of the UMC Utrecht (21-144/C) and judged not to be subject to the Medical Research Involving Human Subjects Act of The Netherlands. 2.2. Data Primary care data was obtained from The Intercity Data Network, which combines data from the dynamic primary care cohorts of five academic primary care networks: the Academic Network of General Practice at Amsterdam University Medical Centre; location VU Medical Center (ANH VUmc) and location Amsterdam Medical Center (AHA AMC), the Research Network Family Medicine (RNFM) Maastricht, the Academic General Practitioner Development Network Groningen (AHON), and the Julius General Practitioners' Network Utrecht (JGPN). Together, they contain data from over 1.2 million adult primary care patients, which are representative of the Dutch population . This data contains deidentified coded and free text data, including free text descriptions of patient symptoms, physical examinations, working diagnoses, and case management. The symptoms and diagnoses are coded according to the International Classification of Primary Care (ICPC-1) coding system. Data from patients with diagnostic codes for cancer (colorectal, lung, and breast cancer, and melanoma) in the primary care dataset were linked to the Dutch National Cancer Registry (NCR) database by a third trusted party. The NCR is a national database which includes over 99% of Dutch cancer patients . NCR data include patient demographics, tumour histology, stage and localisation of cancer, date of diagnosis, and subsequent treatment. The Intercity Data Network, the NCR, and the linkage process have been described previously . 2.3. Population To select cancer patients for whom the primary care diagnostic interval (partially) overlapped with the first COVID-19 wave, we included patients from each database in the intercity network with a newly attributed ICPC-1 code for colorectal (code: D75), lung (R84), or breast (X76) cancer, or melanoma (S77.03) used after 1 March 2020. The diagnosis of cancer for each patient was confirmed by manual exploration of the free text data, thereby employing an established validation process described previously . The first wave of the COVID-19 pandemic was defined as "from the first of March to the 30 June 2020," informed by the National Institute for Public Health and the Environment (RIVM) . We selected patients who presented to the GP with cancer related symptoms, who were then referred to secondary care, and whose primary care diagnostic pathway overlapped with all or part of the first COVID-19 wave. We ceased screening routine care data for such patients for each cancer type if there were no new inclusions for two consecutive months after the first COVID-19 wave. Patients diagnosed through screening programs, specialists, or emergency departments, or who were asymptomatic, were excluded. For melanoma, patients who had a melanoma resected by the GP (and thus, were not referred to secondary care) were not included. Data for patients whose diagnostic interval served as the control period were collected in the previous Dickens project, as elaborated in the thesis of Nicole van Erp . These data describe the duration of the diagnostic process of symptomatic patients diagnosed with colorectal, lung, and breast cancer, and melanoma, prior to the COVID-19 pandemic, from 1 January 2012 to 31 December 2015. 2.4. Data Collection Information used to detail the time intervals of the diagnostic process in primary care was manually collected from the free text routine care data. All data collection was performed according to a data collection manual, which was developed in the previous Dickens project. We used identical methods for the pre-COVID-19 and COVID-19 cohorts . Data collection was performed by the research team comprised of medical doctors and medical students. If there were uncertainties, these were discussed and resolved within the study group. All data required for analysis was entered into Castor, an electronic data capture system, using a standardized capture procedure. The diagnostic time intervals employed in this study were developed from the Aarhus statement, described in Figure 1 . The primary care interval (IPC) was defined as the period between the first contact with primary care for suspected cancer-related signs or symptoms (which could be in-person or through video/telephone consultation) and the date of referral to specialist care. The date of referral is generally explicitly mentioned in primary care data. If not, the moment when responsibility for patient care was transferred to specialist care was identified in the free text and selected. In the case of multiple referrals, the first referral relating to cancer-related symptoms was chosen. The secondary care interval (ISC) was defined as the period between referral by the GP to secondary care and the histological cancer diagnosis, as retrieved from the NCR. Patient demographics, clinical characteristics, signs and symptoms, and dates of first consultation and referral were collected from primary care databases. Comorbidities were manually collected for each patient in accordance with the methods of O'Halloran et al. . Cancer alarm symptoms were assessed per cancer type according to predefined definitions, similar to those previously employed in the Dickens project to determine the pre-COVID-19 durations of IPC and ISC . 2.5. Analyses Patient demographics and clinical characteristics were detailed using descriptive statistics. The durations of the diagnostic intervals, for each cancer population and its subgroups (patient and clinical characteristics) were calculated in days for each cohort. Durations were expressed in medians and interquartile ranges because of the expected non-parametric distribution. Consistent with previous studies, to define same day referrals as 'one day,' one day was added to all intervals. The number of GP consultations with cancer-related complaints (for the specific cancer type) in IPC was counted with a maximum of one consultation per day and included the initial and referral consultation. Mann-Whitney U tests were employed for comparisons of differences regarding duration and number of consultations (COVID-19 versus pre-COVID-19), and a p-value of less than 0.05 was considered statistically significant. IBM SPSS software version 27 (Microsoft, Chicago, IL, USA) was employed for data analysis. 3. Results To assess the impact of the first wave of the COVID-19 pandemic on the duration of the diagnostic pathway before and after primary care referral for symptomatic cancer patients in The Netherlands, we performed a retrospective cohort study using routine primary care data linked to The Netherlands Cancer Registry. We screened 3182 cancer patients for eligibility (IPC overlap the first COVID-19 wave). Overlap of the first COVID-19 wave with IPC was found for 415 cancer patients, and with ISC for 273 patients. The inclusion process is described in a flow diagram in the Supplementary Materials ('Supplementary flow diagram'). In the prior Dickens project, which describes the pre-COVID-19 period, IPC and ISC durations were determined for 979 cancer patients . 3.1. Population Table 1 describes the patient demographics and clinical characteristics of the patients whose IPC or ISC overlapped with the first COVID-19 wave, and of patients included in the pre-COVID-19 study. The mean age at the first GP consultation was between 55 and 70 years, with the majority of patients (64-92%) having registered comorbid conditions. 3.2. Primary Care Interval (IPC) As shown in Figure 2, the primary care interval was prolonged during the first COVID-19 wave for patients with colorectal and lung cancer, but not for patients with breast cancer and melanoma. For colorectal cancer patients, the median IPC duration increased by 39 days, from 5 days (IQR 1-29) pre-COVID-19, to 44 days (IQR 6-230, p < 0.01) during the first wave. For lung cancer patients, the median duration from first consultation to referral increased by 26 days, from 15 days (IQR 3-47) to 41 days (IQR 7-101.75, p < 0.01). For breast cancer and melanoma patients the median IPC duration remained 1 day, and the P75 value, indicating the value above which the 25% longest durations occur, shifted from 1 to 2 days (not statistically significant). This lack of relevant change for breast cancer and melanoma was observed in all subgroup analyses, with median durations remaining at 1 day in all subgroups (not shown in Table). Subgroup analyses suggest differences in impact of the first COVID-19 wave on IPC duration for colorectal and lung cancer, as detailed in Table 2. For colorectal cancer, the observed increase in duration was the largest for females, young patients (<65), those with less than two comorbidities, and those with psychiatric comorbidity. For those with colorectal cancer and alarm symptoms (e.g., rectal bleeding), the median IPC duration increased from one day (IQR 1-18) pre-COVID-19 to one month during COVID-19 (IQR 13-169, p < 0.01). In contrast, for lung cancer, the largest absolute increase was observed for males, elderly patients (>=65), and those with more than two comorbidities or psychiatric comorbidity. The number of cancer symptom related GP consultations in IPC--for all cancer types--were significantly increased during the first COVID-19 wave. For colorectal and lung cancer, the median number of consultations in IPC was 3 (IQR; 2-6) and 4 (IQR; 3-6), as compared to 2 (IQR; 1-4) (p value for change: <0.01) and 3 (IQR; 2-5) (p value for change: <0.01) pre-COVID-19. For breast cancer and melanoma, the median number of consultations remained at 1, but a larger proportion of patients required more than one consultation (p value for change: both <0.05). 3.3. Secondary Care Interval (ISC) The ISC duration was only prolonged for breast cancer, increasing from a median of 3 days (IQR 2-7) before COVID-19, to 6 days (IQR 3-9, p < 0.01) during the first COVID-19 wave. ISC durations during the first COVID-19 wave for colorectal and lung cancer and melanoma were 17.5 (IQR 9-52), 18 (IQR 7-40), and 9 (IQR 3-44) days, respectively, which is similar to the pre-COVID-19 period. Only for lung cancer, the subgroup analyses showed differences; a significant increase in ISC duration for those with psychiatric co-morbidity, from a median of 16 days (IQR 8-30.5) pre-COVID-19 to 40 days during COVID-19 (IQR 14-49). Details on ISC duration before and during the first COVID-19 wave are available in the Supplementary Materials, Scheme S1. 4. Discussion 4.1. Main Findings These results describe substantial delays in primary care for colorectal and lung cancer patients during the first COVID-19 wave, particularly among the subgroups. For colorectal and lung cancer, the median primary care diagnostic interval during the first COVID-19 wave was 39 and 26 days longer than the pre-COVID-19 interval, respectively. Subgroup differences were suggested, affecting different groups for colorectal and lung cancer. The impact of COVID-19 on the secondary care interval was minimal, with only a small increase of three days observed for breast cancer. The delays observed for colorectal and lung cancer in primary care are worrying, given the extent of these delays and the tendency of these tumor types for rapid progression. Sud et al. studied the effect of a 2-month delay for major cancer types in a modeling study that showed an 11% and 7% worsening in 10-year survival rates for lung and colorectal cancer (estimated for a 65-year old patient) . Especially when considering the observed increase in duration of two to six months in P75 values (longest: 25%) for the diagnostic interval time in our study, the potential impact of the COVID-19-related delay on cancer burden and prognosis is worrisome. There were concerns that the impact of the COVID-19 pandemic would disproportionally affect vulnerable patients . Our results suggest that this may be true for colorectal and lung cancer patients with psychiatric comorbidities, for whom the impact of COVID-19 on the duration of the primary care pathway was observed to be twice as severe. Another worrying finding is that patients with colorectal and lung cancer presenting with alarm symptoms were also at increased risk of delay during the first COVID-19 wave. For both these patient populations, targeted delay prevention appears warranted in the case of future pandemics or similar disruptions to health systems. 4.2. Implications for Practice The finding that delays during the first COVID-19 wave occurred in colorectal and lung cancer patients, and hardly at all in melanoma and breast cancer, reflects the known challenges in detecting 'hard-to-recognise' cancers. While the symptoms of melanoma and breast cancer are generally clear, those of lung and colorectal cancer tend to be less specific. During the first COVID-19 wave, recent studies suggest that recognizing and acting upon less specific symptoms was increasingly challenging , particularly for lung cancer, since its symptoms (e.g., coughing) were considered a reason to shift to the use of video or telephone consultation instead of physical consultation during the first COVID-19 wave. This additional challenge in recognizing and referring cancer is reflected not only in a longer duration of the primary care pathway, but also in the additional consultations needed prior to referral. This is likely to be partially related to the increased use of telehealth during this period, resulting in many initial consultations through this medium, requiring a secondary consultation to facilitate a physical examination and a more detailed assessment . However, this alone is unlikely to be responsible for the observed delay. On a patient level, recent studies described patient-related barriers to being referred to specialist services during this period, including a reluctance to 'make a fuss,' and concerns of overburdening the health system or being infected with COVID-19 . On a system level, health professionals described challenges in accessing investigations and communicating with and referring to secondary care . Such barriers for referral are likely to be accentuated for cancer types that generally present with alarm symptoms that are less distinct and for which referral pathways are more complex. The secondary care diagnostic pathway did not appear to have experienced the same extensive delays during the first COVID-19 wave as those seen in the primary care phase. This is likely to be the effect of the well-developed and tailored nature of secondary care cancer pathways and their prioritization of cancer care in times of increased pressure on health care. Future directions: our findings show that the impact of the first wave of the COVID-19 pandemic on the diagnostic pathway of symptomatic cancer was the largest in primary care. The mechanisms underlying primary care delay seem multifactorial and inconsistent between cancer types and subgroups. To reduce the impact of future outbreaks on effective cancer diagnosis, improving understanding of the mechanisms leading to delay would facilitate the development of targeted support for the detection and referral of cancer patients by GPs. 4.3. Strength and Limitations This study employed routine care data from patients throughout The Netherlands for both the prior Dickens project and the current study. The main strength of such data is the large and diverse population from which the data is obtained, as well as the detailed clinical nature of the data. The availability of free text data, which can be used as a prospectively collected transcribed verbatim summary of daily practice consultations, allows very rich and detailed information to be used to determine milestones which mark the beginning and end of the primary care phase of the diagnostic pathway. It also enables the detailed registration of a broad range of symptoms and characteristics, which are not always registered in coded data. As symptoms are registered at the time of their occurrence, recall bias is eliminated. This rich primary care dataset includes over 1.2 million adult primary care patients, from different geographic and socioeconomic regions, which was then linked with the Netherlands Cancer Registry (NCR) database. Linkage to the NCR allows for the use of detailed and reliable information, such as the validation of cancer diagnosis and its date. Data from the pre-COVID-19 period (2012-2015) were used as a comparator. They originated from the same datasets, and we employed the same methods and measures for data collection, providing methodological consistency in order to compare results. Several limitations of this study should be taken into account. The numbers of cancer cases occurring in this study are substantially fewer than those in the prior Dickens study, which was used as the comparator. This is largely due to the inclusion criteria, which demand that presentation to the GP occurs during the first COVID-19 wave, which is a much shorter timeframe than that used in the previous Dickens study. Despite the dataset including over 1.2 million patients, only a small proportion of patients were diagnosed with these cancer types and had exhibited their diagnostic periods within this timeframe. We expect to have included all eligible patients within this inclusion period because of continued screening for patients up to one year after the end of the first COVID-19 wave. However, it is possible that, in the event that cancer was diagnosed more than one year after the first COVID-19 wave, we missed some patients with extensive delays. Routine care data contains complexities, errors, and intricacies. This data is entered by many different health practitioners while--and for the purpose of--providing clinical care for patients. Thus, data collection was very time consuming and can be subject to interpretation. For optimal yield and the prevention of error and subjectivity, data collection was done according to a set framework, and was performed by different researchers with clinical experience, such as medical students or doctors. Similar to the prior Dickens project, if there were uncertainties or missing information in the data that made the diagnostic pathway of the patient unclear, these patients were excluded. Despite this extensive effort, our data may be incomplete and subject to misinterpretation. Routine care data can be incomplete or sub-optimally coded for research purposes. Consequently, missing diagnostic codes could have occurred; i.e., for some patients, the right ICPC code for the cancer diagnosis might not (yet) have been attributed by the GP . This would lead to missing cancer patients in our dataset. Additionally, if there were uncertainties about the cancer diagnostic processes (i.e., the presence of cancer related symptoms, or when a referral occurred), these patients were excluded. A total of 555 patients were excluded because of an 'unclear diagnostic pathway'. Fortunately, the number of patients which could be included were consistent with our original estimates, which were based on the previous Dickens project. We believe the total numbers included are representative and sufficient to robustly demonstrate clinically relevant differences in the diagnostic periods in comparison with the pre-COVID-19 data. Moreover, by adding NCR data to the primary care data required linkage using pre-approved third trusted-party employment and privacy procedures, ensuring the non-reducibility of the data. Such procedures, similar to those in preceding projects, lead to loss of patients, which is generally thought to be a non-selective loss . It should be noted that our analyses of the impact of the COVID-19 outbreak do not include the delay in the diagnostic process which may have occurred before presentation to primary care, in other words, the patient interval from the time of first symptom recognition to consulting primary care. Recent findings suggest that there was widespread avoidance of primary care during the first COVID-19 wave, with reductions of up to 34% in patient presentations with cancer-related symptoms during this period . This delay due to care avoidance is likely to add to the delay observed in our study. Moreover, our findings only describe the impact of the first COVID-19 wave and not the impact during the full COVID-19 pandemic. The impact of the first wave on both health care performance and patient behavior is likely to be larger during the first wave than during consecutive waves . Finally, it should be taken into account that--for colorectal and breast cancer--a national screening program exists in The Netherlands, which was halted because of COVID-19 halfway through March 2020. Additionally, we did not include patients visiting the emergency room. Therefore, our findings are not representative of all new cancer patients, and changes in these other pathways may have influenced the selection of patients visiting primary care with symptoms . Given our focus only on symptomatic patients presenting to primary care during the relatively short first wave of COVID-19, we do not expect this to have impacted our findings. 5. Conclusions This study demonstrates that time to referral in primary care was substantially prolonged during the first COVID-19 wave for patients with colorectal or lung cancer. This impact seems to vary for subgroups, and it is inconsistent between cancer types. For these 'hard-to-diagnose-cancer-types' that exhibit less distinct referral criteria and pathways, delay also occurred in patients presenting with alarm symptoms. For patient populations at risk of pandemic-related delays in primary care, targeted support for detection and referral by GPs seems warranted to ensure effective cancer diagnosis in future pandemics or similar crises. Acknowledgments We would like to thank over 40 medical students from UU medical school who supported the data collection. We also thank the data managers and coordinators affiliated with the retrospective regional databases for sharing and extracting the data for the purposes of this scientific research: Pauline Slottje, Research Coordinator ANH-VUmc Academic Network of General Practice database, Amsterdam UMC location Vrije Universiteit; Hanna Joosten, the Academic Network of General Practice Amsterdam UMC (ANHA); Feikje Groenhof and Ronald Wilmink, University of Groningen, University Medical Center Groningen (AHON database); and Huibert Tange and Donovan de Jonge, Maastricht University, Care and Public Health Research Institute, Department of General Practice (RNFM database). In particular, thanks go to Marloes van Beurden and Nicole Boekema, Julius Center for Health Sciences and Primary Care, for developing the queries employed in the databases that made this research possible and for sharing and extracting data of the JGPN--Julius Center, University Medical Center Utrecht. The authors thank the registration team of The Netherlands Comprehensive Cancer Organization (IKNL) for the collection of data for The Netherlands Cancer Registry. The authors also acknowledge the other members of the COVID-19 and Cancer-NL Consortium: J.C. van Hoeve, department of research and development, Netherlands Comprehensive Cancer Organization (IKNL), Utrecht; M.A.W. Merkx, Department of Research and Development, Netherlands Comprehensive Cancer Organization (IKNL), Utrecht; Department IQ Healthcare, Radboud University Nijmegen Medical Center, Nijmegen; I. Dingemans, Dutch Federation of Cancer Patient Organizations (NFK), Utrecht; I.D. Nagtegaal, department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, on behalf of the Automated Pathology Archive (PALGA); M. van der Schaaf, Department of Insight and Innovation, Dutch Hospital Data (DHD), Utrecht; H.C.P.M. van Weert, Department of General Practice, Amsterdam Public Health, Amsterdam UMC location AMC, Amsterdam; M. Verheij, Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, on behalf of SONCOS (Dutch Multidisciplinary Oncology Foundation); all The Netherlands. This research has been conducted using the ANH VUmc, AHA AMC, AHON, RNFM, and JGPN databases. These are ongoing longitudinal databases containing pseudonymized routine general practice care data extracted from the electronic medical records of participating general practices in different regions of The Netherlands. These databases can be used for scientific research relevant for (general practice) care. Patients are informed about the databases by their general practices. The databases contain data from all enlisted patients, except for those who object to this (opt-out). Detailed information about the cancer diagnoses was obtained from The Netherlands Cancer Registration (NCR). The NCR is a population-based registry with detailed diagnostic and therapeutic data of over 99% of Dutch cancer patients since 1989. Supplementary Materials The following supporting information can be downloaded at: Supplementary flow diagram (Scheme S1)--study inclusion of patients diagnosed with cancer during first COVID-19 wave; Supplementary Table S1--Duration of the secondary care interval (ISC), and time between GP referral and histological diagnosis, before and during the first COVID-19 wave for colorectal, lung, breast cancer, and melanoma. Click here for additional data file. Author Contributions The below-mentioned authors contributed to the following aspects of the research and manuscript: conceptualization, C.W.H., C.H.V.G., N.F.V.E., J.M. and N.J.D.W.; data curation, C.W.H., N.F.V.E., K.M.V.A., J.M., D.B., S.S. and M.P.G.; formal analysis, C.W.H., C.H.V.G., M.F.R.S.v.d.B., O.R. and M.P.G.; funding acquisition, C.W.H., C.H.V.G., S.S. and N.J.D.W.; investigation, C.W.H. and N.F.V.E.; methodology, C.W.H., C.H.V.G., N.F.V.E., M.F.R.S.v.d.B., O.R. and M.P.G.; project administration, C.W.H.; resources, C.W.H.; supervision, C.W.H., C.H.V.G. and M.P.G.; visualization, C.W.H., N.F.V.E. and M.P.G.; writing--original draft, C.W.H. and M.P.G.; Writing--review and editing, C.W.H., C.H.V.G., N.F.V.E., M.F.R.S.v.d.B., O.R., K.M.V.A., O.R.M., J.M., D.B., N.J.D.W., M.P.G. and The COVID-19 and Cancer Consortium. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was not subject to the Dutch Medical Research Involving Human Subjects Act, and therefore, the Research Ethics Committee of the University Medical Center Utrecht judged the study exempt from assessment (21-440/C). Informed Consent Statement This study utilizes aggregated data from a dynamic longitudinal cohort, with informed opt-out consent. Patient consent was waived for this particular study because non-identifiable aggregated data were used. Data Availability Statement The de-identified participant data used for the analysis can be disclosed by the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Primary care cancer diagnostic intervals included in the pathway from time of first symptom presentation to diagnosis, including the primary care interval (IPC) and the secondary care interval (ISC), as detailed in the Aarhus statement . Figure 2 Distribution of primary care interval (IPC) durations for each cancer type, comparing IPC durations pre-COVID-19 with those during COVID-19. P50 marks the median, P25 the 25th percentile, and P75 the 75th percentile. cancers-15-01462-t001_Table 1 Table 1 Patient demographic and clinical characteristics per cancer type for pre-COVID-19 (2012-2015) and the first COVID-19 wave (March-June 2020). Registered comorbidity was defined in accordance with O'Halloran et al. . Cancer Type Colorectal Lung Breast Melanoma Time Period Pre-COVID-19 COVID-19 Pre-COVID-19 COVID-19 Pre-COVID-19 COVID-19 Pre-COVID-19 COVID-19 Primary Care Interval N 313 110 236 118 306 140 124 47 Female--n (%) 154 (49) 66 (60) 104 (44) 62 (53) 306 (100) 140 (100) 61 (49) 28 (60) Age at first GP consultation--mean (SD) 69.5 (12.5) 68.4 (14.4) 68.6 (11.1) 66.4 (10.9) 57.5 (18.2) 58.9 (17.4) 55.0 (17.0) 60.7 (18.1) Registered comorbidity--n (%) 287 (92) 90 (82) 218 (92) 96 (81) 241 (79) 90 (64) 85 (69) 31 (66) Psychiatric comorbidity--n (%) 79 (25) 20 (18) 48 (20) 27 (23) 52 (17) 42 (30) 28 (20) 8 (17) Secondary Care Interval N 259 62 197 75 256 110 106 26 Female--n (%) 130 (50) 33 (53) 87 (44) 42 (56) 256 (100) 110 (100) 52 (49) 14 (54) Age--mean (SD) 69.1 (12.4) 67.8 (14.7) 68.6 (10.6) 67.0 (9.6) 57.8 (17.4) 57.3 (17.3) 58.3 (15.2) 65.0 (16.8) Registered comorbidity--n (%) 236 (91) 52 (84) 182 (92) 65 (87) 202 (79) 74 (67) 77 (73) 23 (89) Psychiatric comorbidity--n (%) 66 (26) 13 (21) 40 (20) 14 (19) 44 (17) 32 (29) 19 (18) 2 (8) cancers-15-01462-t002_Table 2 Table 2 Impact of first COVID-19 wave on duration of the primary care interval--total and subgroups. Cancer Type and COVID-19 Impact Colorectal Cancer Lung Cancer Pre COVID-19 1st Wave COVID-19 p for Diff. Absolute Increase Median Duration (Days) Pre COVID-19 1st Wave COVID-19 p for Diff. Absolute Increase Median Duration (Days) Median IPC Duration in Days (IQR) Median IPC Duration Days (IQR) Total Number of patients (N) N = CPC: 313 CC: 110 LPC: 166 LC: 118 5 (1-29) 44 (6-230) <0.01 39 15 (3-47) 41 (7-102) <0.01 26 Gender Male --N: CPC: 159 CC: 44 LPC: 132 LC: 56 3 (1-25) 30 (2-177) <0.01 27 13 (2-40) 46 (7-98) <0.01 33 Female--N: CPC: 154 CC:66 LPC: 104 LC: 62 7 (1-30) 66 (8-252) <0.01 59 18 (5-50) 40 (6-107) 0.04 22 Age <65 --N: CPC: 100 CC: 37 LPC: 83 LC: 50 4 (1-24) 67 (12-240) <0.01 63 15 (5-51) 31 (7-92) 0.05 16 >=65--N: CPC: 213 CC: 73 LPC: 153 LC: 68 6 (1-32) 37 (4-231) <0.01 31 15 (3-44) 47 (7-105) <0.01 32 Comorbidities present <2--N: CPC: 60 CC: 44 LPC: 53 LC: 43 2 (1-15) 57 (2-231) <0.01 55 10 (1-24) 29 (8-99) <0.01 19 >=2--N: CPC: 247 CC: 66 LPC: 177 LC: 75 6 (1-31) 42 (8-231) <0.01 36 20 (5-51) 46 (6-108) <0.01 27 Psychiatric comorbidity Yes --N: CPC: 79 CC: 20 LPC: 48 LC: 27 5 (1-19) 70 (22-259) <0.01 65 19 (5-50) 55 (11-123) <0.01 36 No--N: CPC: 230 CC: 90 LPC: 187 LC: 91 5 (1-33) 27.5 (4-216) <0.01 22.5 15 (2-44) 32 (5-92) <0.01 17 Alarm symptom at first consult Yes --N: CPC: 169 CC: 45 LPC: 188 LC: 45 1 (1-18) 37 (13-169) <0.01 36 18 (1-18) 37 (2-169) 0.6 19 No--N: CPC: 144 CC: 65 LPC: 188 LC: 101 11.5 (1-35) 52 (13-252) <0.01 40 18 (6-50) 48 (11-108) <0.01 30 GP consult frequency--prior year <5--N: CPC: 130 CC: 56 LPC: 120 LC: 71 4 (1-26) 25 (4-189) <0.01 21 11 (2-37) 39 (9-88) <0.01 28 >=5 --N: CPC: 103 CC: 54 LPC: 66 LC: 47 6 (1-29) 50 (10-232) <0.01 44 18.5 (6-50) 45 (5-108) 0.04 26.5 (N): number of patients; CPC: colorectal cancer pre-COVID-19; CC: colorectal cancer 1st wave COVID-19; LPC: lung cancer pre-COVID-19; LC: lung cancer 1st wave COVID-19. If numbers do not add up to expected total, this is due to missing (left out) information. p. for diff.: p-value for difference in IPC durations pre-COVID-19 and during first COVID-19 wave. No significance testing for differences in COVID-19 impact between subgroups within cancer populations was performed because of low N. IQR: interquartile range. Periods: pre-COVID-19: 2012-2015; first COVID-19 wave: March-June 2020. Comorbidity was defined in accordance with O'Halloran et al. . Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000464 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051083 foods-12-01083 Article Screening of Lesser-Known Salted-Dried Fish Species for Fatty Acids, Tocols, and Squalene Lyashenko Svetlana 1 Chileh-Chelh Tarik 1 Rincon-Cervera Miguel Angel 12 Lyashenko Svetlana P. 1 Ishenko Zalina 3 Denisenko Oleg 3 Karpenko Valentina 3 Torres-Garcia Irene 1 Guil-Guerrero Jose Luis 1* Brys Joanna Academic Editor Malajowicz Jolanta Academic Editor 1 Food Technology Division, ceiA3, CIAMBITAL, University of Almeria, 04120 Almeria, Spain 2 Institute of Nutrition and Food Technology, University of Chile, 7830490 Macul, Chile 3 Pyatigorsk Medical and Pharmaceutical Institute, Branch of Volgograd State Medical University, 357500 Pyatigorsk, Russia * Correspondence: [email protected] 03 3 2023 3 2023 12 5 108331 1 2023 27 2 2023 01 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The fillets and roes of 29 species of dry-salted fishes consumed in Eurasian countries were analyzed for fatty acids (FAs), tocols, and squalene, looking for derived health benefits. FAs were analyzed by GC-FID, and tocols and squalene were analyzed by HPLC-DAD. With some exceptions, docosahexaenoic (DHA, 22:6n-3), eicosapentaenoic (EPA, 20:5n-3), and arachidonic (ARA, 20:4n-6) acids were the prominent polyunsaturated fatty acids (PUFAs). The fillets of Scardinius erythrophthalmus reached the highest amounts of total FAs, ARA, and DHA (23.1, 1.82, and 2.49 mg/100 g). The fillets of Seriola quinqueradiata showed the highest percentages of DHA (34.4% of total FAs). Nutritional quality indices for fish lipids were favorable in all samples, especially the n-6/n-3 PUFA ratio, which was below 1 in most cases. a-Tocopherol was found in all fillets and roes, especially in Cyprinidae and Pleuronectidae species, and the highest value was found in the roes of Abramis brama (5.43 mg/100 g). Most samples contained tocotrienols at trace levels. The fillets of Clupeonella cultriventris contained the highest amounts of squalene (1.83 mg/100 g). Overall, dry-salted fish stand out due to their high concentrations of ARA, EPA, and DHA, as well as for a-tocopherol concentrations in roes. salted-dried fish omega-3 fatty acids DHA EPA tocopherols squalene nutritional quality indices University of AlmeriaPPUENTE2020/005 Junta de AndaluciaProject P20_00806 Campus de Excelencia Internacional Agroalimentario (ceiA3)Centro de Investigacion en Agrosistemas Intensivos Mediterraneos y biotecnologia Agroalimentaria (CIAMBITAL)This research was supported by the Vicerrectorado de Investigacion e Innovacion of University of Almeria (PPUENTE2020/005), Junta de Andalucia (Project P20_00806), Campus de Excelencia Internacional Agroalimentario (ceiA3), and Centro de Investigacion en Agrosistemas Intensivos Mediterraneos y biotecnologia Agroalimentaria (CIAMBITAL). M.A. Rincon-Cervera acknowledges the support of the Postdoctoral Program "Maria Zambrano". pmc1. Introduction Fish are among the most perishable food items, and several methods have been implemented worldwide for preserving them. Fish drying is a simple and inexpensive preservation method usually employed in many European and Asian countries. Drying implies the removal of water from the fish body through evaporation by exposure to the sun and air flow, which gives characteristic color, texture, and flavor to dried fishes . The consumer preference towards dried fish products is not only because of their traditionally pleasant taste and flavor, but also due to their high amounts of n-3 (omega-3) polyunsaturated fatty acids (n-3 PUFAs), which are perceived by the population as health-promoting nutrients. n-3 PUFAs improve health by decreasing the risk of cardiovascular diseases (CVDs); reducing serum triacylglycerol levels, blood pressure, and insulin resistance; modulating the glucose metabolism and inflammatory processes; and developing a neuroprotective role . Many fish species are known to be excellent dietary sources of different n-3 and n-6 PUFAs, particularly arachidonic acid (ARA, 20:4n-6), eicosapentaenoic acid (EPA, 20:5n-3), and docosahexaenoic acid (DHA, 22:6n-3) . ARA plays an essential role in the human body since it is the precursor of eicosanoids that modulate inflammation and are involved in platelet aggregation and blood clotting. EPA and DHA are involved in many physiological functions such as the fluidity of cell membranes and gene expression. These PUFAs decrease the risk of cardiovascular diseases (CVDs) and neurological disorders and ameliorate the harmful effects of fatty liver and oxidative stress. Furthermore, both of these n-3 PUFAs are the metabolic precursors of lipid mediators having anti-inflammatory properties . Although EPA and DHA can be synthesized in the human body from their metabolic precursor a-linolenic acid (ALA, 18:3n-3), the conversion rate is very low because of the limited activity of the D6-desaturase enzyme, which is involved in the metabolic pathway from ALA to long-chain n-3 PUFAs (LCPUFAs). Thus, both EPA and DHA should be included in the diet, and marine foods are the most important sources . The European Food Safety Authority (EFSA) gave recommendations for n-3 LCPUFAs in 2010 . For adults, an adequate intake of EPA + DHA was established at 250 mg/day; for infants and young children, it was set at 100 mg/day for DHA; and for pregnancy and lactation, it was 100-200 mg of DHA. However, higher doses of EPA and DHA (1-2 g/day) may be needed to achieve therapeutic effects in secondary prevention strategies for CVD . Dry-salted fishes are consumed as snacks worldwide; however, little information is available regarding the nutritional quality of these products, particularly concerning tocol (Tc) and squalene (Sq) contents. The interest in characterizing Tc content in foods has increased in the last decades, probably due to the awareness of their health impact. Tocols, which comprise tocopherols (T's) and tocotrienols (T3's), are essential compounds for human nutrition because of their vitamin E and antioxidant bioactivities . Tocols prevent lipid peroxidation by acting as reactive oxygen species scavengers , possess antitumor and anti-inflammatory activities, and prevent CVD and diabetes . On the other hand, Sq displays antioxidant and anti-inflammatory properties, and its intake could be useful for the treatment and prevention of CVD . The aim of this work was to assess the FA profiles, lipid quality indices, and Tc and Sq contents of several dry-salted fishes and roes worldwide consumed. Improving knowledge on this subject will contribute to expanding the limited information available on the nutritional quality of lipids contained in such food products. 2. Material and Methods 2.1. Solvents and Reagents Unless otherwise stated, solvents and reagents were purchased from Sigma-Aldrich (Barcelona, Spain). 2.2. Samples Data regarding samples analyzed in the current study are shown in Table 1. Twenty-eight samples of salted-dried fish and seven samples of roes were selected, resulting in twenty-nine commercially important fish species. The production process of the salted fish analyzed in this work is regulated in the Russian Federation by GOST R 51574-2000 standards. The process can be found at In this process, the mass fraction of table salt in fish meat fits within the 3-6% range. Each species was purchased in five different local markets in the city of Essentuki (Russian Federation), all of them coming from the same industrial process. Individual samples were analyzed separately in triplicate, and average values +-SD calculated for five samples of each species are detailed in tables. 2.3. Moisture Content This procedure is described in Supplementary File S1. 2.4. Fatty Acid Analyses The FA profiles were obtained after direct derivatization of the FAs contained in samples to FA methyl esters (FAMEs), as described in a recent paper by our research group . FAME analyses were performed using a Focus GC (Thermo Electron, Cambridge, UK) equipped with a flame ionization detector (FID) and an Omegawax 250 capillary column. This methodology is fully described in Supplementary File S1. 2.5. Nutritional Quality Indices of Lipids Six indicators based on FA composition were estimated as nutritional quality indices of sampled foods: n-6/n-3 ratio, PUFA/saturated FA (SFA) ratio, atherogenic index (AI), thrombogenic index (TI), hypocholesterolemic/hypercholesterolemic FA ratio (HH), and fish lipid quality (FLQ). AI, TI, HH, and FLQ were calculated according to . To calculate the nutritional indices, the FA concentrations were expressed as mg/100 g. AI = [12:0 + (4 x 14:0) + 16:0]/S Unsaturated FA TI = (14:0 + 16:0 + 18:0)/[(0.5 x S MUFA) + (0. 5x S n-6 PUFA) + (3 x S n-3 PUFA) + (n-3/n-6)] HH = (cis-18:1+ S PUFA)/(12:0 + 14:0 + 16:0) FLQ =100 x (22:6 n-3 + 20:5 n-3)/SFA 2.6. Extraction of Tocols and Squalene This was carried out as described in a previous paper from our research group , and is fully described in Supplementary File S1. 2.7. Analysis of Tocols and Squalene T and T3 homologs were determined using an RP-HPLC instrument (Agilent 1100 series, Palo Alto, CA, USA) equipped with a diode array detector (DAD) and a ProntoSIL C30 column (4.6 x 250 mm, 3 mm; Bischoff Chromatography, Leonberg, Germany) according to . Sq was determined by RP-HPLC/DAD using a Luna C18 column (250 x 4.6 mm, 5 mm; Phenomenex) at a fixed temperature of 30 degC. This methodology is fully described in Supplementary File S1. Tocopherol and tocotrienol contents were used for vitamin E activity (VEA) calculation , according to the following equation:VEA = a-T + (b-T*0.5) + (g-T*0.1) + (d-T*0.03) + (a-T3*0.3) + (b-T3*0.05) + (g-T3*0.01) where different T's and T3's corresponded to the different tocopherol and tocotrienol contents, respectively, expressed as mg/g. The results were expressed as a-T equivalents (mg/g). 2.8. Statistical Analysis Mean values of three samples analyzed in triplicate are reported as mean value +- SD in tables. Normally distributed data was assessed using a Shapiro-Wilk test, and variance homogeneity was verified using Levene's test. All data were analyzed using one-way ANOVA (Statgraphics Centurion XVI.I, Warrenton, VA, USA). Significant differences among mean values were checked through Duncan's test (p < 0.05). 3. Results 3.1. Moisture Content The moisture content of samples is detailed in Table 2. In fish fillets, it ranged from 12.2 (Aspius aspius) to 20.3 g/100 g (Pleuronectes quadrituberculatus). In roe samples, the range was between 20.4 (Scardinius erythrophthalmus) and 25.6 g/100 g (Osmerus mordax). 3.2. Total Fatty Acid Content The total FAs of sampled fishes and roes are summarized in Table 2. Among fishes, the total FA amount ranged between 1.7 in Ballerus sapa and 23.1 g/100 g in S. erythrophthalmus. Among roe samples, the lowest FA contents were detected in Abramis brama and O. mordax (2.9 g/100 g), whereas the roes from Cyrprinus carpio and S. erythrophthalmus were at the top of the range (12.8 g/100 g). Overall, the FA content was generally higher in fish than in roes for the same species: the ratio of FA content between fish and roes from A. brama, Rutilus caspicus, O. mordax, and P. quadrituberculatus ranged between 1.40 and 1.50, whereas for S. erythrophthalmus, this value was 1.80. The only exception to this trend was C. carpio, which showed a lower FA content in fish than in roes (ratio 0.62). S. erythrophthalmus was the species with the highest FA content in fillets and roes. 3.3. Fatty Acid Profiles Data on FA content are shown in Table 2 (FA profiles) and Supplementary Table S1 (FA groups). SFAs ranged between 20.6% (Gadus morhua) and 39.6% (Hypophthalmichthys molitrix) in the fillet samples and between 26.4% (P. quadrituberculatus) and 36.1% (S. erythrophthalmus) in the roe samples. SFAs reached higher percentages than monounsaturated FAs (MUFAs) and PUFAs in the roes of C. carpio, H. molitrix, Mullus barbatus, and Laemonema longipes. Palmitic acid (PA, 16:0) was the main SFA in almost all cases, and only the fillets of C. carpio showed similar proportions of PA and stearic acid (SA, 18:0). MUFAs ranged between 12.3 (Seriola quinqueradiata) and 49.3% (Clupeonella cultriventris). This was the most abundant FA group in C. cultriventris, Alosa kessleri, Rutilus heckelii, Pelecus cultratus, A. aspius, Blice bjoerkna, Parasilurus asotus, P. quadrituberculatus, and Alburnus mento, and in the roes of O. mordax. Oleic acid (OA, 18:1n-9) was the main MUFA in all samples, except in P. quadrituberculatus, which contained palmitoleic acid (POA, 16:1n-7) as the main MUFA. PUFAs ranged between 13.1 (A. aspius) and 49.7% (S. quinqueradiata) and were the most abundant FA group in both fillets and roes. In most cases, n-3 PUFA percentages were higher than n-6 ones. With some exceptions, DHA, EPA, and ARA were the most abundant PUFAs. The fillets of S. quinqueradiata, G. chalcogrammus, and Perca fluviatilis showed the highest amounts of DHA, with 34.4, 31.5, and 30.6% of total FAs, respectively, while in roes, DHA ranged from 10.5 (O. mordax) to 22.6% (R. caspicus) of total FAs. The highest percentages of EPA were found in the fillets of Pleuronectes quadrituberculatus and G. morhua and in the roes of P. quadrituberculatus (21.3, 17.9, and 18.8% of total FAs, respectively). Docosapentaenoic acid (DPA, 22:5n-3) was found in proportions >=5.0% in three samples of fillets (C. carpio, S. quinqueradiata, and Perca fluviatilis) and three samples of roes (L. longipes, P. quadrituberculatus, and C. carpio). The fillets of A. aspius and Barbus tauricus showed the lowest percentages of EPA + DHA (8.8 and 8.9%), whereas S. quinqueradiata (39.4), Gadus chalcogrammus (39.8), and G. morhua (41.0%) showed the highest EPA + DHA proportions. Roe samples showed intermediate values for EPA + DHA percentages (from 16.6 in L. longipes to 37.3% in P. quadrituberculatus). DHA percentages were in most cases higher than EPA percentages. 3.4. Nutritional Quality Indices of Lipids Six nutritional indices were calculated (Supplementary Table S2). The PUFA/SFA ratio ranged between 0.36 (A. aspius) and 2.15 (G. morhua). In roe samples, this ratio was between 0.84 (L. longipes) and 1.74 (P. quadrituberculatus). The n-6/n-3 PUFA ratio was below 1, except in B. tauricus fillets (1.52). AI and TI were below 1 in all cases, ranging from 0.24 (B. tauricus) to 0.73 (H. molitrix) and from 0.15 (P. quadrituberculatus) to 0.57 (P. cultratus) in fillets, respectively. On the other hand, A. aspius and B. tauricus fillets showed the lowest (1.80) and highest (4.85) HH values, respectively, while FLQ was between 9.70 (A. aspius fillets) and 42.10 (P. quadrituberculatus roes). Other samples having good FLQ values were the fillets of G. morhua (41.88), S. quinqueradiata (40.41), and G. chalcogrammus (39.84). 3.5. Tocol and Squalene Contents T and Sq amounts are detailed in Table 3. Among T isoforms, a-T was found in all fillets and roes. The samples having the highest a-T values were the roes of A. brama and P. quadrituberculatus (5.43 and 6.23 mg/100 g). The lowest amounts of a-T were found in the fillets of M. barbatus and O. mordax (0.16 mg/100 g) and in the roes of L. longipes (0.89 mg/100 g). g-T was found only in small amounts in the fillets of B. tauricus, Ballerus ballerus, and P. quadrituberculatus (0.18, 0.04, and 0.04 mg/100 g), as well as in the roes of A. brama (0.19 mg/100 g). d-T were below the detection limit in all samples. Regarding T3's, g-T3 were found in most samples at trace levels, that is, detected but below the LOQ. It was only possible to quantify a-T3 in the roes of A. brama and P. quadrituberculatus (0.09 and 0.08 mg/100 g), and g-T3 was quantified in the fillets of B. tauricus and S. erythrophthalmus (0.05 and 0.06 mg/100 g). The VEA, expressed as a-T equivalents, ranged from 1.6 in the fillets of M. barbatus and O. mordax to 6.26 mg/100 g in the roes of P. quadrituberculatus. The VEA range for fillets (from 0.16 in M. barbatus to 3.15 mg/100 g in P. quadrituberculatus) was lower than that for roes (from 0.89 in L. longipes to 6.26 mg/100 g) due to the low a-T content of the former, which is the most active vitamer. Sq was found in variable amounts in 29 out of 35 analyzed samples, and the highest concentrations were detected in the fillets of C. cultriventris and S. quinqueradiata (1.83 and 1.54 mg/100 g). All roes contained this compound, and the range was between 0.05 (S. erythrophthalmus) and 0.70 mg/100 g (R. caspicus); for fillets, Sq ranged from undetectable levels in eight samples to 1.83 mg/100 g in C. cultriventris. 4. Discussion 4.1. Total Fatty Acid Content The highest amounts of total FAs were found in the fillets of Clupeonella cultriventris (19.7) and S. erythrophthalmus (23.1 g/100 g), both of marine origin (Table 1), while most of the analyzed fish of fluvial origin had low total FA values. The total FA amounts of the former agree with those shown by salted mackerel, which is the name for over 30 species of pelagic or midwater-dwelling fish belonging to the Scombridae family. For this type of marine/fatty fish, the USDA Nutrient Database (FDC ID: 168149) indicates 21.7 g of fat per 100 g of fillet , which is in good agreement with the best fatty fishes reported here. 4.2. Fatty Acid Composition Concerning n-3 PUFAs, DHA was especially abundant in the families Carangidae (~25-34% of total FAs), Gadidae (~23-32%), Osmeridae (~23-38%), and Percidae (~31%). EPA stands out in roes of the Osmeridae and Pleuronectidae species (16.4 and 18.8%) and in fillets of the Pleuronectidae (21.3%) and Gadidae (8-18%) species. As for n-6 PUFAs, ARA reached the maximum percentages in the roes of Cyprinidae and Moridae species (~4-7%) and in fillets of Mulllidae (4.8%). Considering n-9 MUFAs, OA was the predominant FA of Clupeidae species (~30-31%). As for FA groups (Supplementary Table S1), n-3 PUFAs were the outstanding group in the families Gadidade (~42-44%), Percidae (42.5%), and Carangidae (37-47%), while the roes of Pleuronectidae also showed high percentages (43%). The remaining FA groups did not show a clear tendency among families and analyzed organs. This distribution of the various FAs in fish species was as expected. For example, fish from cold sea families accumulate PUFAs to maintain the fluidity of cell membranes, as occurs with the species of Gadidae, Osmeridae, and Percidae analyzed here. Conversely, OA-rich Cupleidae species occur in more temperate waters (Table 1). The concentrations of ARA, EPA, and DHA in fish fillets and roes are shown in Figure 1. The fillets of S. erythrophthalmus contain the highest amounts of ARA and DHA (1.82 and 2.49 g/100 g), which is a relevant fact due to the importance of both PUFAs for the development and performance of the central nervous system . Such high DHA percentages were expected since this species contains 17.94% DHA of total FAs by wet weight . However, DHA percentages for species reported here, e.g., S. erythrophthalmus (10.8%) and C. carpio (11.7%), were lower than those reported in the fresh state by (17.7 and 13.98%, respectively), suggesting that the dry-salting process can induce a reduction in this highly unsaturated PUFA due to oxidative processes. However, for inland fish C. carpio, the DHA percentage obtained in this work agrees with that reported for fish caught in the same season (11.0%) , and the same is true for G. morhua, for which the DHA percentage obtained in this work (23.1%) agrees with that reported previously . Therefore, the FA percentages of the various dry-salted fish, especially the percentages of highly unsaturated FAs, not only depend on the percentages inherent to fillets in the fresh state, which depend in turn on several factors such as diet and catch season, but also strongly depend on various factors inherent to the production process carried out in each case. S. erythrophthalmus contains DHA at amounts similar to dry-salted mackerel detailed by the USDA Nutrient Database, 2.96 g/100 g DHA, while the ARA proportion obtained here (7.9) was higher than that of mackerel (0.258 g/100 g). S. erythrophthalmus also provides a high amount of EPA, namely 0.97 g/100 g, which is approximately half of that reported for mackerel (1.62 g/100 g). Interestingly, the roes of this species contain both EPA and DHA (1.01 and 2.28 g/100 g), as well as good amounts of ARA (0.78 mg/100 g). This means that the consumption of just 14.4 g of fillets and 15.2 g of roes of S. erythrophthalmus provides the recommended daily intake of 500 mg of EPA + DHA. Dry-salted B. ballerus fillets also contain good amounts of ARA, EPA, and DHA (0.72, 0.99, and 2.25 mg/100 g), and therefore an intake of 15.4 g of such fillets provides the critical amount of 500 mg EPA + DHA for preventing CVD. Other samples providing 500 mg EPA + DHA al low intakes were the fillets of C. cultriventris (20.5 g), G. morhua (21.0 g), and P. quadrituberculatus (22.4 g) and the roes of C. carpio (23.0 g) and P. quadrituberculatus (23.1 g). In contrast, higher portions are needed to achieve 500 mg EPA + DHA when consuming the fillets of A. kessleri (100.9 g), B. sapa (112.3 g), and A. aspius (183.3 g). The fact that DHA is more abundant than EPA in most samples is relevant because of its critical role in the development and performance of the nervous and visual systems, as well as in the modulation of neuroinflammation . 4.3. Nutritional Quality Indices for Fatty Acids The nutritional quality indices for fatty acids are detailed in Supplementary Table S2. The PUFA/SFA ratio is one of the indices traditionally used to assess the nutritional quality of the lipid fraction of foods, and values higher than 0.4 are desirable for decreasing CVD risk . Most values in the current work fit within the range reported previously for other fish species . However, the relationship between SFA intake and an increase in the risk of CVD is unclear, and other nutritional indices have been recently used to assess the nutritional quality of the lipid fraction of foods, such as AI, TI, HH, and FLQ . The n-6/n-3 PUFA ratio is used for the nutritional assessment of lipids. Considering that n-6 and n-3 PUFAs are the metabolic precursors of proinflammatory and anti-inflammatory lipid mediators, respectively, an excessive intake of n-6 PUFAs could lead to inflammatory diseases. Therefore, the regular intake of foods having a low n-6/n-3 ratio helps to balance the proportion of both types of PUFAs and contributes to preventing or alleviating inflammatory diseases. A recent systematic review and meta-analysis study reported that a diet having a low n-6/n-3 PUFA ratio could significantly decrease the serum concentration of inflammatory markers such as tumor necrosis factor a (TNF-a) and interleukin 6 (IL-6) . The AI is the ratio between those SFAs considered proatherogenic and the unsaturated FAs (UFAs), i.e., MUFAs and PUFAs, which are considered antiatherogenic. AI values lower than 1.5 are desirable, and all analyzed samples fulfilled this criterion. AI values commonly reported for fish ranged between 0.21 and 1.41 . The TI estimates the thrombogenic potential of FAs contained in foods and is calculated as the ratio between SFAs (14:0, 16:0, and 18:0) and UFAs, although it gives more weight to n-3 PUFAs, which are recognized as cardiovascular health-promoting PUFAs. TI values are interpreted as the lower the value, the lower the thrombogenic risk, and values of TI < 1.15 are considered beneficial for cardiovascular health . All samples showed TI values lower than 0.60, which agrees with previous reports for fish (0.14-0.87) . The HH ratio is also used as a reference to estimate the potential of a given food to decrease the risk of CVD related to the metabolism of cholesterol and is considered more reliable than the PUFA/SFA ratio . The higher the HH ratio, the better the protective effect against CVD. Reported HH ratios for various fish species are in the range of 1.5-3.0 . Most HH values were within this range, highlighting the high value of B. tauricus (4.85). The FLQ index is used to show EPA + DHA proportions among total FAs in marine foods. Therefore, a high FLQ index means a protective effect against the risk of CVD. Some samples showed FLQ values higher than 25 (EPA + DHA > 25%), and therefore such samples exert a high CVD prevention effect. However, the consumption of salted-dried fishes must be moderated because of their high sodium content. According to nutritional lipid quality indices (PUFA/SFA >= 1.0, n-6/n-3 ratio <= 0.25, AI <= 0.40, TI <= 0.30, HH >= 2.5, and FLQ >= 25), some samples can be classified as excellent for decreasing the risk of CVD. These are the fillets of A. brama, G. morhua, P. fluviatilis, S. lucioperca, S. quinqueradiata, and P. quadrituberculatus, as well as the roes of P. quadrituberculatus. Two of these species are from marine waters (G. morhua and S. quinqueradiata), and four are from inland waters (A. brama, P. fluviatilis, S. lucioperca, and P. quadrituberculatus). The expected high sodium content of the samples analyzed leads to the selection of those fulfilling the recommended daily intake of 500 mg EPA + DHA through reduced consumption. In this regard, an amount less than 25 g of G. morhua and P. quadrituberculatus can provide this recommended intake. 4.4. Tocol and Squalene Contents Vitamin E is the generic name given to eight isoforms grouped into four T's and four T3's, which are mainly found in vegetable oils and nuts. These compounds are produced only by photosynthetic organisms and therefore are essential for humans. Vitamin E is a lipophilic antioxidant that may have a role in the prevention or amelioration of cardiovascular and aging-related diseases such as neurological disorders, having anticancer and anti-inflammatory properties . Among all isoforms of vitamin E, a-T is the most bioavailable one due to its high affinity with the hepatic a-T transfer protein (a-TPP). The bioavailability of T3's is lower than that of a-T, and among them, the a isoform is the one with the highest bioavailability. When the food matrix has a low level of a-T and high levels of a-T3 there is an increased absorption of the last compound . Previous reports on a-T for fillets showed similar amounts between fishes from marine (7.5-26.8 mg/g) and inland (6.6-26.3 mg/g) waters . a-T values for A. brama, G. morhua, and P. fluviatilis (0.19, 0.76, and 0.54 mg/100 g, respectively) obtained in the current study were lower than those reported for these fish in the fresh condition (2.91, 1.05, and 1.50 mg/100 g, respectively) , and this fact might be due to this vitamin being partially degraded in the dry-salting process. Another study on the T profiles of the fillets of marine and inland water fishes reported no differences for fishes depending on the water type . These authors reported 2.96 and 5.15 mg/100 g of total T's for M. barbatus and P. fluviatilis respectively, whereas in the current work, M. barbatus and P. fluviatilis contained 0.16 and 0.54 mg/100 g, thus reinforcing what was previously suggested regarding the dry-salting process decreasing tocol amounts in fishes. Lower amounts of a-T were detected in the fillets of M. barbatus (Fam. Mullidae) and O. mordax (Fam. Osmeridae). For dry-salted mackerel, the USDA Nutrient Database indicates 2.38 mg/100 g , which is a value located at the top of the data range obtained here. Overall, roes, especially those of fish belonging to families Cyprinidae and Pleuronectidae, seem to be a better source of T's than fillets. For the roes of three dry-salted fishes, 8.9 (Coregonus albula), 5.04 (Cuplea barengus membras), and 15.37 mg/100 g (Coregonus spp.) were reported , which are values in good agreement with the highest values found here. T3's have been much less explored than T's in fish. In the current work, it was only possible to quantify small amounts of a-T3 in two roes and g-T3 in two fillets. Such small amounts of T3's in fish have been previously reported . a-T is the only component of the unsaponifiable fraction for which an adequate intake (AdI) for the population has been provided, which was set at 11 and 13 mg/day for adult females and males . For calculations, the usual serving size for dry-salted fish consumption (150 g) was taken from . The consumption of fillets and roes of dry-salted fish provides very different amounts of VEA. For instance, consumption of ~176 and ~208 g (for males and females) of the roes of P. quadrituberculatus would be enough to fulfill the AdI for VEA, which is a little more than the serving size for this food type. As for fillets, the same would be achieved through the consumption of ~346 and ~409 g of P. quadrituberculatus, which is approximately twice the usual serving size of salted-dried fish. However, although VEA values of roes are on average higher than those of fillets, most species display values far from these figures; thus, other VEA-rich foods are needed to fulfill daily nutritional requirements. According to Regulations EC No. 1924/2006 and EU No. 1169/2011 (European Parliament and Council of the European Union, 2006, 2011) on nutrition and health claims made on foods, the nutrition claim "source of vitamin E" can only be applied to foods containing at least a significant amount of the vitamin under consideration, which corresponds to 15% of the AdI . For vitamin E, the requirements were set only for a-T at 12 mg per 100 g; therefore, the content of this vitamin should be set under 1.8 mg/100 g. The fillets of two species (S. erythrophthalmus and P. quadrituberculatus) and most roes (especially the ones of Cyprinidae and Pleuronectidae species) fulfill a-T requirements. Thus, the roes of dry-salted fishes could be considered as vitamin E sources in most cases according to EU regulations. Sq is a terpene that is naturally available in animal and vegetal sources and has cardioprotective, antioxidant, antibacterial, and anticarcinogenic properties . A previous work reported Sq amounts in raw muscle from freshwater fishes caught in the Czech Republic; among others, C. carpio, H. molitrix, A. brama, P. fluviatilis, S. erythrophthalmus, and A. aspius were analyzed . These authors reported Sq contents between 0.362 and 0.861 mg/100 g, whereas in the current study, values ranged from undetectable amounts to 0.39 mg/100 g for the same species. In a first approximation, higher Sq amounts could be expected in the dry-salted samples when compared to fresh samples. However, Sq is a molecule prone to oxidation due to its high degree of unsaturation, and the dry-salting process probably reduces the total amount detected in the fresh state in various fish species. The estimated daily intake of Sq in humans ranges between 30 and 400 mg . In this regard, the richest sources of Sq analyzed in this work were the fillets of C. cultriventris, S. quinqueradiata, and S. leptolepis, which provide 1.83, 1.54, and 1.26 mg/100 g of Sq. Consequently, it can be concluded that the Sq supply of dry-salted fish analyzed here is quite small. 4.5. Considerations about Salt Content of the Analyzed Fish Efforts have been made to reduce the sodium content of food products in the European Union via food reformulation in various industries. The World Health Organization (WHO) recommends <5 g/day of dietary salt intake (<2 g/day sodium) and provides an internationally accepted baseline for reformulation efforts. However, most Europeans continue to consume levels of salt above the recommended limit . In this regard, following criteria set by the Codex Alimentarius standard for salted Atlantic herring and salted sprat, according to the process carried out in the industry, the various fishes analyzed here can be classified as lightly salted fish, in which the salt content in the fish muscle in water phase is above 4 g/100 g and below or equal to 10 g salt/100 g . According to this work, a consumption of ~25 g of G. morhua and P. quadrituberculatus can provide the recommended daily intake of 500 mg EPA + DHA, and considering their salt content between 3 and 6 g/100 g, as previously explained, a total salt intake of ~0.7-1.5 g is expected through their consumption. This amount would not greatly conflict with the recommended daily sodium intake set by the WHO. 5. Conclusions Overall, the fillets and roes of dry-salted fish analyzed in this work are highlighted due to their high concentrations of conditionally essential PUFAs, i.e., ARA, EPA, and DHA. In most cases, DHA percentages were higher than EPA percentages, while some species constitute excellent sources of both PUFAs. Considering the expected high sodium content of the fish analyzed, those fulfilling the recommended daily intake of 500 mg of EPA + DHA through reduced consumption should be focused on for consumption. Interestingly, reduced consumption of most species could be enough to fulfil the recommended daily intake of long-chain n-6 and n-3 PUFAs. Moreover, the fillets and roes analyzed here contain high concentrations of a-T, which was the most prominent tocol found in all organs and species, and most samples display small amounts of Sq. Interestingly, the roes of most Cyprinidae species could be considered as sources of vitamin E. Future actions regarding this type of food should be aimed at designing dry-salting processes able to avoid the loss of bioactive compounds (T's, T3's, and Sq) in the resulting products. Supplementary Materials The following supporting information can be downloaded at: File S1: Supplementary File S1. Analytical Methodologies ; File S2: Supplementary Table S1. Fatty acid groups and ratios of dry-salted fish; File S3: Supplementary Table S2. Nutritional indices for fatty acids. Click here for additional data file. Author Contributions S.L.: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Validation, Visualization; T.C.-C.: Formal Analysis, Investigation, Methodology, Validation, Visualization, Writing--Original Draft; M.A.R.-C.: Data Curation, Formal Analysis, Investigation, Methodology, Software, Writing--Original Draft; S.P.L.: Investigation, Methodology, Validation; Z.I.: Investigation, Methodology, Software, Validation; O.D.: Investigation, Methodology, Software, Validation; V.K.: Investigation, Methodology, Software, Validation; I.T.-G.: Investigation, Methodology, Software, Validation; J.L.G.-G.: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing--Review and Editing. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Data is contained within the article or supplementary material. Conflicts of Interest The sponsors had no role in the design, execution, interpretation, or writing of the study. Abbreviations ANOVA: one-way analysis of variance; ALA: a-linolenic acid; ARA: arachidonic acid; CVD: cardiovascular disease; DHA: docosahexaenoic acid; DPA: docosapentaenoic acid; EPA: eicosapentaenoic acid; ETA: eicosatetraenoic acid; FA: fatty acid; FAME: FA methyl ester; FLQ: fish lipid quality; IA: index of atherogenicity; IT: index of thrombogenicity; HH: hypocholesterolemic/hypercholesterolemic ratio; HPLC: high-pressure liquid chromatography; LA: linoleic acid; MUFA: monounsaturated FA; OA: oleic acid; PA: palmitic acid; POA: palmitoleic acid; PUFA: polyunsaturated FA; SA: stearic acid; SDA: stearidonic acid; SFA: saturated FA; Sq: squalene; UFA: unsaturated FA; T3: tocotrienol; Tc: tocol; T: tocopherol; VA: vaccenic acid; VEA: vitamin E activity. Figure 1 Concentrations of ARA, EPA, and DHA in the fillets and roes of dry-salted fishes analyzed in this work. foods-12-01083-t001_Table 1 Table 1 Data on analyzed samples. Label Species Common Name Local Name Catching Area Catching Month Average Body Size Length, cm Weight, g Order Clupeiformes Family: Clupeidae 1 Alosa kessleri (Grimm, 1887) Caspian anadromous shad Sel'd-chernospinka, beshenka Volga-Caspian fishery basin, Northern fishery region, fishing areas of the Volga delta, Russian Federation June 30-40 500-960 2 Clupeonella cultriventris (Nordmann, 1840) Black and Caspian Sea sprat Tyul'ka Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation July 6-10 70-150 Order Cypriniformes Family Cyprinidae 3 Abramis brama (Linnaeus, 1758) Freshwater bream Lesh Volga-Caspian fishery basin, Northern fishery region, fishing areas of the Volga delta, Russian Federation May 30-40 500-650 4 Alburnus mento (Heckel, 1836) Bleak Chernomorsko-azovskaya shemaya Azovo-Chernomorsky fishery basin, Veselovsky reservoir, left tributary of the river Don, Russian Federation April 19-22 100-300 5 Aspius aspius (Linnaeus, 1758) Asp Zhereh, belest' Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation May 33-50 1200-1500 6 Ballerus ballerus (Abramis ballerus) (Linnaeus, 1758) Zope or blue bream Sinetc Volga-Caspian fishery basin, Northern fishery region, fishing areas of the Volga delta, Russian Federation June 24-28 300-400 7 Ballerus sapa (Pallas, 1814) White-eye bream Beloglazka, sopa Volga-Caspian fishery basin, Northern fishery region, Kuibyshev reservoir, Russian Federation May 21-27 150-250 8 Barbus tauricus (Kessler, 1877) Crimean barbel Usach krimskiy Azovo-Chernomorsky fishery basin, Kuban River, Russian Federation July 15-36 900-1100 9 Blicca bjoerkna (Linnaeus, 1758) White bream Gustera Volga-Caspian fishery basin, Northern fishery region, Kuibyshev reservoir, Russian Federation July 20-24 100-200 10 Carassius auratus (Linnaeus, 1758) Goldfish Zolotaya ribka, karas kitayskiy, srebryaniy karas Volga-Caspian fishery basin, Northern fishery region, Kazan Bay of the Kuibyshev Reservoir, Russian Federation May 16-24 450-650 11 Cyprinus carpio (Linnaeus, 1758) Common carp Sazan, karp obiknovenniy Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation June 30-50 350-600 12 Hypophthalmichthys molitrix (Valenciennes, 1844) Silver carp Tolstolobik Russian Far East fishery basin, lake Khanka/Xinkaihu river basin Amur, Russian Federation August 30-60 2000-5000 13 Pelecus cultratus (Linnaeus, 1758) Ziege, sichel, sabre carp, or sabrefish Chehon' Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation June 30-50 700-1100 14 Rutilus caspicus (Yakovlev, 1870) Caspian roach Vobla Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation May 22-35 500-800 15 Rutilus heckelii (Nordmann, 1840) Roach Taran, taranka Azovo-Chernomorsky fishery basin, Sea of Azov, Russian Federation April 15-25 400-1000 16 Scardinius erythrophthalmus (Linnaeus, 1758) Common rudd Krasnoperka, krasnoglazka Azovo-Chernomorsky fishery basin, Sea of Azov, Russian Federation May 20-25 700-1200 17 Vimba vimba (Linnaeus, 1758) Vimba bream Ribec obiknovenniy Volga-Caspian fishery basin, Southern fishery region, Caspian Sea, Russian Federation May 23-34 300-500 Order Gadiformes Family Gadidae 18 Gadus chalcogrammus (Pallas, 1814) Alaska pollock Mintay Russian Far East fishery basin, West Bering Sea zone, Bering Sea, Russian Federation January 50-70 2500-5000 19 Gadus morhua (Linnaeus, 1758) Atlantic cod Treska Northern fishery basin, Barents Sea, Russian Federation October 55-65 200-1100 Family Moridae 20 Laemonema longipes (Schmidt, 1938) Longfin codling Lemonema Russian Far East fishery basin, region of the South Kuril, The Russian Kuril Islands, Russian Federation August 49-53 500-850 Family Percidae 21 Perca fluviatilis (Linnaeus, 1758) European perch Okun' rechnoy Volga-Caspian fishery basin, Northern fishery region, Kuibyshev reservoir, Russian Federation November 22-30 300-500 Order Osmeriformes Family Osmeridae 22 Osmerus mordax (Mitchill, 1814) Rainbow smelt Koryshka Russian Far East fishery basin, Sea of Okhotsk zone, West Kamchatka Subzone, Shelikhov Bay, Russian Federation May 25-31 140-300 23 Sander lucioperca (Linnaeus, 1758) Pike-perch Sudak Volga-Caspian fishery basin, Northern fishery region, Kuibyshev reservoir, Russian Federation August 32-40 870-930 Order Perciformes Family Carangidae 24 Selaroides leptolepis (Cuvier, 1833) Yellowstripe scad Selar, zheltiy polosatik Gulf of Tonkin, Vietnam November 10-22 300-600 25 Seriola quinqueradiata (Temminck and Schlegel, 1845) Japanese amberjack Lakedra, zheltohvost Russian Far East fishery basin, Sea of Japan zone, The Peter the Great Gulf, Russian Federation August 800-1000 >9000 Family Mullidae 26 Mullus barbatus (Linnaeus, 1758) Red mullet Barabul'ka Azovo-Chernomorsky fishery basin, Kerch Strait, Russian Federation April 10-20 40-70 Order Pleuronectiformes Family Pleuronectidae 27 Pleuronectes quadrituberculatus (Pallas, 1814) Alaska plaice Kambala zheltobryuhaya (chetirehbugorchataya) Russian Far East fishery basin, Sea of Okhotsk zone, West Kamchatka Subzone, Russian Federation August 25-40 600-1100 Order Salmoniformes Family Salmonidae 28 Oncorhynchus gorbuscha (Walbaum, 1792) Pink salmon Gorbusha Russian Far East fishery basin, East Kamchatka zone, Storozh river, Russian Federation July 43-50 1000-1300 Order Siluriformes Family Siluridae 29 Parasilurus asotus (Linnaeus, 1758) Amur catfish Som Russian Far East fishery basin, lake Khanka/Xinkaihu river basin Amur, Russian Federation May 50-60 1000-1500 foods-12-01083-t002_Table 2 Table 2 Moisture, fatty acid profile, and total fatty acid content of sampled fishes and roes. Data are shown as mean value +- SD (n = 5). Species Fatty Acids (FA% of Total FAs) +,++ Moisture (g/100 g) Total FAs (g/100 g) 14:0 15:0 16:0 17:0 18:0 20:0 16:1n-7 18:1n-9 18:1n-7 20:1n-9 24:1n-9 18:2n-6 18:3n-3 18:4n-3 20:4n-6 20:4n-3 20:5n-3 22:5n-3 22:6n-3 Fillets Family Carangidae S. leptolepis 1.6 +- 0.3 efg n.d. 21.6 +- 1.1 lmnop 1.3 +- 0.2 fgh 14.2 +- 0.2 p n.d. 2.7 +- 0.3 b 7.7 +- 0.4 bc 2.1 +- 0.1 bcde n.d. 2.6 +- 0.2 j 1.9 +- 0.4 ij 0.9 +- 0.0 g n.d. 3.8 +- 0.1 ij 0.8 +- 0.0 h 6.0 +- 0.0 ij 4.3 +- 0.3 no 25.3 +- 0.9 m 16.3 +- 0.1 f 4.7 +- 0.2 h S. quinqueradiata 0.9 +- 0.1 ab 0.7 +- 0.0 ef 18.6 +- 0.3 efgh 1.4 +- 0.1 gh 13.9 +- 0.4 p n.d. 1.2 +- 0.1 a 9.2 +- 0.5 cde 1.9 +- 0.3 bcd n.d. n.d. n.d. n.d. n.d. 3.2 +- 0.3 gh n.d. 5.0 +- 0.4 fg 7.1 +- 0.4 s 34.4 +- 1.0 p 17.4 +- 0.1 h 3.7 +- 0. 1def Family Clupeidae A. kessleri 2.5 +- 0.3 jklm 0.6 +- 0.0 de 17.0 +- 0.5 de 0.8 +- 0.1 cde 3.5 +- 0.3 bc 1.6 +- 0.2 e 12.4 +- 0.7 q 31.3 +- 0.8 u 4.0 +- 0.1 jkl 1.3 +- 0.0 fgh n.d. a 1.1 +- 0.1 defg 0.8 +- 0.0 fg n.d. 1.9 +- 0.1 d n.d. 5.4 +- 0.2 ghi 3.1 +- 0.2 hij 7.3 +- 0.4 abc 14.0 +- 0.1 bc 3.9 +- 0.0 f C. cultriventris 5.5 +- 0.2 q 0.3 +- 0.0 b 17.3 +- 0.6 de 3.3 +- 0.2 j 4.2 +- 0.3 cd 0.2 +- 0.0 ab 16.2 +- 0.1 s 30.0 +- 1.5 u 2.3 +- 0.1 cde 0.2 +- 0.0 ab 0.6 +- 0.1 de 0.4 +- 0.2 ab 3.1 +- 0.0 l 1.0 +- 0.1 d 0.4 +- 0.0 a 0.2 +- 0.0 c 3.5 +- 0.0 cd 0.9 +- 0.1 b 8.9 +- 0.2 de 16.7 +- 0.2 g 19.7 +- 0.2 s Family Cyprinidae A. brama 2.1 +- 0.2 ghij 0.5 +- 0.0 cd 16.2 +- 0.4 cd 0.7 +- 0.0 bcd 4.8 +- 0.3 de 3.6 +- 0.1i 4.7 +- 0.2 d 24.8 +- 0.5 r 2.9 +- 0.0 gh 0.8 +- 0.0 d n.d. a 0.9 +- 0.1 cde 0.5 +- 0.0 cde n.d. 5.2 +- 0.2 l n.d. 9.1 +- 0.1 qr 4.6 +- 0.1 op 15.4 +- 0.3 h 12.7 +- 0.1 a 3.8 +- 0.0 ef A. mento 4.3 +- 0.1 op 0.9 +- 0.0 gh 20.9 +- 1.3 klmn 0.7 +- 0.0 bcd 4.5 +- 0.2 d n.d. 4.7 +- 0.1 d 16.9 +- 1.9 no 4.1 +- 0.7 klm 0.4 +- 0.0 bc 0.4 +- 0.0 bc 2.0 +- 0.0 j 4.7 +- 0.6 n 3.2 +- 0.2 i 1.5 +- 0.2 c 0.9 +- 0.0 i 6.4 +- 0.1 jkl 1.9 +- 0.2 de 10.4 +- 0.3 ef 14.6 +- 0.1 d 3.4 +- 0.2 cde A. aspius 2.7 +- 0.1 lm 0.9 +- 0.0 gh 22.4 +- 0.6 nopqr 0.8 +- 0.0 cde 6.5 +- 0.3 i 3.4 +- 0.3i 9.4 +- 0.3 n 28.3 +- 0.2 t 3.8 +- 0.2 ijk 1.1 +- 0.2 e 0.6 +- 0.0 de 0.8 +- 0.1 bcde 0.5 +- 0.0 cde n.d. 1.9 +- 0.1 d n.d. 1.7 +- 0.3 a 1.1 +- 0.3 b 7.1 +- 0.3 abc 12.5 +- 0.3 a 3.1 +- 0.1 c B. ballerus 1.6 +- 0.2 def 0.9 +- 0.0 gh 23.2 +- 1.4 pqrs n.d. 6.4 +- 0.4 hi n.d. 7.1 +- 0.0 k 14.5 +- 0.4 kl 3.5 +- 0.0 ij n.d. n.d. 1.4 +- 0.1 fghi 1.9 +- 0.2 i n.d. 6.4 +- 0.4 m 1.1 +- 0.0 k 8.8 +- 0.2 pq 2.3 +- 0.1 ef 19.9 +- 1.6 k 17.3 +- 0.2 h 11.3 +- 0.3 q B. bjoerkna 3.7 +- 0.3 n 0.9 +- 0.0 gh 17.8 +- 0.7 def 0.9 +- 0.1 def 9.6 +- 0.2 mn n.d. 8.7 +- 0.4 m 22.9 +- 0.4 q 3.9 +- 0.1 ijkl 4.7 +- 0.2 m n.d. 0.7 +- 0.0 bcd 0.5 +- 0.1 cde n.d. 3.4 +- 0.3 hi 0.6 +- 0.0 f 5.8 +- 0.4 hij 3.5 +- 0.1 jkl 7.8 +- 0.2 cd 17.2 +- 0.2 h 4.9 +- 0.2 hi B. sapa 1.3 +- 0.2 bcde 0.6 +- 0.1 de 23.1 +- 0.8 pqrs 0.6 +- 0.1 bc 10.2 +- 0.3 n n.d. 5.5 +- 0.6 efgh 11.9 +- 1.0 hi 2.9 +- 0.1 gh n.d. n.d. 1.1 +- 0.2 cdefg 0.7 +- 0.0 efg n.d. 9.3 +- 0.1 p n.d. 8.7 +- 0.4 pq 4.2 +- 0.2 no 17.5 +- 1.0 i 18.0 +- 0.1 i 1.7 +- 0.4 a B. tauricus 1.5 +- 0.3 def 0.7 +- 0.0 ef 10.3 +- 0.2 a 2.6 +- 0.1 i 4.9 +- 0.2 de 2.3 +- 0.2 g 7.1 +- 0.6 k 16.7 +- 0.3 n 3.4 +- 0.1 hi 1.5 +- 0.0 h n.d. 13.5 +- 0.2 n 1.9 +- 0.1 i n.d. 8.9 +- 0.2 o n.d. 2.8 +- 0.1 b 3.9 +- 0.1 lmn 6.1 +- 0.2 a 13.8 +- 0.2 b 5.9 +- 0.2 k C. auratus 1.1 +- 0.1 abcd 0.5 +- 0.0 cd 21.8 +- 1.3 lmnop 0.6 +- 0.1 bc 6.2 +- 0.5 fghi n.d. 8.0 +- 0.1 l 11.8 +- 0.5 ghi 2.5 +- 0.0 fg n.d. 0.6 +- 0.0 de 1.7 +- 0.1 ij 0.6 +- 0.1 def n.d. 7.7 +- 0.4 n 0.7 +- 0.1 g 6.8 +- 0.3 kl 2.5 +- 0.2 fg 18.2 +- 0.7 ij 15.1 +- 0.2 e 6.8 +- 0.2 l C. carpio 1.4 +- 0.0 cdef 2.1 +- 0.3 j 14.1 +- 0.6 b n.d. 15.0 +- 0.3 q 3.1 +- 0.4 h 6.3 +- 0.2 i 9.9 +- 0.6 def 4.1 +- 0.1 klm 1.2 +- 0.0 efg 3.2 +- 0.2 k 1.2 +- 0.0 efgh 2.0 +- 0.2 i n.d. 4.7 +- 0.1 k n.d. 7.7 +- 0.2 mno 5.7 +- 0.3 r 11.7 +- 0.2 fg 18.9 +- 0.2 k 7.9 +- 0.1 no H. molitrix 6.0 +- 0.5r 0.8 +- 0.1 fg 21.1 +- 1.1 klmno 0.8 +- 0.0 cde 7.5 +- 0.0 j 0.3 +- 0.1 b 8.9 +- 0.3 mn 26.6 +- 0.8 s 2.1 +- 0.2 bcde 1.2 +- 0.2 ef n.d. 3.7 +- 0.4 l 0.3 +- 0.0 bc 1.9 +- 0.1 f 2.6 +- 0.3 ef 0.4 +- 0.0 d 5.2 +- 0.1 gh 1.6 +- 0.1 cd 7.3 +- 0.7 abcd 19.3 +- 0.2 l 8.2 +- 0.4 o P. cultratus 1.8 +- 0.1 fghi 0.6 +- 0.0 de 24.1 +- 0.9 rs 0.7 +- 0.1 bcd 10.1 +- 1.5 mn 0.9 +- 0.1 cd 6.4 +- 0.1 ij 33.7 +- 1.2 v 2.2 +- 0.4 bcde 1.1 +- 0.1 ef 0.5 +- 0.0 cd 1.0 +- 0.1 cdef 0.5 +- 0.0 cde n.d. 2.7 +- 0.1 f n.d. 2.1 +- 0.2 a 1.8 +- 0.3 d 7.7 +- 0.4 bcd 16.3 +- 0.1 f 7.8 +- 0.1 no R. caspicus 1.6 +- 0.3 efg 0.6 +- 0.0 de 20.8 +- 1.0 jklmn n.d. 5.5 +- 0.2 ef n.d. 7.0 +- 0.3 jk 18.5 +- 0.7 p 3.7 +- 0.1 ijk 2.1 +- 0.1 ij n.d. 0.6 +- 0.0 bc n.d. a n.d. 4.0 +- 0.3 j n.d. 9.7 +- 0.4 r 3.7 +- 0.2 klm 19.1 +- 0.1jk 15.1 +- 0.2 e 6.9 +- 0.1 l R. heckelii 2.6 +- 0.2 klm 0.7 +- 0.1 ef 20.7 +- 1.4 jklmn 0.8 +- 0.0 cde 6.2 +- 0.1 ghi 1.1 +- 0.0 d 11.3 +- 0.4 p 23.4 +- 0.4 qr 5.7 +- 0.1 qr 2.3 +- 0.1 j n.d. 2.6 +- 0.2 k 1.4 +- 0.2 h n.d. 2.3 +- 0.2 de n.d. 7.1 +- 0.4 lm 2.6 +- 0.3 fgh 7.8 +- 0.2 cd 17.2 +- 0.2 h 5.7 +- 0.3 jk S. erythrophthalmus 1.7 +- 0.1 efgh n.d. 22.1 +- 0.8 mnopq 5.1 +- 0.3 k 4.4 +- 0.0 d n.d. 5.9 +- 0.0 ghi 13.6 +- 0.0 jk 4.1 +- 0.3 klm 1.3 +- 0.0 fgh n.d. 8.1 +- 0.4 m 5.8 +- 0.0 o n.d. 7.9 +- 0.4 n 1.0 +- 0.1 j 4.2 +- 0.0 e n.d. 10.8 +- 0.6 f 16.2 +- 0.2 f 23.1 +- 0.4 t V. vimba 1.7 +- 0.1 efgh 0.6 +- 0.0 de 19.5 +- 0.3 fghij 1.0 +- 0.1 efg 5.8 +- 0.2 fgh 0.8 +- 0.1 c 7.5 +- 0.1 kl 18.8 +- 1.2 p 4.6 +- 0.3 mno 1.3 +- 0.1 fgh n.d. 3.8 +- 0.1 l 4.0 +- 0.2 m n.d. 3.9 +- 0.2 j 0.7 +- 0.0 g 6.2 +- 0.6 jk 3.1 +- 0.2 hij 12.8 +- 0.2g 14.2 +- 0.2 c 9.9 +- 0.3 p Family Gadidae G. chalcogrammus 1.3 +- 0.2 bcde n.d. 24.7 +- 0.6 st n.d. 5.6 +- 0.1 fg n.d. 1.6 +- 0.2 a 10.4 +- 0.5 efg 2.5 +- 0.2 efg 4.5 +- 0.4 m 1.2 +- 0.3 h 3.0 +- 0.2 j 0.8 +- 0.0 fg n.d. 1.2 +- 0.1 bc 0.9 +- 0.1 i 8.3 +- 0.3 op 2.4 +- 0.2 f 31.5 +- 0.7 o 16.4 +- 0.1 f 3.3 +- 0.0 cde G. morhua 2.3 +- 0.2 ijkl n.d. 14.9 +- 0.1 bc n.d. 3.4 +- 0.2 b n.d. 7.0 +- 0.3 jk 16.0 +- 0.5 lmn 4.4 +- 0.3 lmno 4.6 +- 0.3 m 1.0 +- 0.1 g 1.0 +- 0.1 cdef n.d. a n.d. 1.1 +- 0.1 bc n.d. 17.9 +- 0.6 w 1.2 +- 0.2 bc 23.1 +- 0.7l 15.2 +- 0.2 e 5.8 +- 0.2 k Family Mullidae M. barbatus 3.0 +- 0.2 m 1.0 +- 0.1 h 17.9 +- 0.4 defg 1.5 +- 0.2 h 12.0 +- 0.4 o n.d. 2.4 +- 0.3 b 7.0 +- 0.2 ab 18.0 +- 0.6 u 0.6 +- 0.1 cd 1.6 +- 0.2 i 1.5 +- 0.1 ghi n.d. n.d. 4.8 +- 0.1 kl n.d. 3.4 +- 0.3 bc 4.1 +- 0.4 mn 19.8 +- 1.0 k 16.3 +- 0.3 f 5.2 +- 0.3 ij Family Osmeridae O. mordax 4.2 +- 0.2 nop 0.3 +- 0.1 b 20.3 +- 1.0 hijk 0.6 +- 0.0 bc 5.8 +- 0.4 fgh 0.7 +- 0.1 c 9.1 +- 0.5 mn 12.5 +- 0.6 ij 6.0 +- 0.3 rs 0.4 +- 0.0 bc 0.4 +- 0.0 bc 0.9 +- 0.1 cde 0.6 +- 0.0 def 1.1 +- 0.1 d 0.8 +- 0.0 ab n.d. 12.2 +- 0.5 s 1.0 +- 0.2 b 22.5 +- 0.4 l 17.3 +- 0.1 h 4.1 +- 0.2 fg S. lucioperca 1.4 +- 0.0 cdef 0.5 +- 0.0 cd 20.7 +- 1.9 jklmn 0.5 +- 0.1 b 6.0 +- 0.2 fghi 0.3 +- 0.0 b 5.1 +- 0.3 def 18.2 +- 0.3 op 1.9 +- 0.4 bc 0.2 +- 0.0 ab 0.7 +- 0.0 ef 1.0 +- 0.1 cdef 2.7 +- 0.3 k 0.2 +- 0.0 b 2.9 +- 0.3 fg 0.1 +- 0.0 b 5.1 +- 0.2 fg 1.0 +- 0.1 b 27.8 +- 0.9 n 14.6 +- 0.1 d 2.4 +- 0.1 b Family Percidae P. fluviatilis 1.0 +- 0.1 abc 1.3 +- 0.1 i 19.6 +- 0.4 ghij 1.0 +- 0.0 efg 8.8 +- 0.4 kl n.d. 1.5 +- 0.2 a 9.4 +- 0.4 def 1.7 +- 0.1 ab n.d. n.d. a n.d. a 0.2 +- 0.0 ab n.d. 4.8 +- 0.3 kl n.d. 3.8 +- 0.2 cde 7.9 +- 0.2 t 30.6 +- 0.7 o 17.3 +- 0.1 h 3.2 +- 0.1 cd Family Pleuronectidae P. quadrituberculatus 3.9 +- 0.1 no n.d 13.3 +- 0.5 b 1.4 +- 0.2 gh 2.3 +- 0.0 a n.d. 17.0 +- 0.2 t 12.7 +- 1.1 ij 6.5 +- 0.6 s 1.4 +- 0.0 gh n.d. 0.8 +- 0.0 bcde n.d. 2.1 +- 0.1 g 2.2 +- 0.0 de n.d. 21.3 +- 0.1 y 3.3 +- 0.2 ijk 6.2 +- 0.2 ab 20.3 +- 0.1 m 8.1 +- 0.1 o Family Salmonidae O. gorbuscha 4.5 +- 0.3 p 0.6 +- 0.0 de 10.3 +- 0.4 a n.d. 5.5 +- 0.3 efg 9.6 +- 0.4 j 3.4 +- 0.2 c 12.3 +- 0.4 hij 1.3 +- 0.2 a 4.1 +- 0.1 l 1.2 +- 0.1 h 1.4 +- 0.1 fghi 0.9 +- 0.0 g 3.0 +- 0.2 h 0.5 +- 0.0 a 1.3 +- 0.1 l 7.6 +- 0.5 mn 2.6 +- 0.3 fgh 14.8 +- 0.7 h 17.2 +- 0.1 h 7.2 +- 0.0 lm Family Siluridae P. asotus 2.1 +- 0.1 hijk 0.6 +- 0.0 de 18.0 +- 0.8 defg 0.7 +- 0.1 bcd 9.4 +- 0.0 lm 1.4 +- 0.1 e 10.1 +- 0.4 o 19.7 +- 1.2 p 5.4 +- 0.1 pq 2.0 +- 0.0 i 0.6 +- 0.0 de 3.5 +- 0.3 l 2.4 +- 0.2 j n.d. a 4.0 +- 0.2 j 0.5 +- 0.0 e 4.4 +- 0.3 ef 4.1 +- 0.3 mn 7.0 +- 0.6 abc 18.3 +- 0.1 j 7.2 +- 0.3 lm Roes Family Cyprinidae A . brama 1.6 +- 0.2 def 0.9 +- 0.0 gh 22.8 +- 0.3 opqr 0.9 +- 0.2 cde 5.5 +- 0.2 ef 1.9 +- 0.0 f 4.7 +- 0.1 d 16.5 +- 0.7 mn 3.8 +- 0.3 ijk 1.5 +- 0.0 h 0.7 +- 0.0 ef 0.9 +- 0.0 cde 1.9 +- 0.1 i n.d. 4.2 +- 0.1 j n.d. a 7.1 +- 0.2 lm 2.9 +- 0.0 ghi 19.8 +- 0.1 k 22.4 +- 0.2 n 2.9 +- 0.1 bc C. carpio 0.9 +- 0.0 ab 0.7 +- 0.1 ef 20.6 +- 0.5 jklm 0.7 +- 0.0 bcd 5.9 +- 0.1 fghi 0.8 +- 0.0 c 5.4 +- 0.3 efg 16.7 +- 0.3 n 4.2 +- 0.2klmn 0.6 +- 0.0 cd 0.8 +- 0.0 f 1.0 +- 0.1 cdef 0.4 +- 0.0 bcd n.d. 6.5 +- 0.2 m n.d. a 4.2 +- 0.1 e 5.5 +- 0.3 r 12.9 +- 0.8 g 24.4 +- 0.1 o 12.7 +- 0.5 r R. caspicus 0.9 +- 0.0 ab 0.9 +- 0.1 gh 23.8 +- 1.1 qrs 0.9 +- 0.0 def 5.7 +- 0.1 fgh n.d. 4.9 +- 0.3 de 10.8 +- 0.3 fgh 4.8 +- 0.1 o 0.7 +- 0.0 d n.d. a n.d. a 0.8 +- 0.0 fg n.d. 4.0 +- 0.2 j 0.4 +- 0.0 d 13.1 +- 0.7 t 3.9 +- 0.0 lmn 22.6 +- 6.9 l 25.1 +- 0.2 p 4.6 +- 0.2 gh S. erythrophthalmus 0.7 +- 0.1 a 0.4 +- 0.1 bc 26.2 +- 1.1 t 0.6 +- 0.0 bc 8.2 +- 0.2 jk n.d. 6.1 +- 0.2 hi 8.5 +- 0.2 cd 4.7 +- 0.3 no n.d. n.d. a 2.6 +- 0.0 k 2.3 +- 0.0 j n.d. 6.1 +- 0.2 m 0.9 +- 0.0 i 7.9 +- 0.2 no 2.7 +- 0.0 fgh 17.8 +- 0.4 ij 20.4 +- 0.1 m 12.8 +- 0.2 r Family Moridae L. longipes 1.1 +- 0.1 abcd 0.5 +- 0.1 cd 23.8 +- 0.4 qrs 0.7 +- 0.0 bcd 8.8 +- 0.3 kl n.d. 5.6 +- 0.1 fgh 18.6 +- 0.5 p 6.2 +- 0.1 rs 2.7 +- 0.2 k 0.4 +- 0.0 bc 1.6 +- 0.0 hij 0.9 +- 0.0 g n.d. 4.9 +- 0.4 kl 0.4 +- 0.0 d 4.1 +- 0.1 de 5.0 +- 0.3 pq 12.5 +- 0.5 g 25.4 +- 0.1 q 7.5 +- 0.1 mn Family Osmeridae O. mordax 5.8 +- 0.6 qr 0.4 +- 0.0 bc 19.1 +- 0.8 fghi 0.6 +- 0.1 bc 2.0 +- 0.2 a n.d. 13.7 +- 0.3 r 15.2 +- 0.7 lm 7.4 +- 0.4 t 0.3 +- 0.0 b 0.3 +- 0.0 b 1.0 +- 0.1 cdef 0.7 +- 0.0 efg 1.6 +- 0.2 e 1.0 +- 0.1 b 0.4 +- 0.0 d 16.4 +- 0.6u 1.1 +- 0.2 b 10.5 +- 0.2 f 25.6 +- 0.2 q 2.9 +- 0.1 bc Family Pleuronectidae P. quadrituberculatus 2.1 +- 0.1 hijk 0.5 +- 0.0 cd 17.9 +- 1.3 defg 1.2 +- 0.2 fgh 4.7 +- 0.1 d n.d. 4.7 +- 0.3 d 5.8 +- 0.0 a 4.9 +- 0.0 op 0.8 +- 0.0 d n.d. n.d. n.d. 0.4 +- 0.0 c 3.0 +- 0.2 fg n.d. 18.8 +- 0.3 x 5.3 +- 0.3 qr 18.5 +- 0.9 ijk 22.2 +- 0.2 n 5.8 +- 0.0 k + Other FAs of undetermined structure accounted for 100% of total FAs; ++ within each column, different superscript letters indicate significant differences among values (p < 0.05) according to one-way ANOVA followed by Duncan's test; n.d.: not detected (concentrations below LOQ, as reported in Supplementary File S1). foods-12-01083-t003_Table 3 Table 3 Tocol profiles and contents, VEA, and squalene (mg/100 g) of sampled fishes and roes. Data are shown as mean value +- SD (n = 5) a. a-T g-T a-T3 g-T3 Total Tocols VEA Squalene Fillets Family Carangidae S. leptolepis 0.39 +- 0.04 de n.d. n.d. n.d. 0.39 +- 0.0 de 0.39 +- 0.4 de 1.26 +- 0.04 p S. quinqueradiata 1.03 +- 0.08 k n.d. n.d. n.d. 1.03 +- 0.08 k 1.03 +- 00.8 k 1.54 +- 0.04 q Family Clupeidae A. kessleri 0.54 +- 0.01 g n.d. n.d. n.d. 0.54 +- 0.01 g 0.54 +- 0.0 g 0.31 +- 0.10 hi C. cultriventris 0.53 +- 0.06 fg n.d. n.d. n.d. 0.53 +- 0.6 fg 0.53 +- 0.6 fg 1.83 +- 0.09 r Family Cyprinidae A. brama 0.19 +- 0.02 a n.d. n.d. n.d. 0.19 +- 0.01 a 0.19 +- 0.02 a n.d. A. mento 0.54 +- 0.05 g n.d. n.d. n.d. 0.54 +- 0.05 gh 0.54 +- 0.05 gh n.d. A. aspius 0.41 +- 0.08 def n.d. n.d. n.d. 0.41 +- 0.08 def 0.41 +- 0.08 def 0.39 +- 0.02 jk B. ballerus 0.67 +- 0.4 hi 0.04 +- 0.0 a n.d. n.d. 0.71 +- 0.04 i 0.67 +- 0.4 hi 0.47 +- 0.02 l B. bjoerkna 1.68 +- 0.06 l n.d. n.d. n.d. 1.68 +- 0.06 l 1.68 +- 0.06 l n.d. B. sapa 0.18 +- 0.01 a n.d. n.d. n.d. 0.18 +- 0.01 a 0.18 +- 0.01 a 0.29 +- 0.03 gh B. tauricus 0.25 +- 0.04 bc 0.18 +- 0.08 b n.d. 0.05 +- 0.02 a 0.43 +- 0.08 de 0.27 +- 0.05 bc 0.96 +- 0.06 o C. auratus 0.55 +- 0.04 gh n.d. n.d. n.d. 0.55 +- 0.4 gh 0.55 +- 0.04 gh 0.19 +- 0.02 ef C. carpio 0.21 +- 0.02 b n.d. n.d. n.d. 0.21 +- 0.02 b 0.21 +- 0.02 b n.d. H. molitrix 0.36 +- 0.03 cd n.d. n.d. n.d. 0.36 +- 0.03 cd 0.36 +- 0.03 cd 0.28 +- 0.02 gh P. cultratus 0.25 +- 0.02 bc n.d. n.d. n.d. 0.25 +- 0.02 bc 0.25 +- 0.02 bc 0.18 +- 0.02 def R. caspicus 0.25 +- 0.02 bc n.d. n.d. n.d. 0.25 +- 0.02 bc 0.25 +- 0.02 bc n.d. R. heckelii 0.89 +- 0.05 j n.d. n.d. n.d. 0.89 +- 0.05 j 0.89 +- 0.5 j 0.31 +- 0.02 hi S. erythrophthalmus 2.77 +- 0.04 m n.d. n.d. 0.06 +- 0.02 a 2.83 +- 0.04 m 2.78 +- 0.04 m 0.24 +- 0.04 fg V. vimba 0.49 +- 0.08 efg n.d. n.d. n.d. 0.49 +- 0.08 efg 0.49 +- 0.08 efg 0.19 +- 0.01 ef Family Gadidae G. chalcogrammus 0.54 +- 0.01 g n.d. n.d. n.d. 0.54 +- 0.01 g 0.54 +- 0.01 g n.d. G. morhua 0.76 +- 0.08 i n.d. n.d. n.d. 0.76 +- 0.08 i 0.76 +- 0.08 i 0.34 +- 0.03 hij Family Mullidae M. barbatus 0.16 +- 0.02 a n.d. n.d. n.d 0.16 +- 0.02 a 0.16 +- 0.02 a n.d. Family Osmeridae O. mordax 0.16 +- 0.03 a n.d. n.d. n.d. 0.16 +- 0.03 a 0.16 +- 0.03 a 0.45 +- 0.05 kl S. lucioperca 0.19 +- 0.02 a n.d. n.d. n.d. 0.19 +- 0.02 a 0.19 +- 0.02 a n.d. Family Percidae P. fluviatilis 0.54 +- 0.02 g n.d. n.d. n.d. 0.54 +- 0.02 g 0.54 +- 0.02 g 0.13 +- 0.07 cde Family Pleuronectidae P. quadrituberculatus 3.14 +- 0.06 n 0.04 +- 0.01 a n.d. n.d. 3.18 +- 0.06 n 3.15 +- 0.06 n 0.54 +- 0.03 m Family Salmonidae O. gorbuscha 0.17 +- 0.01 a n.d. n.d. n.d. 0.17 +- 0.0 a 0.17 +- 0.01 a 0.11 +- 0.11 bcd Family Siluridae P. asotus 0.18 +- 0.01 a n.d. n.d. n.d. 0.18 +- 0.01 a 0.18 +- 0.01 a 0.58 +- 0.04 m Roes Family Cyprinidae A. brama 0.54 +- 0.19 p 0.19 +- 0.0 b 0.09 +- 0.2 a n.d. 0.56 +- 0.18 p 5.45 +- 0.19 p 0.54 +- 0.01 m C. carpio 3.08 +- 0.11 n n.d. n.d. n.d. 3.08 +- 0.1.1 n 3.08 +- 0.11 n 0.08 +- 0.01 bc R. caspicus 1.05 +- 0.09 k n.d. n.d. n.d. 1.05 +- 0.09 k 1.05 +- 0.09 k 0.70 +- 0.01 n S. erythrophthalmus 3.44 +- 0.08 o n.d. n.d. n.d. 3.44 +- 0.08 o 3.44 +- 0.08 o 0.05 +- 0.01 ab Family Moridae L. longipes 0.89 +- 0.01 j n.d. n.d. n.d. 0.89 +- 0.01 a 0.89 +- 0.01 j 0.59 +- 0.02 m Family Osmeridae O. mordax 0.90 +- 0.0 j n.d. n.d. n.d. 0.90 +- 0.0 a 0.90 +- 0.01 j 0.39 +- 0.00 jk Family Pleuronectidae P. quadrituberculatus 6.23 +- 0.09 q n.d. 0.08 +- 0.03 a n.d. 6.31 +- 0.09 q 6.26 +- 0.0 q 0.16 +- 0.09 de Within each column, different superscript letters indicate significant differences among values (p < 0.05) according to one-way ANOVA followed by Duncan's test; n.d.: not detected (concentrations below LOQ, as reported in Supplementary File S1). 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PMC10000465 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050726 healthcare-11-00726 Review Low-Intensity Blood Flow Restriction Exercises Modulate Pain Sensitivity in Healthy Adults: A Systematic Review Karanasios Stefanos 12* Lignos Ioannis 2 Kouvaras Kosmas 3 Moutzouri Maria 1 Gioftsos George 1 Attilio Parisi Academic Editor 1 Laboratory of Advanced Physiotherapy (LAdPhys), Physiotherapy Department, School of Health and Care Sciences, University of West Attica, 12243 Aigaleo, Greece 2 Physiotherapy Department, University of Patras, 20504 Patras, Greece 3 Hellenic Orthopedic Musculoskeletal Training (OMT) eDu, 11631 Athens, Greece * Correspondence: [email protected]; Tel.: +30-21-0623-1744 02 3 2023 3 2023 11 5 72610 2 2023 23 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Low-intensity exercise with blood flow restriction (LIE-BFR) has been proposed as an effective intervention to induce hypoalgesia in both healthy individuals and patients with knee pain. Nevertheless, there is no systematic review reporting the effect of this method on pain threshold. We aimed to evaluate the following: (i) the effect of LIE-BFR on pain threshold compared to other interventions in patients or healthy individuals; and (ii) how different types of applications may influence hypoalgesic response. We included randomized controlled trials assessing the effectiveness of LIE-BFR alone or as an additive intervention compared with controls or other interventions. Pain threshold was the outcome measure. Methodological quality was assessed using the PEDro score. Six studies with 189 healthy adults were included. Five studies were rated with 'moderate' and 'high' methodological quality. Due to substantial clinical heterogeneity, quantitative synthesis could not be performed. All studies used pressure pain thresholds (PPTs) to assess pain sensitivity. LIE-BFR resulted in significant increases in PPTs compared to conventional exercise at local and remote sites 5 min post-intervention. Higher-pressure BFR results in greater exercise-induced hypoalgesia compared to lower pressure, while exercise to failure produces a similar reduction in pain sensitivity with or without BFR. Based on our findings, LIE-BFR can be an effective intervention to increase pain threshold; however, the effect depends on the exercise methodology. Further research is necessary to investigate the effectiveness of this method in reducing pain sensitivity in patients with pain symptomatology. KAATSU training exercise occlusion training pain threshold hypoalgesia This research received no external funding. pmc1. Introduction Physical exercise is considered a beneficial intervention to reduce pain sensitivity in healthy individuals and patients with chronic pain conditions . Clinically important changes in pain reduction are reported during or after a single bout of exercise, a phenomenon widely known as exercise-induced hypoalgesia (EIH) . Based on experimental studies, the magnitude of EIH varies according to different factors, such as exercise parameters (i.e., type, dose, duration, and intensity), the type of noxious stimulus used for assessment (pressure, thermal, or electrical), the site of measurement (local or remote, muscle, or bone), and the timing of assessment (during or after exercise) . Evidence suggests that EIH increases when the intensity of exercise is higher and over the exercising limb compared to remote sites in individuals with or without chronic pain . During the last two decades, a new training method using low-intensity exercise with blood flow restriction (LIE-BFR) has been suggested to produce significant improvements in muscle strength, hypertrophy, and endurance in healthy individuals . LIE-BFR is used during voluntary resistance exercises (using 20-40% of one repetition maximum [RM]) or aerobic exercises (using 50% of heart rate or VO2max) . BFR training involves partial restriction of arterial blood flow, applying 40% to 80% of limb occlusive pressure using elastic or inflatable air cuffs of different diameters . When air cuffs are used, external pressure is achieved with pneumatic tourniquet systems or a manual pump system . Recently, the effectiveness of LIE-BFR has been investigated in various musculoskeletal pathologies, suggesting comparable improvements in muscle strength, hypertrophy, and function compared to traditional exercise programs . Hence, the method has been proposed as a useful alternative in rehabilitation when high-intensity conventional exercises are contraindicated or should be avoided . In addition to the positive effects on skeletal muscles, LIE-BFR has shown significant reductions in pain intensity in patients with knee problems or lateral elbow tendinopathy . As a result, it has been suggested that the BFR component may trigger a hypoalgesic response similar to high-load resistance exercise . Further investigations have demonstrated that LIE-BFR induces greater reductions in pressure pain thresholds compared to conventional training . These hypoalgesic responses were partially explained by endogenous opioid and endocannabinoid system pain-modulation mechanisms . However, other studies have supported that the addition of BFR to LIE did not provide an additional hypoalgesic response when the exercise was performed to failure . Additionally, based on a recent randomized controlled trial (RCT), elbow flexion LIE-BFR produced a similar reduction in pain perception compared to HIE only in the exercising limb . Despite growing research evidence in the current field, it remains unclear whether BFR exercises induce a significant hypoalgesic effect compared to other interventions or how different types of applications may influence the hypoalgesic response. Although several systematic reviews and meta-analyses have investigated the effect of BFR exercises on pain intensity , there are no reviews summarizing their effect on pain sensitivity. Pain intensity describes the magnitude of experienced pain measured using subjective scales, such as the visual analogue scale, numerical rating pain scale (0-10), and other instruments during activities . However, pain ratings may significantly vary due to pain sensitivity that includes complex interactions of ethnic, environmental, physical, psychosocial, and genetic factors . Measuring pain sensitivity remains a complex issue in research and the evaluation of pain thresholds is most commonly used in the laboratory setting . Pain threshold refers to the lowest intensity at which a given stimulus is perceived as painful, including a number of stimulus modalities, such as heat, cold, pressure, and chemical stimuli . Based on the available evidence, it remains unclear if BFR exercise causes a reduction in experimentally induced pain in healthy individuals or individuals with pain. Therefore, our study intends to evaluate the effect of LIE-BFR on pain threshold compared to other interventions in healthy individuals or patients with different pathologies. 2. Materials and Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines in the search strategy and reporting according to the PRISMA statement . 2.1. Search Strategy A systematic search from inception to January 2023 was conducted using the PICOS framework (P = participants; I = interventions; C = comparison; O = outcomes, S = study design) in PubMed, CINAHL, EMBASE, PEDro, ScienceDirect, Cochrane Library, Grey literature databases and clinical trial registries . Search strategy also included contact with experts in the field and manual search of the reference lists of the eligible studies. Systematic reviews were not included or assessed for quality but were examined for possible references. Moreover, internet sources were searched informally and discussions with colleagues for serendipitous discoveries were implemented to retrieve additional articles. The key terms included: "blood flow restriction" OR "ischemic training" OR "kaatsu" OR "occlusion training" OR "vascular occlusion" OR "vascular restriction" AND "pain threshold". The full search strategy is described in Supplementary File S1. 2.2. Eligibility Criteria 2.2.1. Participants Studies were considered eligible if they included healthy individuals or patients over 18 years old of any ethnicity and both sexes. Patients in eligible studies were required to present with local or widespread pain. 2.2.2. Intervention We included studies that used a standardized single bout of LIE (resistance or aerobic) incorporating restriction of blood flow alone or as an additive intervention to another type of intervention. To be considered low intensity, exercise intervention was required to include a resistance exercise using 20-40% of 1RM or an aerobic exercise at 50% of heart rate or VO2max . Studies that included HIE-BFR (>60% of 1RM; >50% of heart rate or VO2max) or did not adequately report the duration and intensity of exercise were excluded. 2.2.3. Comparison Groups Studies were considered eligible if they included a control condition, placebo, sham, or any other type of intervention. 2.2.4. Outcome Outcome measures included any type of assessment of the pain threshold without restriction on the type of stimulus, e.g., pressure pain threshold, cold pressor pain tolerance, heat pain intensity, etc. Studies that used other methods of pain rating, such as subjective scales or muscle pain during exercise, were excluded. 2.2.5. Study Design We included only RCTs (parallel-group, cross-over, or pilot study designs), or quasi-randomized clinical trials if RCTs were unavailable , published in English. We applied no restriction on publication year. Systematic reviews, case reports, reviews, cross-sectional studies, and cohort studies were excluded from the present intervention review . 2.3. Study Selection and Data Extraction After importing the search results into EndNote V.X9, two independent researchers (KK and IL) screened and selected the relevant studies using a two-step process . In the first stage, each title and/or abstract was independently evaluated by the two reviewers, aiming to minimize selection bias. In the second stage, the full text for each potentially eligible study was retrieved and evaluated against the criteria for eligibility by the same independent reviewers. Any disagreement was resolved by consulting a third reviewer (SK). In parallel, the same reviewers independently extracted data from eligible studies using a standardized data extraction form. For each study, we extracted the sample size, participants' demographic characteristics, intervention parameters, and outcomes of interest (pain threshold). In case information was missed or unclear, we communicated with the authors via email. Pain threshold is considered the minimum intensity of a stimulus (pressure, thermal, or electrical) at which an individual perceives or senses pain . The available eligible studies included only the use of an algometer; therefore, we extracted only pressure pain threshold (PPT) measurements in units of kg/cm2. 2.4. Methodological Quality Quality assessment was independently performed by two reviewers (IL and KK) using the PEDro rating scale . The PEDro scale contains 11 criteria scored by a dichotomous answer (Yes/No). The first criterion is related to the study eligibility criteria and is not computed in the total score while the rest are related to the study's internal validity and statistical reporting . Based on the number of criteria satisfied (0-10), we rated the methodological quality as 'poor' for a score of <=4, 'moderate' for a score of 5 or 6, and 'high quality' for a score of >=7 . Differences in the bias risk rating were discussed during a consensus meeting, and a third reviewer (GG) was involved if a consensus could not be reached. 2.5. Data Analysis, Summary and Synthesis of Findings Data from the included studies were assessed for heterogeneity in a two-stage procedure. Initially, we sub-grouped the studies according to the setting, population investigated, exercise interventions, and outcomes. Then, we assessed sub-group heterogeneity using participants' inclusion criteria, experimental and control intervention characteristics (type, equipment, volume, duration, etc.), and type of assessment (stimulus, timing, site of measurement, equipment, etc.). Because evidence for substantial clinical heterogeneity was demonstrated, we followed best-evidence synthesis to summarize the data. The risk of bias scores was considered when determining the evidence available. 3. Results After the removal of duplicates, 1249 publications were identified as relevant. Screening of titles and abstracts resulted in 11 records that were considered eligible for full-text assessment. Subsequently, five studies that did not meet the eligibility criteria were excluded. Six RCTs were finally included in the qualitative synthesis . Two of them included a parallel , while four studies followed a cross-over design . 3.1. Participants A total of 189 healthy participants were included with a mean age of 24.1 years. Of the participants, 44% were women and 56% were men, and the sample sizes ranged from 12 to 60 healthy individuals. All subjects were asked to maintain normal dietary habits during participation in the experimental protocols and refrain from caffeine, alcohol, and intense exercise the day before the experimental trials. All eligible studies described some common exclusion criteria, such as serious cardiovascular diseases, venous deficiency, lymphoedema, history of heart surgery, pulmonary embolism, cancer, or thrombosis . Table 1 shows the characteristics and main results of the included trials. 3.2. Interventions Five studies evaluated the effectiveness of LIE-BFR alone compared to other exercise interventions , while only two of them included a control group . One study compared the effectiveness of LIE-BFR between concentric and eccentric isokinetic contractions . Four of the eligible studies investigated the effect of dynamic resistance exercises with BFR and one investigated the effect of low-intensity aerobic exercise with BFR . Three studies used lower-limb exercises with BFR, including a leg press , knee extension , and cycling . Three studies included upper-limb exercises, of which two used a dynamic elbow flexion resistance exercise and one used an isometric handgrip contraction . Three of the eligible studies used a pneumatic tourniquet system to apply the BFR condition . The rest of the studies used inflatable air cuffs and determined arterial occlusive pressure with the help of a hand-held Doppler ultrasound . Three studies used LIE-BFR with low occlusive pressure (40-50% AOP) , two studies included exercise with both low and high occlusive pressures (40% and 80% AOP, respectively) , and one trial included only high occlusive pressure (80% AOP) . 3.3. Outcome Measures Pain sensitivity was assessed using pressure pain thresholds across all studies. Hand-held pressure algometers with a stimulation area of 1 cm diameter were used across all trials. Five studies included measurements at the exercising limb and remote sites and one trial investigated the effects of exercise with BFR only at a local site (biceps brachii muscle) . Five studies included a follow-up measurement 5 min after exercise trials, while two studies added a follow-up assessment 24 h post-intervention . One study examined PPTs throughout a 2-week isokinetic training program . 3.4. Methodological Quality Table 2 shows the results of the methodological assessment based on the PEDro criteria. Out of six studies, two were rated as 'high', one was rated as 'moderate' and one was rated as 'low quality'. Blinding therapists was not feasible in all trials due to the nature of the interventions. Four out of six studies did not ensure the blinding of the participants. One study included the blinding of outcome assessors. There was a low to no drop-out rate among the trials. 3.5. Effects on Pain Perception Five studies reported significant within-group increases in PPTs after a single bout of LIE-BFR at a short-term follow-up (5 min post-intervention) . Pain sensitivity was significantly decreased after a LIE-BFR using knee extension, leg press, isometric handgrip, or 20 min of cycling at both the exercising limb and distal areas of the body . Based on the results of a single RCT, an elbow flexion isotonic LIE-BFR resulted in a significant increase in PPTs only at the brachialis brachii muscle and without significant changes at remote areas . One RCT using elbow flexion isokinetic LIE-BFR reported no changes in PPTs at a local site of measurement throughout a 2-week training program . Significantly greater increases in PPTs at local and distal sites of the body were found in favor of lower-limb LIE-BFR with 80% arterial occlusive pressure (AOP) compared to LIE-BFR with 40% AOP, HIE, and LIE alone . Based on the same studies, LIE-BFR with 40% AOP had better results in reducing pain sensitivity than LIE alone . Notably, the differences did not remain statistically different at the 24 h follow-up. In contrast to previous findings, two cross-over trials found comparable decreases in PPTs between LIE-BFR and LIE, using either a resistance leg extension or a handgrip isometric exercise . A similar hypoalgesic effect between elbow flexion LIE-BFR and HIE was found only at the biceps brachii muscle immediately after intervention . No differences were found in PPTs between concentric LIE-BFR and eccentric LIE-BFR at the biceps brachii muscle using elbow flexion isokinetic exercises during a two-week training program . 4. Discussion We analyzed six randomized controlled trials that evaluated the effectiveness of LIE-BFR compared to other exercise interventions. A total of 189 healthy subjects with a mean age of 24.1 years were included. Most eligible trials showed a 'moderate' or 'high quality' rating; however, they included small sample sizes. One study that presented a 'poor' methodological quality required careful consideration regarding generalizability of the study results . There was substantial heterogeneity among eligible studies regarding the assessment sites and the type or volume of exercise interventions. Based on the authors' knowledge, this is the first review to summarize the research evidence on the effectiveness of LIE-BFR on pain thresholds. The main findings of our study suggest that various types of LIE-BFR can induce an immediate hypoalgesic effect both at local and remote sites in healthy adults. Although EIH was found to be higher after LIE-BFR compared to conventional exercise without BFR , the heightened hypoalgesic effect is possibly based on increased exercise volume due to the BFR component . No differences were found between eccentric and concentric LIE-BFR . It is well documented that HIE can been used as a pain-modulation intervention ; however, there is a critical question as to whether the use of an adjunct or alternative intervention such as LIE-BFR can also increase the benefits of exercise in pain conditions. Several systematic reviews have investigated the effects of LIE-BFR on pain intensity in patients with knee musculoskeletal pathologies ; however, their results remain inconclusive. For example, there is no evidence of further improvement in pain reduction for the use of LIE-BFR compared to conventional resistance training in patients with knee osteoarthritis . Another review suggested significantly less knee joint pain in favor of low-intensity BFR training compared to non-BFR training in patients after ACLR . These discrepancies may be attributed to the differences in the participants' characteristics, the severity of condition and the method of BFR training . In the same line, our findings suggest that the observed reductions in pain sensitivity depend on BFR methodology, such as (i) the degree of pressure (higher pressures result in greater EIH) ; (ii) the work volume (exercise to failure results in similar EIH with LIE alone) ; and (iii) the exercising limb (upper-limb exercise results in local and not remote reductions in PPTs) . In another area of research, the use of cooling systems during BFR training has shown significant results in terms of safety, blood pressure changes, and point-of-care blood products (platelet-rich plasma), suggesting their potential use in cardiac rehab . Nevertheless, evidence of the effect of such factors during BFR training on pain sensitivity is lacking and requires further investigation. Although the effectiveness of LIE-BFR in pain reduction in patients with musculoskeletal pathologies remains unclear, a promising aspect of using the current method in a clinical setting is the potential to allow more intense exercise with less pain, especially when targeting within-session pain modulation . Several underlying mechanisms by which LIE-BFR may induce greater EIH have been proposed . These mechanisms involve central descending pain control pathways ; conditioned pain modulation (CPM) ; motor control units recruitment ; stimulation of baroreceptors ; metabolites production and psychological contributing factors . Based on the results of two trials, the activation of systemic mechanisms, including CPM and stimulation of baroreceptors, was confirmed as the changes in PPTs were mediated due to the level of discomfort, increase in blood pressure, and elevated concentration of biomarkers (beta-endorphins) . However, other RCTs have reported that EIH following different types of LIE-BFR was not mediated by similar factors . Hence, the stimulation of Group III and IV afferents and high-threshold motor unit recruitment were considered the most possible mechanisms of action . The various BFR exercise methodologies may potentially activate different local and systemic hypoalgesic mechanisms. Limitations and Future Research The present systematic review should be interpreted in light of its limitations. First, restricting our inclusion criteria to only English-language publications may have increased the risk of missing critical information published in other languages. Second, there was a small number of well-designed studies in the current field that were also under-populated. As a result, their external validity could be compromised. Additionally, due to the substantial clinical heterogeneity of intervention protocols, a meta-analysis was not feasible. Specifically, each study included a different type of exercise (i.e., leg press, knee extension, isometric handgrip, cycling, isotonic elbow flexion, and isokinetic elbow flexion), while substantial variability was found in the workload (i.e., 75 reps or exercise to failure). Although we intended to analyze both healthy and unhealthy individuals, there were no studies evaluating the effect of LIE-BFR on pain perception in patients with pain. Therefore, our results cannot be generalized to various pathological populations with acute or chronic pain symptomatology. Future research investigations focusing on the possible immediate hypoalgesic effects of LIE-BFR in individuals presenting with various pain conditions seem necessary. Considering that various underlying pain-modulation mechanisms have been proposed to be activated with LIE-BFR , more RCTs are needed to examine which exercise properties are mostly involved. 5. Conclusions Based on the available data, LIE-BFR can be an effective intervention to reduce pain sensitivity at local and remote sites in healthy adults, suggesting segmental and central underlying mechanisms. However, the magnitude of the hypoalgesic effect varies depending on the exercise parameters that potentially activate different local and systemic pain-modulation mechanisms. Specifically, using LIE-BFR at the lower-limb with higher occlusive pressure (80% AOP) can induce greater hypoalgesia compared to lower pressures (40% BFR) or exercise alone. Additionally, the increased hypoalgesic effect seems to be based on the volume of exercise (exercise to failure) and the exercising limb. Further research is required to investigate the effectiveness of LIE-BFR in reducing the pain threshold in individuals with various pathological conditions. Supplementary Materials The following supporting information can be downloaded at: File S1: Search Strategy. Click here for additional data file. Author Contributions Conceptualization, S.K.; methodology, S.K.; validation, S.K. and G.G.; formal analysis, S.K.; investigation, I.L. and K.K., resources, I.L. and K.K.; data curation, I.L. and K.K.; writing original draft preparation, S.K.; writing--review and editing S.K. and M.M.; supervision, G.G.; project administration, S.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 PRISMA study selection flow chart. PRISMA: preferred reporting items for systematic reviews and meta-analyses. healthcare-11-00726-t001_Table 1 Table 1 Included studies, demographics and results. Study (Year) Design Total Sample Size N (Mean Age +- SD, Sex) Interventions Equipment Follow-Up Outcome Measures Results Hill et al. (2019) Parallel design 25 healthy individuals (25 women) Ecc LIE-BFR (n = 12; 21.7 years +- 1.0) Con LIE-BFR (n = 13; 22.0 years +- 1.6) Unilateral isokinetic elbow flexion (120deg s) (1) Ecc LIE-BFR(40% AOP) at 30% of eccentric peak torque (30-15-15-15 reps) (2) Con LIE-BFR(40% AOP) at 30% of concentric peak torque (30-15-15-15 reps) Inflatable cuffs with a manual pump (KAATSU Master, Sato Sports Plaza, Tokyo, Japan) Between 7 testing days PPTs at the biceps brachii muscle There was no significant group x testing day interaction (p = 0.682) Hughes et al. (2020) Cross-over design 12 healthy individuals (29 +- 6 years; 10 men and 2 women) Unilateral leg press (1) LIE using at 30% 1RM (30-15-15-15 reps) (2) LIE-BFR(40% AOP) at 30% 1RM (30-15-15-15 reps) (3) LIE-BFR(80% AOP) at 30% 1RM (30-15-15-15 reps) (4) HIE at 70% 1RM (4 sets x 10 reps) Personalized Tourniquet system (Delfi Medical Inc, Vancouver, BC, Canada) 5 min post-exercise 24 h post-exercise PPTs at the dominant and nondominant quadriceps, dominant biceps brachii, nondominant upper trapezius muscles LIE-BFR (80% AOP) showed significantly higher PPTs compared to all trials (p < 0.05) at all measurements sites 5 min post-exercise LIE-BFR (40% AOP) showed significantly higher PPT compared to LIE (p < 0.05) at all measurements sites 5 min post-exercise HIE showed higher PPTs compared to LIE (p < 0.05) at all measurements sites 5 min post-exercise Hughes et al. (2021) Cross-over design 12 healthy individuals (27 +- 6 years; 12 men) Static bicycle X 20 min (1) LIE (2) LIE-BFR(40% AOP) at 40% VO2max (3) LIE-BFR(80% AOP) at 40% VO2max (4) HIE at 70% VO2max Personalized tourniquet system (Delfi Medical Inc, Vancouver, BC, Canada) 5 min post-exercise 24 h post-exercise PPTs at the dominant and nondominant quadriceps, dominant biceps brachii, nondominant upper trapezius muscles PPTs were significantly increased following BFR (40% AOP) and BFR (80% AOP) compared with LIE (p < 0.05). BFR (80% AOP) presented higher increase in PPTs compared to BFR (40% AOP) (p < 0.05). BFR (80% AOP) and HI-AE presented increased PPTs in remote areas of the body. Karanasios et al. (2022) Parallel design 40 healthy individuals (26.6 years +- 6.8; 17 women and 23 men) Elbow flexion with dumbbells (1) LIE-BFR(40% AOP) at 30% RM (30-15-15-15 reps) (2) HIE at 70% RM (4 sets x 10 reps) Personalized tourniquet system (Mad-Up Pro, France) 5 min post-exercise PPTs at the dominant and nondominant quadriceps, biceps brachii and upper trapezius muscles Non-significant between-group changes in PPTs at all measurement sites Statistically significant reductions between post-exercise in LIE-BFR and HIE at dominant biceps brachii Song et al. (2022) Cross-over design 60 healthy individuals (21.8 years +- 3.2; 21 men, 39 women) Isometric handgrip contraction (1) LIE-BFR (50% AOP) at 30% of max strength (4 sets x 2 min contraction) (2) LIE at 30% of max strength (4 sets x 2 min contraction) (3) control Inflatable cuffs with a manual pump (E20, Hokanson Inc., Bellevue, WA, USA) 5 min post-exercise PPTs at the dominant forearm and ipsilateral tibialis anterior PPTs increased similarly in both exercise groups compared to control at a local and non-local site. Non-significant differences between exercise conditions. Song et al. (2022) Cross-over design 40 healthy individuals (23.7 years +- 4.3; 18 men, 22 women) Unilateral knee extension (1) LIE-BFR (80% AOP) at 30% RM (to failure) (2) LIE at 70% RM (to failure) (3) control Inflatable cuffs with a manual pump (E20, Hokanson Inc., Bellevue, WA, USA) 5 min post-exercise PPTs at the dominant forearm and ipsilateral tibialis anterior Both exercise conditions presented greater changes in PPTs compared to control (p > 0.05) Non-significant differences between exercise conditions Abbreviations: LIE-BFR, low-intensity blood flow restriction; USA, United States of America; PPTs, pressure pain thresholds, HIE, high-intensity exercise; AOP, arterial occlusive pressure; LI-AE, low-intensity aerobic exercise; HI-AE, high-intensity aerobic exercise; Ecc, eccentric; Con, concentric; RM, repetition maximum; 24 h, 24 hours; reps, repetitions. healthcare-11-00726-t002_Table 2 Table 2 Methodological quality assessment using the PEDro scale. 1 2 3 4 5 6 7 8 9 10 11 Total Score Hill et al. (2019) + + - - - - - - - + + 4/10 Hughes et al. (2020) + + + + - - - + + + + 7/10 Hughes et al. (2021) + + + + - - - + + + + 7/10 Karanasios et al. (2022) + + + + + - + + + + + 9/10 Song et al. (2022) + + + - - - - + + + + 6/10 Song et al. (2022) + + + + + - - + + + + 8/10 1. Eligibility criteria were specified; 2. subjects were randomly allocated to groups (in a cross-over study, subjects were randomly allocated an order in which treatments were received); 3. allocation was concealed; 4. the groups were similar at baseline regarding the most important prognostic indicators; 5. there was blinding of all subjects; 6. there was blinding of all therapists who administered the therapy; 7. there was blinding of all assessors who measured at least one key outcome; 8. measures of at least one key outcome were obtained from more than 85% of the subjects initially allocated to groups; 9. all subjects for whom outcome measures were available received the treatment or control condition as allocated or, where this was not the case, data for at least one key outcome were analyzed by "intention to treat"; 10. the results of between-group statistical comparisons are reported for at least one key outcome; 11. the study provides both point measures and measures of variability for at least one key outcome; Note: The first item relates to external validity and the remaining 10 items are used to calculate the total score, which ranges from 0 to 10. + Yes - No. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000466 | Lactic acidosis, a hallmark of solid tumour microenvironment, originates from lactate hyperproduction and its co-secretion with protons by cancer cells displaying the Warburg effect. Long considered a side effect of cancer metabolism, lactic acidosis is now known to play a major role in tumour physiology, aggressiveness and treatment efficiency. Growing evidence shows that it promotes cancer cell resistance to glucose deprivation, a common feature of tumours. Here we review the current understanding of how extracellular lactate and acidosis, acting as a combination of enzymatic inhibitors, signal, and nutrient, switch cancer cell metabolism from the Warburg effect to an oxidative metabolic phenotype, which allows cancer cells to withstand glucose deprivation, and makes lactic acidosis a promising anticancer target. We also discuss how the evidence about lactic acidosis' effect could be integrated in the understanding of the whole-tumour metabolism and what perspectives it opens up for future research. lactic acidosis glucose deprivation tumour heterogeneity metabolic symbiosis Warburg effect ITMO Cancer of AviesanFinancial support from ITMO Cancer of Aviesan within the framework of the 2021-2030 Cancer Control Strategy, on funds administered by Inserm. pmc1. Introduction Lactic acidosis is a hallmark of the tumour microenvironment, one that has been shown to promote cancer resistance to chemotherapy . It results from the intensive secretion of lactate and protons in the presence of glucose by cells displaying the Warburg effect, a characteristic anomaly of proliferating, and, particularly, cancer cells. Cells harbouring the Warburg effect perform high-rate glycolysis, lactic fermentation, and co-excretion of lactate and protons . This enables them to proliferate at a high rate in the presence of glucose, which they consume avidly. However, the rapid consumption of glucose leads to its exhaustion, and an energetic dead-end and paradox. Interestingly, lactic acidosis has been shown to help cancer cells withstand glucose deprivation . In media conditioned with high lactate concentration and acidity, cancer cell lines avoid apoptosis and survive 10 times longer in the absence of glucose. Further studies have demonstrated that cancer cells resist glucose starvation by reprogramming their metabolism . In this review, we focus on the essential literature addressing how lactic acidosis affects energy metabolism and preserves homeostasis in glucose-deprived cancer cells, and what therapeutic prospects it opens up. We then discuss how this effect at the cellular scale could help understand the metabolism of whole tumours. 2. Defining the Experimental Conditions of the Presented Studies In this work, we review a series of studies relevant to address how lactic acidosis helps cells resist glucose deficiency. These studies are performed in varying conditions (Table 1). In order to clarify the various experimental conditions, we emphasise the following definitions . "Lactosis" refers to an in vitro condition in which extracellular lactate concentration exceeds 15 mM. It must be noted that most presented studies were performed with culture media containing 10% foetal bovine serum, which brings ~1.5 mM lactate to the medium . At pH 6.7, >15 mM added lactate helps cancer cells resist glucose deprivation . "Acidosis" refers to an extracellular pH of 5.8-6.7. Under pH 6.7 normal cells suffer from acidosis, and tumour pH can drop down to 5.8 . "Lactic acidosis" refers to the combination of both lactosis and acidosis. Lactic acidosis and acidosis are frequently encountered in tumours . Both originate from the co-secretion of lactate and protons, and acidosis is also caused by the mitochondrial production of CO2 and its dissociation into H+ . Lactosis is a condition virtually absent in vivo, but one that can be achieved easily in vitro to study the effect of lactate independently from acidification by adding buffered sodium lactate to the medium. "Glucose deprivation" or "depletion" refers to conditions where glucose is scarce, but not necessarily absent from the milieu. Intratumoral glucose concentration can drop to 0.1-0.4 mM, while its level in healthy tissues is ~1 mM . In vitro studies recreate glucose deprivation with culture media that contain, initially, up to 3 mM glucose, the amount that cancer cells typically deplete in one day . cancers-15-01417-t001_Table 1 Table 1 The presented studies addressing lactic acidosis' impact on cell energy metabolism are performed under various conditions. For each reference, the tested cell line or cancer type and medium conditions (glucose concentration, lactate concentration, and pH) are specified. When unspecified, the pH value was assumed to equal 7.4. Reference Glucose Concentration (mM) Lactate Concentration (mM) pH Cell Lines or Tumour Origin 3 20 6.7 4T1, Bcap37, RKO, SGC7901 Unspecified 25 6 to 6.7 HMEC, DU145, SiHa, WiDr 10 10 6.5 MCF-7, MDA-MB-468, MDA-MB-231, SkBr3 5 and 25 5 to 30 6.7 U251 and glioblastoma Unspecified 10 or 20 7.4 A549, H1299 10 5 to 30 7.4 A549, H1299 Unspecified 10 or 30 7.4 SiHa and mouse xenograft 6 25 6.5 4T1, Bcap37, HeLa, A549 Unspecified 4 to 40 5 to 8 MCF7, T47D Unspecified 5 or 10 7.4 A549, H1299, BEAS-2B 10 3 to 40 6.2 A549, A427, MCF7, MRC5 Unspecified 0 6.5 A549, H1299, MRC5 5 10 7.4 SiHa, HeLa 10 10 or 25 6.7 MCF-7, ZR-75-1, T47D, MDA-MB-231, MDA-MB-157 5.6 10 or 20 6.7 LS174T, HCT116, MCT4 Unspecified 20 7.4 MCF7 Unspecified 10 7.4 MDA-MB-231 0 28 6.2 A549, A427 Unspecified 20 7.4 U87-MG, A172, U251 Unspecified 20 7.4 92.1 0 10 7.4 MDA436 and mouse xenograft 10 2 to 20 7.4 Human myeloid cell lines 0.175 4 7.4 glioma stem cells 2.5 or 25 10 7.4 Colo205, Ls174T, Mosers, HT29 1 to 2.5 25 7.4 MCF-7 Unspecified 20 7.4 Huh-7, Hep3B 0 20 6.8 A549 0 20 6.7 4T1, HeLa, NCI-H460 Unspecified 0 6.5 PANC-1, SW1990 Unspecified 12 6.8 PaTu-8902, HeLa, HepG2, HDF 3. Lactic Acidosis Seen by Cancer Research: A Brief History In the 2000s, cancer research took a renewed interest in the Warburg effect, a hallmark of cancer discovered a century ago . As a consequence, views on lactic acidosis changed drastically. Acidosis had been known to promote tumour aggressiveness by exerting a selective pressure. Some cancer cells had been shown to survive acidosis by maintaining an alkaline intracellular pH, while other cells--cancerous or healthy--underwent hydrolysis and death . The proliferation of those selected cells, which are more resistant to unfavourable environments, had been known to increase tumour malignancy . As for lactate, it had been considered more of a by-product of glycolysis until the 1980s, when its use as a nutrient in non-cancerous tissues was discovered . The role of extracellular lactate in cancer was investigated only later, in the 2000s , when it was found to correlate with tumour malignancy . Two explanations for this were initially proposed. First, lactate promotes relaxation of the tissue surrounding the tumour, which would make room for its development and metastasis . Second, lactate makes the cellular environment hostile, as does acidosis , which promotes angiogenesis . The metabolic importance of extracellular lactate and lactic acidosis was first evidenced in 2008. Lactic acidosis was shown to alter the expression of metabolism genes and, more importantly, lactate was proven to be, per se, a key source of energy for cancer cells . In 2009, the term "reverse Warburg effect" was first used to describe cancer cells not showing the Warburg effect, but instead inducing it in neighbouring stromal fibroblasts and consuming the lactate produced by them . These discoveries reappraised the paradigm of the Warburg effect, showing that it wasn't compulsory in cancer since lactate could be metabolised rather than only produced. Following these works, in 2012, Wu et al., demonstrated that lactic acidosis allows cells to avoid glucose starvation . Lactic acidosis rescues glucose-deprived cancer cells, but importantly, acidosis or lactosis alone have much more limited effects. After this pioneering work, lactic acidosis was further shown to reprogram cell metabolism . Nowadays, extracellular lactate and acidosis are viewed as central players in cancer cell metabolism . 4. Lactic Acidosis' Effect on Energy Metabolism Lactic acidosis was shown to impact numerous aspects of energy metabolism. We focus here on nutrient import, glycolysis, the tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OxPhos), and pathways generating reduced coenzymes . 4.1. Lactic Acidosis and Exchanges at the Plasma Membrane In glucose deprivation, the capacity of cancer cells to uptake and metabolise alternative nutrients is key to their survival . Extracellular acidosis and lactosis were shown to increase such capacity. 4.1.1. Acidosis Sustains the Activity of Proton-Nutrient Symporters Extracellular acidosis has a direct impact on exchanges at the plasma membrane . In healthy tissues, protons are more concentrated inside the cell than outside. In tumours, the contrary is true . Extracellular acidosis inverts the transmembrane proton gradient in tumour cells, which may positively impact proton-nutrient symports. Of interest, lactate is imported in cancer cells via the monocarboxylate transporters (MCTs) . Since MCTs co-transport lactate with a proton, lactate import should be sensitive to the proton gradient and facilitated under acidosis. This mechanism is expected to explain why cancer cells respond differently to lactosis and lactic acidosis , since a rise in extracellular lactate only increases intracellular lactate levels in acidic conditions . The co-transport of extracellular lactate and protons probably underlies the synergy of their effects on intracellular metabolism . Of note, protons are also co-imported with several other nutrients, such as Fe2+, folates, amino acids and peptides. Brown & Ganapathy suggested that acidosis may affect their uptake , but this hypothesis remains to be confirmed . 4.1.2. Lactate and Acidosis Indirectly Enhance Nutrient Uptake Extracellular lactic acidosis indirectly promotes the uptake of several nutrients . The import of lactate itself is increased in lactic acidosis, in part due to MCT1 overexpression , which is a response to an extracellular lactate signal that is potentiated by extracellular acidity . Extracellular lactate induces MCT1 and MCT4 via the G-protein-coupled receptor 81 (GPR81) transduction pathway . In acidosis, extracellular lactate can also induce GPR81 expression . Extracellular lactate signal enhancing MCT-mediated lactate import is necessary to cancer cell survival in absence of glucose, glutamine and pyruvate . This supports the idea that 'lactate induces its own metabolism', which doesn't exclude other regulations of MCT expression . Glutamine uptake is increased by extracellular lactate or acidosis, as both conditions increase the expression of the glutamine transporter ASCT2 (alanine, serine and cysteine transporter 2) . Fatty acid uptake is enhanced by acidosis , and folate import is intensified by 10 mM extracellular lactic acid . Finally, and importantly, lactic acidosis seems to minimise glucose uptake, but not in all cell lines and cancers. Lactic acidosis decreases glucose uptake in various cell lines , as lactate in lung cancer cell lines . On the opposite, 10 mM lactate has no effect on glucose uptake in the T47D breast cancer cell line . The expression of the glucose transporters GLUT1 and GLUT4 are decreased by 2 mM lactate and acidosis in lung and breast cancer cell lines , and by acidosis in cervix, pharynx and colon cancer cell lines but not in lung cancer cell lines . 4.1.3. Lactic Acidosis and pH Homeostasis Cell exposure to lactic acidosis is associated with a drop in intracellular pH from 7.3 to ~6.9 . Behind this acidification, several probable effects may be discerned. On the one hand, as discussed earlier, acidosis enhances proton-nutrient co-import, which could contribute to cellular acidification. On the other hand, lactate as a signal can mitigate the drop in pH by favouring alkalinization. A level of 10 mM extracellular lactate induces Carbonic Anhydrase IX (CA IX) , a transmembrane enzyme supporting proton export and a key regulator of cell pH . 4.2. Lactic Acidosis, Glycolysis, and Lactic Fermentation Unlike cells showing the Warburg effect, in which glycolysis and lactate dehydrogenase (LDH)-catalysed lactic fermentation are known to be hyperactive, cells exposed to lactic acidosis show a reduction in these pathways' activity. In glucose abundance, acidosis and lactic acidosis lower glucose consumption and lactate secretion , which indicates that glycolysis and lactic fermentation are downregulated. More interestingly, lactic acidosis decreases cancer cell dependency on glucose catabolism . Thus, in glucose sufficiency, lactic acidosis minimises glucose catabolism activity and its importance in cell survival . Glycolysis and lactic fermentation are likely downregulated at the level of both gene expression and enzyme activity. The expression of glycolysis enzymes is reduced by lactic acidosis in breast cancer cell lines , and by extracellular lactate in lung cancer cell lines , but it is maintained by extracellular lactate in breast cancer cell lines . The activity of glycolysis enzymes, especially the rate-limiting hexokinase and phosphofructokinase , is directly decreased by intracellular acidification . In line, intracellular acidification has been predicted in silico to hinder the Warburg effect . Intracellular lactate accumulation, in parallel, directly inhibits lactic fermentation . The interconversion of lactate and pyruvate through LDH follows the mass action law, therefore a rise in lactate concentration inhibits its production from pyruvate and favours the reverse reaction. This thermodynamic effect leads to a complete stop of lactic fermentation at ~25 mM intracellular lactate . This concentration is within the range resulting from lactic acidosis. 4.3. Lactic Acidosis and Mitochondrial Catabolism 4.3.1. Lactic Acidosis Intensifies Mitochondrial Catabolism Lactic acidosis enhances mitochondrial metabolic activity, in particular the TCA cycle and OxPhos. Both lactic acidosis and lactosis enhance mitochondrial biogenesis and the expression of the enzymes of the TCA cycle and OxPhos , which potentiates mitochondrial catabolism and ATP production. The reactivation of those pathways allows the maintenance of the cellular ATP concentration in glucose deprivation and increases resistance to starvation . 4.3.2. Lactic Acidosis Shapes TCA Cycle Alternative Fueling In addition to glucose-derived pyruvate, the TCA cycle can be supplied with various substrates. This flexibility is particularly true of cancer cells . In challenging nutritional contexts such as glucose deprivation, the TCA cycle of cancer cells can be sustained by alternative nutrients. Lactate and glutamine are its main substrate suppliers after glucose . The use of both is promoted by lactic acidosis. The pyruvate generated from lactate can directly sustain the TCA cycle . This pathway depends on upstream lactate import by MCTs, whose enhancement in lactic acidosis is discussed in Section 4.1.2. In line, extracellular lactate increases the mitochondrial membrane potential, and hence ATP production efficiency in OxPhos , and could even be necessary to pro-tumoural cell proliferation . In more detail, the routing of lactate to mitochondria is debated. In the classical view, lactate is converted to pyruvate in the cytosol, then pyruvate is shuttled to mitochondria . In addition to this classical way, Brooks et al. proposed an alternative model in which lactate would be shuttled to mitochondria via the mitochondrial lactate oxidation complex (mLOC), that includes MCT1 . The controversy raised by this model has been well-reviewed in , that summarized the evidence for and against it in non-cancer cells. In cancer cells supplied with sufficient glucose, lactate's contribution to the TCA cycle over glucose remains under debate: some studies suggest that lactate shuttled to mitochondria is preferred , while others question this . Either way, under glucose deprivation, we can hypothesise that lactate's contribution to the TCA cycle is of significant importance. Glutamine is a major nutrient for cancer cells. It undergoes oxidative glutaminolysis in mitochondria, where it is processed by glutaminase 1 or 2 (GLS1/2) and then glutamate dehydrogenase 1 (GDH1) to sustain the TCA cycle. Lactic acidosis , acidosis , and lactate upregulate GLS1 and GLS2 and stimulate oxidative glutaminolysis. Lactic acidosis, however, doesn't necessarily promote glutamine consumption compared to lactosis . In summary, either extracellular lactate, acidosis or lactic acidosis enhance glutamine utilisation by inducing glutaminase expression . 4.4. Lactic Acidosis and Redox Homeostasis Cell survival requires redox homeostasis, i.e., controlled levels of reactive oxygen species (ROS) and redox coenzymes. The former lead to cell death when they accumulate, and the latter support the entire metabolism and cellular antioxidant defences. Particularly, a high NADPH/NADP+ ratio kinetically favours anabolic reactions and helps keep ROS levels low. In cancer cells this ratio is abnormally high and sustains hyperactive anabolism . High NADPH levels are supported by the oxidation of nutrients, such as lactate and glutamine via the TCA cycle and then oxidation of lactate-derived malate and isocitrate by the malic enzyme 1 (ME1) and Isocitrate Dehydrogenase 1 (IDH1), and mainly glucose via the pentose phosphate pathway (PPP). Redox homeostasis in cancer cells is therefore particularly sensitive to nutritional stress such as glucose deprivation. In this condition, lactic acidosis helps stabilise the NADPH/NADP+ ratio at ~50% of its level in glucose sufficiency . Likely, the gatekeepers of the NADPH/NADP+ ratio in glucose abundance have reduced efficiency under glucose deprivation and lactic acidosis, whereas new control mechanisms gain importance. On the one hand, glutamine use via ME1 is not necessary to the maintenance of the NADPH/NADP+ ratio under lactic acidosis . Glutamine would indeed be completely degraded in mitochondrial catabolism instead of sustaining ME1 activity . On the other hand, the glucose directed away from glycolysis towards the PPP would prevail more in NADPH/NADP+ maintenance under lactic acidosis. Lactic acidosis and acidosis respectively increase the expression and activity of glucose-6-phosphate dehydrogenase (G6PD), the first enzyme of the PPP, and lactic acidosis makes G6PD activity necessary to NADPH/NADP+ ratio maintenance and cell survival in glucose sufficiency. However in glucose deprivation, the PPP alone cannot maintain redox balance . Alternatively, lactate would become a key player in NADPH/NADP+ ratio maintenance, via the TCA cycle , and IDH1 . Whether, in glucose abundance, such reprogramming strengthens cell defences against ROS level increase is uncertain. Acidosis increases ROS levels and cell sensitivity to oxidative stress, but cell adaptation to acidosis decreases them . Lactate import through MCT1 is key to maintain low ROS levels . Lactic acidosis was found to either increase ROS levels, as does acidosis , or to rescue acidosis' negative effect . At any rate, in glucose deprivation, lactic acidosis mainly prevents increased ROS levels by providing IDH1 with its substrate . A high NADH/NAD+ ratio supports ATP production. Lactic acidosis impact on the NADH/NAD+ ratio has not been directly investigated. However lactate use by the TCA cycle increases the NADH/NAD+ ratio in glucose deprivation . This increase could contribute to the inhibition of glycolysis by lactic acidosis: a high NADH/NAD+ ratio would inhibit glycolysis according to the mass action law. Yet this hypothesis remains to be tested. 4.5. Section Summary In the energy metabolism of cancer cells, acidosis and extracellular lactate act as enzymatic inhibitors, and lactate as a signal and a nutrient. They mostly curb glycolysis and lactic fermentation and enhance the TCA cycle and OxPhos . Acidification and lactate accumulation in the tumour microenvironment would promote and sustain an oxidative phenotype, which is fitter than the fermenting phenotype in glucose deprivation, an adverse nutritional context that is common in tumours. 5. Therapeutic Strategies Targeting Lactic Acidosis Nowadays, lactic acidosis per se is targeted in therapies directed against cancer. Of note, it is also a major target in the treatment of type 2 diabetes . Neutralising acidosis in tumours has been proposed as a way to restore sensitivity of cancer cells to glucose starvation and increase the efficacy of regular treatments. The proof of principle of this approach has been established by combining transarterial chemoembolization (TACE) with the infusion of bicarbonate, a basifying agent that turns neoplastic lactic acidosis into lactosis . Compared to TACE alone, TILA-TACE (Targeting-Intratumoural-Lactic-Acidosis TACE) presented a very significantly enhanced anticancer activity for patients with hepatocellular carcinoma. The mechanisms underlying this activity have been evaluated in detail by Ying et al. . Modulating extracellular lactate availability in tumours by nanomedicine is another promising therapeutic strategy. The delivery by nanoparticles of a cocktail of lactate oxidases and catalases to colon carcinoma cells in vitro suppresses tumoural lactosis and stops cell proliferation . The delivery by nanoparticles of a glucose catalase combined with a MCT1 inhibitor, that together prevent the use of both glucose and lactate by tumour cells, inhibits the proliferation of SiHa cell line xenografts in mice . Conversely, lactate-loaded nanoparticles induce an overload of lactate and cytotoxicity in orthotopic glioblastoma models, although only in normoxic conditions and not in hypoxia . Understanding the effects of lactic acidosis also helps reappraise the potential of already-existing targets. In particular, the lactate transporter MCT1 was formerly targeted to inhibit lactate secretion in cells showing the Warburg effect, and is now targeted to hamper lactate uptake . Similarly the strategies targeting LDH isoforms were aimed historically at inhibiting lactate production from pyruvate. The LDHA isoform, that has a higher affinity for pyruvate than for lactate and catalyses preferentially lactate production, is a historical target that still attracts much attention . However, with the discovery of lactic acidosis effect, the LDHB isoform that catalyses preferentially the conversion of lactate to pyruvate now rises as an alternative target . 6. Implications of Lactic Acidosis in the Whole-Tumour Metabolism Deciphering how lactic acidosis impacts cancer cells enlightens important aspects of the metabolism of the whole tumour, and raises new perspectives to complement its understanding. From the belief that cancer cells have a unique metabolic signature, i.e., the Warburg effect, research has progressively recognized intratumoural heterogeneity as the metabolic hallmark of cancer . The main metabolic heterogeneity in tumours is now suggested to be mitochondrial activity , that is promoted and sustained by lactic acidosis. To describe this heterogeneity, tumours have traditionally been modelled as the coexistence of two metabolic populations: oxidative cells relying on OxPhos and fermenting cells showing the Warburg effect and relying on glycolysis and lactic fermentation . Oxidative cells would be located in normoxic regions, in perivascular compartments , and fermenting cells in hypoxic regions farther from blood vessels . Each population would thrive on different energy sources, fermenting cells glucose and oxidative ones lactate, and lactate would be transferred from fermenting to oxidative cells . This model is supported by the coexistence in tumours of cells overexpressing MCT4, a preferential lactate exporter, and cells overexpressing MCT1, a preferential lactate importer . Interestingly, a possible lactate transport via gap junctions has been evidenced recently . This lactate transfer supports the idea of a metabolic symbiosis between both populations within tumours . In this model, a central question is how the metabolic phenotypes of both populations are determined . Hypoxia is thought to be the major promoter of the fermenting phenotype . Lactic acidosis, according to the evidence presented in this work, is likely the promoter of the oxidative phenotype . However this hypothetical scenario raises a paradox: the oxidative phenotype, that derives from lactic acidosis, i.e., from the fermenting phenotype that is promoted by hypoxia, cannot thrive in hypoxic conditions. Two hypotheses could solve this paradox. In the first hypothesis, fermenting cells would induce the oxidative phenotype in their neighbours, located in better-perfused regions. However lactic acidosis intensity, maximal around secretory cells, decreases with the distance , which raises the question of the minimal level of lactic acidosis necessary to promote the oxidative phenotype. In the second hypothesis, lactic acidosis would feedback the Warburg effect in fermenting cells by switching them to an oxidative phenotype, which questions the minimal oxygen level necessary for the oxidative phenotype to survive. A possible answer to this question is that in the meantime, lactic acidosis could promote angiogenesis . This questions the timeline of lactic acidosis action, in the promotion of both oxidative phenotype and angiogenesis. A third perspective to answer the paradox is to address how, earlier, hypoxia and lactic acidosis may interplay in the promotion of metabolic phenotypes, which has caught little attention until now . 7. Conclusions Lactic acidosis associated with tumour progression allows cancer cells to survive in unfavourable environments. In the last decade, the influence of neoplastic lactic acidosis on the energy metabolism of cancer cells has been deciphered. Lactic reduces glycolysis and lactic fermentation, stimulates the TCA cycle and OxPhos, and promotes the use of alternative nutrients. All in all, it contributes to cell resistance to glucose deprivation. Cancelling lactic acidosis' effect is therefore a relevant anticancer strategy that restores cancer cell sensitivity to glucose deprivation, a common feature of the tumour microenvironment. In the future, clarifying how lactic acidosis action is integrated in the whole-tumour metabolism would be of high interest. Author Contributions Writing--original draft preparation, Z.D.; writing--review and editing, Z.D., A.B., G.J.P.R. and B.P.; supervision, G.J.P.R. and B.P.; funding acquisition, G.J.P.R. and B.P. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Lactic acidosis rewires energy metabolism and maintains cellular homeostasis. Lactic acidosis enhances the uptake of folate, long-chain fatty acids, glutamine, and lactate. It represses glucose import, glycolysis (by inhibiting HK and PFK, its rate-limiting enzymes) and lactic fermentation. It enhances lactate conversion to pyruvate, routing of pyruvate and glutamine towards the TCA cycle, ATP generation by OxPhos, and coenzyme reduction by IDH1 and the oxidative PPP. It also upregulates CA IX expression, which basifies intracellular pH. Abbreviations: ASCT2: Alanine, Serine, Cysteine Transporter 2; CA IX: carbonate anhydrase 1; GLUT1: glucose transporter 1; HK: hexokinase; IDH1: isocitrate dehydrogenase 1; MCT1: monocarboxylate transporter 1; OxPhos: oxidative phosphorylation; PFK1: phosphofructokinase 1; PPP: pentose phosphate pathway; TCA: tricarboxylic acid. Figure 2 Lactic acidosis would contribute to a metabolic symbiosis between fermenting and oxidative cells within tumours. In this model, two populations coexist in tumours: fermenting cells in hypoxic regions, and oxidative cells in normoxic regions where lactic acidosis would exert its effect. Fermenting cells would consume the glucose spared by oxidative cells and generate the lactate fueling them, both being in a metabolic symbiosis. Lactic acidosis promotes the switch from a fermenting to an oxidative phenotype. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000467 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050799 cells-12-00799 Article Melatonin Inhibits VEGF-Induced Endothelial Progenitor Cell Angiogenesis in Neovascular Age-Related Macular Degeneration Lin Liang-Wei Conceptualization Validation Writing - original draft 1+ Wang Shih-Wei Methodology Resources 234+ Huang Wei-Chien Software Validation 1567 Huynh Thanh Kieu Software Validation 158 Lai Chao-Yang Investigation 6 Ko Chih-Yuan Methodology Data curation 19 Fong Yi-Chin Methodology Investigation 91011 Lee Jie-Jen Methodology 2 Yang Shun-Fa Formal analysis 1213* Tang Chih-Hsin Conceptualization Writing - review & editing Funding acquisition 16141516* Satomura Kazuhito Academic Editor Bonder Claudine Academic Editor 1 Graduate Institute of Biomedical Sciences, China Medical University, Taichung 403433, Taiwan 2 Department of Medicine, MacKay Medical College, New Taipei City 25245, Taiwan 3 Institute of Biomedical Sciences, Mackay Medical College, New Taipei City 25245, Taiwan 4 School of Pharmacy, College of Pharmacy, Kaohsiung 807378, Taiwan 5 Drug Development Center, China Medical University, Taichung 403433, Taiwan 6 Department of Medical Laboratory Science and Biotechnology, College of Medical and Health Science, Asia University, Taichung 40354, Taiwan 7 Research Center for Cancer Biology and Center for Molecular Medicine, China Medical University, Taichung 403433, Taiwan 8 Center for Molecular Medicine, China Medical University Hospital, Taichung 40402, Taiwan 9 Department of Orthopedic Surgery, China Medical University Hospital, Taichung 40402, Taiwan 10 Department of Sports Medicine, College of Health Care, China Medical University, Taichung 403433, Taiwan 11 Department of Orthopedic Surgery, China Medical University Beigang Hospital, Yun-Lin County 65152, Taiwan 12 Institute of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan 13 Department of Medical Research, Chung Shan Medical University Hospital, Taichung 40201, Taiwan 14 Department of Pharmacology, School of Medicine, China Medical University, Taichung 403433, Taiwan 15 Chinese Medicine Research Center, China Medical University, Taichung 403433, Taiwan 16 Department of Medical Research, China Medical University Hsinchu Hospital, Hsinchu 40402, Taiwan * Correspondence: [email protected] (S.-F.Y.); [email protected] (C.-H.T.) + These authors contributed equally to this work. 03 3 2023 3 2023 12 5 79920 1 2023 15 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Neovascular age-related macular degeneration (AMD) is described as abnormal angiogenesis in the retina and the leaking of fluid and blood that generates a huge, dark, blind spot in the center of the visual field, causing severe vision loss in over 90% of patients. Bone marrow-derived endothelial progenitor cells (EPCs) contribute to pathologic angiogenesis. Gene expression profiles downloaded from the eyeIntegration v1.0 database for healthy retinas and retinas from patients with neovascular AMD identified significantly higher levels of EPC-specific markers (CD34, CD133) and blood vessel markers (CD31, VEGF) in the neovascular AMD retinas compared with healthy retinas. Melatonin is a hormone that is mainly secreted by the pineal gland, and is also produced in the retina. Whether melatonin affects vascular endothelial growth factor (VEGF)-induced EPC angiogenesis in neovascular AMD is unknown. Our study revealed that melatonin inhibits VEGF-induced stimulation of EPC migration and tube formation. By directly binding with the VEGFR2 extracellular domain, melatonin significantly and dose-dependently inhibited VEGF-induced PDGF-BB expression and angiogenesis in EPCs via c-Src and FAK, NF-kB and AP-1 signaling. The corneal alkali burn model demonstrated that melatonin markedly inhibited EPC angiogenesis and neovascular AMD. Melatonin appears promising for reducing EPC angiogenesis in neovascular AMD. melatonin endothelial progenitor cells vascular endothelial growth factor (VEGF) platelet-derived growth factor-BB (PDGF-BB) angiogenesis neovascular age-related macular degeneration Ministry of Science and Technology of TaiwanMOST 111-2314-B-039-048-MY3 China Medical UniversityCMU111-ASIA-04 CMU111-ASIA-05 China Medical University HospitalDMR-111-108 DMR-111-229 DMR-110-176 DMR-111-165 DMR-112-090 DMR-112-146 DMR-112-096 MacKay Medical CollegeMMC-RD-110-1B-P015 MMC-RD-110-1B-P023 MMC-RD-111-1B-P010 MMC-RD-111-1B-P016 This work was supported by grants from the Ministry of Science and Technology of Taiwan (MOST 111-2314-B-039-048-MY3), China Medical University (CMU111-ASIA-04; CMU111-ASIA-05), China Medical University Hospital (DMR-111-108; DMR-111-229; DMR-110-176; DMR-111-165; DMR-112-090; DMR-112-146; DMR-112-096) and MacKay Medical College (MMC-RD-110-1B-P015; MMC-RD-110-1B-P023; MMC-RD-111-1B-P010; MMC-RD-111-1B-P016). pmc1. Introduction Age-related macular degeneration (AMD) is an age-related ocular disease that leads to visual impairment, drusen, retinal pigmentary changes, and blood vessel angiogenesis in the retina . Increasing life expectancies and aging populations in most countries worldwide are contributing to a steady increase in the global prevalence of AMD . AMD can be broadly classified as the non-neovascular (dry) or neovascular (wet) type. Neovascular AMD is described as abnormal angiogenesis in the retina and the leaking of fluid and blood that creates a large blind spot in the center of the visual field, causing severe vision loss in more than 90% of patients . Angiogenesis is a complex process that regulates many physiological functions, including wound healing and tissue development, as well as reproduction , while it also contributes to pathological processes, such as atherosclerosis and inflammatory diseases , as well as neovascular AMD . Angiogenic factors such as vascular endothelial growth factor (VEGF) and platelet-derived growth factor-BB (PDGF-BB) contribute to neovascular AMD . Inhibiting angiogenesis is therefore a critical strategy in neovascular AMD. Currently, anti-VEGF therapy is the only available treatment for neovascular AMD; this therapy targets the vascular endothelial growth factor receptor (VEGFR) . Anti-VEGF/VEGFR2 therapy can effectively inhibit choroidal neovascularization (CNV) and downregulate levels of VEGF mRNA expression in mice with laser-induced CNV . However, although anti-VEGF drugs have provided positive results in clinical trials, these outcomes have not translated into real-world outcomes . Thus, other treatment targets besides VEGF and VEGFR are necessary for neovascular AMD. Endothelial progenitor cells (EPCs) are derived from bone marrow-derived endothelial stem cells, and are involved in physiological and pathological angiogenesis . EPCs are recruited in response to angiogenesis, and regulate several cellular functions such as proliferation and migration . Characterized by their surface markers CD34 and CD133, as well as by VEGFR2, EPCs play an important role in the progression of new blood vessel formation . Importantly, VEGF stimulates EPC angiogenesis, including the survival, motility, and tube formation of EPCs , via the VEGFR2/c-Src/FAK signaling pathway as well as the transcription factors NF-kB and AP-1 ; this mobilization of EPCs enables the development of neovascular AMD . EPC-dependent angiogenesis appears to be a valuable treatment target for neovascular AMD, as the anti-VEGF drug ranibizumab significantly reduces the high levels of circulating EPCs that are involved in AMD angiogenesis . The synthesis and release of the neurohormone melatonin enables organisms to respond to circadian and seasonal rhythms . Melatonin is mainly secreted by the pineal gland under the influence of light stimulation of the retina; to a lesser extent, melatonin is also synthesized within the eye, where melatonin uses ocular structures to mediate a variety of diurnal rhythms and physiological processes within the eye . Increasing the concentration of melatonin at night promotes sleep, while decreasing the concentration of melatonin during the day promotes alertness . Melatonin concentrations tend to decrease with age . The effects of melatonin are beneficial for numerous physiological functions, including the promotion of ocular surface wound healing , reductions in inflammation and oxidative stress , and angiogenesis . The expression and secretion of VEGF is important in retinal physiology . The release of VEGF from retinal pigment epithelial cells helps to protect neuronal cells and the choroid, maintaining a healthy retina . Notably, melatonin reduces retinal levels of VEGF and protects against ocular angiogenesis diseases . However, whether melatonin affects VEGF-induced EPC angiogenesis in neovascular AMD is unclear. This study therefore aimed to determine whether melatonin treatment inhibits VEGF-induced EPC angiogenesis during the development of neovascular AMD. The study also sought to define any other underlying mechanisms, such as signaling pathways, which may mediate this process. 2. Materials and Methods 2.1. Materials Recombinant human VEGF (100-20) was bought from PeproTech (Rocky Hill, NJ, USA). VEGFR2 (07-158), phospho-VEGFR2 (orb106137), CD133 (orb13002), and b-actin (a5441) antibodies, and melatonin (M5250) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Phospho-FAK (3283S) antibodies was purchased from Cell Signaling (Danvers, MA, USA). FAK (sc-1688), phospho-c-Src (sc-12928-R), c-Src (2105S), phospho-c-Jun (sc-822), c-Jun (sc-74543), phospho-p65 (sc-101752), p65 (sc-8008), CD31 (sc-18916), and CD34 (sc-74499) antibodies, as well as the angiotensin II (FAK activator; sc-363643) and c-Src activator (sc-3052), were purchased from Santa Cruz Biotechnology (Dallas, TX, USA). The NF-kB activator (prostratin; ab120880) was purchased from Abcam (Cambridge, MA, USA). PDGF-BB antibody (MBS9404630) was purchased from MyBioSource (San Diego, CA, USA). The VEGFR2 short hairpin RNA (shRNA) plasmid was purchased from the National RNAi Core Facility Platform (Taipei, Taiwan). 2.2. Cell Culture Human primary EPCs were prepared as described in our previous protocols . EPCs were cultured in MV2 complete medium (PromoCell, Heidelberg, Germany) with 20% fetal bovine serum (FBS; HyClone, Logan, UT, USA), and maintained in a humidified incubator at 37 degC, 5% CO2 . 2.3. Analysis of the Eyeintegration v1.0 Database Gene expression profile records were downloaded from the eyeIntegration v1.0 database accessed on 13 January 2022) for 57 normal retina tissue samples and 448 retina tissue samples from AMD patients, for analysis of CD31, CD34, CD133, VEGF, and PDGF-BB expression . 2.4. Migration Assay Transwell chambers (8.0 mm pore sizes; Corning, NY, USA) were used for the migration assay. EPCs (8 x 103 in each well) were applied to the upper chambers of 24-well plates in 200 mL of serum-free MV2 complete medium containing 100 ng/mL VEGF. The lower chambers were filled with 300 mL of MV2 complete medium combined with 5% FBS and different concentrations of melatonin (0.1, 0.3, or 1 mM), then incubated for 18 h at 37 degC and 5% CO2. The cells in the lower chambers were fixed with 3.7% formaldehyde and stained with 0.5% crystal violet solution. The numbers of migrated cells were counted by microscope (Nikon, Tokyo, Japan) and analyzed by MacBiophotonics ImageJ software . 2.5. Tube Formation Assay The 48-well plates were coated with 150 mL of Matrigel (BD Biosciences, MA, USA) and incubated for 30 min at 37 degC. EPCs (2 x 104 cells/well) were seeded onto the gel layer in a 50% MV2 complete medium containing VEGF with melatonin (0.1, 0.3, or 1 mM), then incubated for 6 h at 37 degC. EPC tube formation was evaluated under an inverted phase-contrast microscope (Nikon, Tokyo, Japan). The number of tube branches was quantified by MacBioPhotonics ImageJ software . 2.6. Proliferation Assay EPCs (5 x 103) were seeded in a 96-well plate and incubated with melatonin for 24 h or 48 h, before adding 10 mL of CCK-8 reagent (96992, Sigma-Aldrich, St. Louis, MO, USA) and incubating the EPCs at 37 degC for 2-4 h. The samples were quantified by a microplate reader (Bio-Tek, Winooski, VT, USA) at OD 570 nm. 2.7. Angiogenesis Protein Array The cell lysate was examined with the Human Angiogenesis Protein Array (ARY007, R&D Systems, Minneapolis, MN, USA), following the manufacturer's protocol . The results of the protein array were quantified with the ImageQuantTM LAS 4000 biomolecular imager (GE Healthcare Life Sciences, Chicago, IL, USA). 2.8. Chromatin Immunoprecipitation (ChIP) Assay The chromatin immunoprecipitation analysis followed the previously described methodology . DNA was immunoprecipitated with an anti-p65 or anti-c-Jun antibody and purified by phenol-chloroform extraction. Immune complexes were collected with protein G-Sepharose beads and eluted from the beads using an elution buffer. The purified DNA pellet was subjected to PCR, and then the PCR products were analyzed on 1.5% agarose gel electrophoresis and visualized by UV light. The primers 5'-CCAAGAGGCTAGATTCACAGTCAC and 3'-TTCAGCTGTTCCGGCCTTT were used to amplify across the PDGF-BB promoter region (-197/-7). 2.9. Chick Chorioallantoic Membrane (CAM) Assay The CAM assay was performed according to our previously published method . VEGF and melatonin (0.1, 0.3, or 1 mM) were mixed with Matrigel and dropped onto the developing chicken egg, then incubated at 38 degC in an 80% humidified atmosphere. After 14 days, CAMs were observed by microscopy and photographic documentation. The number of CAM blood vessels was quantified by MacBioPhotonics ImageJ software. 2.10. Matrigel Plug Assay The Matrigel plug angiogenesis assay was performed according to our previous research . Male nude mice (4 weeks old) were subcutaneously injected with 300 mL Matrigel containing VEGF with the indicated concentrations of melatonin. The plugs were collected after 7 days and processed by immunofluorescence staining for co-staining with CD31, CD34 and CD133 antibodies. All samples were then stained with 40,6-diamidino-2-phenylindole (DAPI) and captured by the TissueFAXS-S-plus imaging system (TissueGnostics, Vienna, Austria). Hemoglobin levels were examined using Drabkin's reagent and detected at 450 nm with a microplate reader (Bio-Tek, Winooski, VT, USA). 2.11. Molecular Docking The structures of melatonin (PDB code: 5mxb) and VEGFR2 (PDB code: 3V2A) were downloaded from the Protein Data Bank (PDB, accessed on 11 May 2022). The molecular docking analysis between melatonin and the VEGFR2 extracellular domain (ECD) was performed using Discovery Studio software . 2.12. Corneal Alkali Burn Model Male C57BL/6J mice (6-8 weeks old) were anesthetized with an intramuscular injection of Zoletil (0.2 mL/kg). Alkali burn injury was induced by placing 2 mm diameter filter paper (soaked in 1 mol/L NaOH) on the center of the right cornea for 30 s, before gently washing the ocular surface with 30 mL of 1X PBS solution. The mice were then immediately treated with melatonin by intraperitoneal (IP) injection (20 mg/kg or 60 mg/kg), or 1X PBS solution by IP injection, or the VEGF inhibitor bevacizumab (5 mg/mL) by eye drop, continuing with the same treatment regimen every 2 days. The eyeballs were observed by a microscope (Nikon, Tokyo, Japan) on days 0, 3, 5, and 7. On day 7, all mice were sacrificed, and their eyeballs were collected and fixed in Davidson's fluid for histological analysis . All animal procedures were performed according to an approved protocol issued by the Institutional Animal Care and Use Committee of China Medical University (Taichung, Taiwan). 2.13. Statistical Analysis All statistical analyses were performed using GraphPad Prism 7.0 software, and all values are expressed as the mean +- standard deviation (SD). Differences between selected pairs from the study groups were analyzed for statistical significance using the Student's t-test. One-way analysis of variance (ANOVA) followed by post hoc testing was used for statistical analyses of multiple group comparisons. The difference was considered to be significant if the p value was <0.05. 3. Results 3.1. Higher Levels of EPC Markers Correlate with AMD Progression Angiogenesis plays an important role in AMD . To confirm the involvement of EPCs in neovascular AMD, we analyzed gene expression profiles from the eyeIntegration v1.0 database. EPC-specific markers CD34 and CD133 and blood vessel markers CD31 and VEGF were all highly expressed in AMD retinas and graded with Minnesota Grading System (MGS) scores of 1 to 4, whereas their expression was low in retinas from healthy individuals , indicating that EPCs contribute to the progression of neovascular AMD. 3.2. Melatonin Inhibits VEGF-Promoted Proliferation, Migration, and the Tube Formation of EPCs without Cytotoxicity In previous research, melatonin treatment has shown strong antiangiogenic effects by suppressing the proliferation, migration and invasion of endothelial cells , and melatonin effectively disrupted the tube formation of human umbilical vein endothelial cells (HUVECs) and dose-dependently reduced the viability of HUVECs , although the effects of melatonin are unclear in EPCs. When we examined the apoptotic effects of melatonin in EPCs, MTT assay results showed that incubating EPCs with different concentrations of melatonin (0.1-1 mM) for 24 h or 48 h did not affect cell viability , so this concentration range was used for further experiments. The incubation of EPCs with VEGF (100 ng/mL) and melatonin (0.1-1 mM) for 24 h showed that VEGF alone promoted the proliferation of EPCs; VEGF plus melatonin significantly reduced this proliferation in a concentration-dependent manner . Next, the migration assay results showed that melatonin significantly inhibited VEGF-induced cell migration in a dose-dependent manner , while the tube formation assay showed that VEGF alone stimulated the reorganization and the formation of capillary-like structures in EPCs, whereas the addition of melatonin to VEGF significantly suppressed these effects . 3.3. In Vivo Results Show that Melatonin Inhibits VEGF-Induced EPC Recruitment and Angiogenesis To examine whether melatonin inhibits VEGF-induced angiogenesis in vivo, Matrigel was mixed with VEGF (100 ng/mL) and different concentrations of melatonin as indicated in the CAM assay . The results showed that melatonin reduced VEGF-induced neoangiogenesis . Using the Matrigel plug assay to examine the in vivo angiogenesis activity of melatonin, we observed that VEGF promoted microvessel formation and hemoglobin levels over 7 days in the Matrigel plugs, whereas melatonin significantly and dose-dependently inhibited this process . In the co-immunofluorescent staining results for the blood vessel marker CD31 and EPC-specific markers CD34 and CD133, all markers were significantly and dose-dependently reduced by melatonin . Our findings show that melatonin effectively suppresses VEGF-induced EPC recruitment and angiogenesis in vivo. 3.4. Melatonin Inhibits VEGF-Induced Increases in PDGF-BB Expression and EPC Angiogenesis The results of the angiogenesis protein array show that VEGF treatment increased the amount of angiogenic factors in EPCs and that the addition of melatonin decreased these factors ; in particular, the expression of PDGF-BB was significantly reduced after melatonin treatment . Furthermore, we found that melatonin decreased VEGF-induced PDGF-BB expression in EPCs in a dose-dependent manner . Whereas melatonin significantly inhibited VEGF-induced EPC migration and tube formation, these effects were significantly reversed when the EPCs were transfected with PDGF-BB cDNA for 24 h . Moreover, we found that the levels of PDGF-BB gene expression were significantly higher in retinas from patients with neovascular AMD than in retinas from healthy individuals . These results suggest that melatonin suppresses angiogenesis by inhibiting VEGF-induced PDGF-BB production in EPCs. 3.5. Melatonin Reduces VEGF-Induced EPC Angiogenic Functions by Inhibiting the VEGFR2/c-Src/FAK Signaling Pathway We examined whether melatonin is capable of blocking the VEGF/VEGFR2 interaction. Using molecular docking software to predict melatonin-VEGFR2 binding affinity, we found that melatonin interacts with the VEGFR2 ECD, with an energy value of -27.121 kCal/mol for the docked complex , indicating that melatonin inhibits VEGF-induced angiogenesis by directly binding with VEGFR2. Next, we found that melatonin inhibits the VEGF-induced phosphorylation of VEGFR2, c-Src, and FAK in EPCs . We then transfected EPCs with VEGFR2 cDNA or treated the EPCs with FAK or c-Src activators to verify whether VEGF/VEGFR2 signaling regulates EPC angiogenesis. Whereas melatonin treatment significantly inhibited VEGF-induced EPC migration and tube formation, these effects were significantly reversed by transfection with VEGFR2 cDNA, and also by treatment with the FAK and c-Src activators , suggesting that melatonin inhibits the VEGF-induced phosphorylation of VEGFR2, c-Src, and FAK in EPCs via VEGFR2/c-Src/FAK signaling. 3.6. NF-kB and AP-1 Contribute to Melatonin-Induced Inhibition of EPC Angiogenesis VEGF-induced phosphorylation of the NF-kB subunit (p65) and AP-1 subunit (c-Jun) was significantly and dose-dependently reduced by melatonin . Next, we tested whether NF-kB or AP-1 are involved in the melatonin-induced inhibition of EPC angiogenesis. Treatment with NF-kB and AP-1 activators significantly promoted EPC angiogenesis, which was significantly reduced by melatonin treatment . We then observed that melatonin significantly reduced NF-kB or AP-1 luciferase activity and their translocation into the nucleus . We also explored whether PDGF-BB is involved in the melatonin-induced inhibition of NF-kB or AP-1 transcriptional activation, using the ChIP assay to assess the in vitro recruitment of NF-kB or AP-1 to the PDGF-BB promoter. As shown in Figure 6G,H, VEGF induced the binding of NF-kB or AP-1 to the PDGF-BB element, and melatonin treatment reduced this binding. These results indicate that melatonin inhibits VEGF-induced PDGF-BB production and angiogenesis in EPCs via the suppression of NF-kB and AP-1 activity. 3.7. Melatonin Treatment Inhibits EPC Angiogenesis in the Corneal Alkali Burn Model As shown in Figure 7A, corneal neovascularization was increased in the PBS-treated eyes, and decreased after melatonin treatment in a dose-dependent manner. Notably, the effects of melatonin in the highest dose group (60 mg/kg) were similar to those of the bevacizumab treatment group. After the animals were sacrificed on Day 7, the eyeballs were removed to examine corneal epithelial defects. H&E staining showed that corneal swelling was dose-dependently decreased by melatonin . Co-immunofluorescence staining for EPCs and vessel markers showed that melatonin significantly and dose-dependently inhibited EPC angiogenesis and the recruitment of CD31-, CD133-positive colonies . The effects of melatonin 60 mg/kg were similar to those of bevacizumab treatment. Levels of PDGF-BB expression were increased in the control group and significantly reduced after melatonin or bevacizumab treatment . Thus, melatonin appears to suppress PDGF-BB production, EPC recruitment, and angiogenesis, as well as AMD development in vivo. 4. Discussion Neovascular AMD is a serious type of late AMD and an angiogenesis-dependent disease . By triggering the mobilization of EPCs from the bone marrow and their recruitment during pathological states, VEGF supports the differentiation of EPCs into mature endothelial cells at angiogenesis sites . EPCs may serve as a biomarker of neovascular AMD, based on the higher levels of EPC expression in blood from patients with AMD compared with blood from healthy controls . Our analysis of gene expression profiles downloaded from the eyeIntegration v1.0 database confirmed high levels of EPC-specific markers (CD34 and CD133) in the retinal tissue of patients with AMD. Our preclinical findings also indicated that EPCs contribute to angiogenesis and AMD progression. Our results are consistent with pre-existing clinical evidence and emphasize the importance of EPCs in neovascular AMD. VEGF is described as an endothelial cell-specific mitogen that promotes the proliferation of new vessels and increases vascular permeability, and is considered to be a critical angiogenic factor of all angiogenesis processes . Anti-VEGF treatment is an established therapeutic approach for neovascular AMD . However, although the existing anti-VEGF agents, including bevacizumab, effectively inhibit VEGF activation and EPC-derived pathological angiogenesis , many patients do not show the expected efficacy of anti-VEGF agents after repeated administration . EPC-targeting therapies may therefore be a promising option to inhibit the angiogenesis process in neovascular AMD. In this study, EPCs were used to investigate the antiangiogenic effects of melatonin. Our findings show that melatonin inhibits VEGF-induced EPC angiogenesis in a concentration-dependent manner, without any evidence of cytotoxicity. Moreover, melatonin significantly suppressed the VEGF-induced stimulation of EPC recruitment and angiogenesis in vivo. Importantly, the corneal alkali burn model indicated that the inhibitory effects of melatonin on EPC-derived pathological angiogenesis are similar to those of bevacizumab, indicating that melatonin has potential against EPC-derived angiogenesis in neovascular AMD. There is much evidence to indicate that the binding of VEGF to VEGFR2 regulates angiogenesis progression in physiological and pathological conditions, and promotes EPC-derived angiogenesis . In our study, we found that melatonin inhibits VEGF-induced angiogenesis in EPCs by blocking the VEGF/VEGFR2 signaling pathway. Notably, molecular docking software results identified a good affinity between melatonin and the VEGFR2 ECD. To the best of our knowledge, this study is the first to identify that melatonin has the potential to bind with VEGFR2 and that melatonin may compete with VEGF in this binding process. Our in vitro evidence also showed that melatonin dramatically reduced the phosphorylation of VEGFR2 in EPCs. All of these results reveal that melatonin inhibits EPC-derived angiogenesis by regulating VEGF/VEGFR2 activity. VEGF and PDGF-BB, as well as their receptors, are critical for normal and pathologic angiogenesis . In neovascular AMD, VEGF promotes new vessel growth, while PDGF-BB maintains the interaction between pericytes and endothelial cells in maturing vessels . While VEGF antagonists can inhibit angiogenesis in neovascular AMD, dual VEGF/PDGF inhibitors have proven to be even more beneficial in inhibiting angiogenesis in human endothelial cells and human pericytes in neovascular AMD , as well as in suppressing neovascularization in a mouse model of laser-induced CNV . In our study, melatonin significantly reduced VEGF-induced PDGF-BB production in EPCs, as well as EPC migration and tube formation. In addition, our findings from the corneal alkali burn model suggest that melatonin can significantly inhibit corneal levels of PDGF-BB expression and angiogenic activity. Our results suggest that melatonin suppresses angiogenesis in EPCs by inhibiting PDGF-BB production. The promotion or inhibition of angiogenesis is part of the homeostatic balance, with positive and negative effects outside the optimum range. Melatonin influences this balance, with evidence from several clinical research investigations demonstrating that this hormone has antiangiogenic effects in cancer and chronic ocular diseases. For instance, in cancer treatment, adjuvant melatonin appears to be very effective in early-stage disease and helps to reduce the side effect profiles after radiotherapy and chemotherapy . In patients with central serous chorioretinopathy, treatment with oral melatonin (3 mg) three times daily for 1 month resulted in significant improvements from baseline in best-corrected visual acuity (BCVA) and decreases in central macular thickness (CMT), without any adverse effects . The attractive side effects profile and relatively low cost of melatonin suggest that this hormone may be appropriate in a chronic ocular disease such as AMD, although supporting data from large prospective studies are needed before melatonin can be used in the clinic . The FDA-approved the anti-VEGF agents bevacizumab, aflibercept, and ranibizumab, and have shown good therapeutic results in neovascular AMD, but anti-VEGF agents are limited by the necessity for monthly injections in the clinic and the long-term nature of treatment . Moreover, the high cost of anti-VEGF therapy is a heavy burden for patients . Our study evidence suggests that melatonin may overcome new existing therapeutic obstacles with anti-VEGF agents and offer a novel option for treating neovascular AMD. In conclusion, our study indicates that melatonin inhibits VEGF-induced increases in PDGF-BB expression in EPCs by inhibiting the signaling of VEGFR2, c-Src, FAK, NF-kB and AP-1, all of which appear to effectively inhibit EPC angiogenesis . Thus, melatonin shows promising therapeutic potential, alone and in combination with a VEGF inhibitor, for neovascular AMD. Acknowledgments We would like to thank Suh-Hang Juo of China Medical University for providing guidance on the corneal alkali burn model, and to Iona J. MacDonald of China Medical University for her editing. Supplementary Materials The following supporting information can be download at: Figure S1: Melatonin suppresses tube formation by inhibiting PDGF-BB expression in EPCs. Figure S2: Melatonin suppresses tube formation by inhibiting VEGFR2, c-Src, and FAK expression in EPCs. Figure S3: Melatonin suppresses tube formation by inhibiting NF-kB and AP-1 expression in EPCs. Methodology for the MTT assay, western blot analysis, and luciferase reporter assay are detailed in the Supplementary File. Click here for additional data file. Author Contributions Conceptualization, L.-W.L. and C.-H.T.; Data curation, C.-Y.K.; Formal analysis, S.-F.Y.; Funding acquisition, C.-H.T.; Investigation, C.-Y.L. and Y.-C.F.; Methodology, S.-W.W., C.-Y.K., Y.-C.F., and J.-J.L.; Resources, S.-W.W.; Software, W.-C.H. and T.K.H.; Validation, L.-W.L., W.-C.H. and T.K.H.; Writing--original draft, L.-W.L.; Writing--review & editing, C.-H.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal procedures were approved and performed according to guidance issued by the Institutional Animal Care and Use Committee of China Medical University (Approval no. 2021-174). Informed Consent Statement Not applicable. Data Availability Statement The data generated and analyzed will be made from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A-D) High levels of EPCs and blood vessel markers in AMD retinas were graded by Minnesota Grading System (MGS) scores. Levels of EPC-specific markers (CD34 and CD133) and blood vessel markers (CD31 and VEGF) were analyzed in gene expression profiles of normal retina tissue and neovascular AMD tissue samples downloaded from the eyeIntegration v1.0 database. p < 0.05 compared with the normal group. Figure 2 Melatonin decreases VEGF-induced EPC proliferation, cell migration, and tube formation without cytotoxic effects. (A) EPCs were incubated with melatonin (0.1-1 mM) for 24 h or 48 h, and cell viability was examined using the MTT assay (n = 4). (B) EPCs were incubated with VEGF (100 ng/mL) and melatonin (0.1-1 mM) for 24 h. Cell proliferation (n = 4) was examined by the CCK-8 assay. (C) EPCs were incubated with VEGF (100 ng/mL), and different concentrations of melatonin (0.1-1 mM) for 18 h. Cell migration (n = 3) was examined by the Transwell assay. (D) EPCs were incubated with VEGF (100 ng/mL) and different concentrations of melatonin (0.1-1 mM) for 6 h. The capillary-like structure formation was determined by the tube formation assay (n = 3). * p < 0.05 compared with the control group; # p < 0.05 compared with the VEGF-treated group. Figure 3 Effects of melatonin on VEGF-induced EPC angiogenesis in vivo. (A) Five-day-old fertilized chick embryos (n = 5) were treated with VEGF (100 ng/mL) and different concentrations of melatonin (0.1-1 mM) for 14 days. After treatment, the CAMs were examined by microscopy and photographed. (B-D) Matrigel plugs were treated with PBS (control group) or VEGF (100 ng/mL) with different concentrations of melatonin (0.1-1 mM) and subcutaneously injected into the flanks of nude mice (n = 5). After 7 days, the plugs were photographed, and then hemoglobin levels were quantified and visualized by co-immunofluorescence staining at 20x magnification for CD31, CD34, and CD133 antibodies. * p < 0.05 compared with the control group; # p < 0.05 compared with the VEGF-treated group. Figure 4 Melatonin reduces VEGF-induced EPC migration and tube formation by inhibiting PDGF-BB production. (A) EPCs were incubated with VEGF (100 ng/mL) alone and in combination with melatonin (1 mM) for 24 h. Cell lysates were collected from each treatment condition and from untreated EPCs, and then profiled for proteomes using the Human Angiogenesis Protein Array. (B) Levels of PDGF-BB expression were quantified in each protein array sample. (C) EPCs were incubated with VEGF (100 ng/mL) and melatonin (0.1-1 mM) for 24 h, and PDGF-BB expression was examined by western blot analysis (n = 3). (D,E) EPCs were transfected with PDGF-BB cDNA overnight, then left untreated or were treated with VEGF (100 ng/mL) and melatonin (1 mM) for 24 h, before being examined by the Transwell (n = 3) and tube formation assays (n = 3). (F) Levels of PDGF-BB expression were analyzed in gene expression profile records downloaded from the eyeIntegration v1.0 database for normal retina tissue samples and neovascular AMD tissue samples. * p < 0.05 compared with the control group; # p < 0.05 compared with the VEGF-treated group. Figure 5 Melatonin reduces the VEGF-induced stimulation of EPC migration and tube formation by inhibiting the VEGFR2/c-Src/FAK signaling pathway. (A) Molecular docking software revealed a binding affinity between melatonin and VEGFR2. (B-D) EPCs were incubated with VEGF (100 ng/mL) and different concentrations of melatonin (0.1-1 mM) for 2 h. VEGFR-2, c-Src and FAK phosphorylation was examined by western blot (n = 3). (E,F) EPCs were transfected with VEGFR2 cDNA or treated with FAK or c-Src activators overnight, then left untreated or were treated with VEGF (100 ng/mL) alone and in combination with melatonin (1 mM) for 24 h, before being examined by the Transwell (n = 4) and tube formation assays (n = 4). * p < 0.05 compared with the control group; # p < 0.05 compared with the VEGF-treated group. Figure 6 Melatonin inhibits the VEGF-induced stimulation of EPC angiogenesis by inhibiting NF-kB and AP-1 activation. (A,B) EPCs were incubated with VEGF (100 ng/mL) and different concentrations of melatonin (0.1-1 mM) for 2 h. p65 and c-Jun phosphorylation was examined by western blot (n = 3). (C,D) EPCs were treated with NF-kB or AP-1 activators overnight, then left untreated or were treated with VEGF (100 ng/mL) alone and in combination with melatonin (1 mM) for 24 h, before being examined by the Transwell (n = 4) and tube formation assays (n = 4). (E) EPCs were transfected with the NF-kB or AP-1 luciferase plasmids and then treated with VEGF (100 ng/mL) and different concentrations of melatonin (0.1-1 mM) before determining luciferase activity (n = 4). EPCs were then treated with VEGF (100 ng/mL) and melatonin (1 mM), before undergoing (F) immunofluorescence staining with NF-kB and AP-1 antibodies, or (G,H) a ChIP assay (n = 3). * p < 0.05 compared with the control group; # p < 0.05 compared with the VEGF-treated group. Figure 7 Antiangiogenic effects of melatonin in the corneal alkali burn model. (A) Photos of a normal cornea and an alkali-burned cornea. Stereomicroscopic findings for eyes from mice (n = 6 per group) on days 1, 3, 5, and 7 after treatment with PBS, melatonin (20 mg/kg or 60 mg/kg), or bevacizumab (5 mg/mL). (B,C) At 7 days after the alkali burn injury, corneal stromal thickness was detected by H&E staining and quantified in mice with uninjured corneas, mice with untreated injured corneas, melatonin-treated mice, or bevacizumab-treated mice. (D,E) Levels of CD31, CD34, CD133 and PDGF-BB expression in corneas were subjected to co-immunofluorescence staining and quantified. * p < 0.05 compared with uninjured corneas; # p < 0.05 compared with damaged corneas. Figure 8 The schematic diagram summarizes the proposed mechanism whereby melatonin suppresses VEGF-induced EPC angiogenesis in neovascular AMD. Melatonin suppresses VEGF-induced increases in the production of PDGF-BB, the recruitment of EPCs, and EPC angiogenesis by inhibiting VEGFR2, c-Src, FAK, NF-kB and AP-1 signaling. 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PMC10000468 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050752 cells-12-00752 Article PGRMC1 Ablation Protects from Energy-Starved Heart Failure by Promoting Fatty Acid/Pyruvate Oxidation Lee Sang R. Mukae Moeka Jeong Kang Joo Park Se Hee Shin Hi Jo Kim Sang Woon Won Young Suk Kwun Hyo-Jung Baek In-Jeoung Hong Eui-Ju * Dubey Raghvendra Academic Editor College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Republic of Korea * Correspondence: [email protected] 27 2 2023 3 2023 12 5 75223 1 2023 20 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Heart failure (HF) is an emerging epidemic with a high mortality rate. Apart from conventional treatment methods, such as surgery or use of vasodilation drugs, metabolic therapy has been suggested as a new therapeutic strategy. The heart relies on fatty acid oxidation and glucose (pyruvate) oxidation for ATP-mediated contractility; the former meets most of the energy requirement, but the latter is more efficient. Inhibition of fatty acid oxidation leads to the induction of pyruvate oxidation and provides cardioprotection to failing energy-starved hearts. One of the non-canonical types of sex hormone receptors, progesterone receptor membrane component 1 (Pgrmc1), is a non-genomic progesterone receptor associated with reproduction and fertility. Recent studies revealed that Pgrmc1 regulates glucose and fatty acid synthesis. Notably, Pgrmc1 has also been associated with diabetic cardiomyopathy, as it reduces lipid-mediated toxicity and delays cardiac injury. However, the mechanism by which Pgrmc1 influences the energy-starved failing heart remains unknown. In this study, we found that loss of Pgrmc1 inhibited glycolysis and increased fatty acid/pyruvate oxidation, which is directly associated with ATP production, in starved hearts. Loss of Pgrmc1 during starvation activated the phosphorylation of AMP-activated protein kinase, which induced cardiac ATP production. Pgrmc1 loss increased the cellular respiration of cardiomyocytes under low-glucose conditions. In isoproterenol-induced cardiac injury, Pgrmc1 knockout resulted in less fibrosis and low heart failure marker expression. In summary, our results revealed that Pgrmc1 ablation in energy-deficit conditions increases fatty acid/pyruvate oxidation to protect against cardiac damage via energy starvation. Moreover, Pgrmc1 may be a regulator of cardiac metabolism that switches the dominance of glucose-fatty acid usage according to nutritional status and nutrient availability in the heart. Pgrmc1 heart starvation ischemia metabolism Chungnam National University2022-0651-01 This work was supported by a research fund of Chungnam National University (no. 2022-0651-01). pmc1. Introduction Heart failure is an emerging epidemic, and patients with reduced ejection fraction rates have a mortality rate of >70% . Despite extensive studies on the epidemiology and risk factors, the mortality rate of heart failure remains high . Malnutrition is a known risk factor for myocardial damage . Clinically, individuals are exposed to malnutrition-mediated cardiac risks during surgery, sepsis, and some serious diseases . Currently used drugs for cardiomyopathy, such as angiotensin-converting enzyme inhibitors or beta blockers, reduce vasoconstriction and decrease the risk of death . However, improving the function of the heart itself will provide a more fundamental breakthrough in the treatment of energy-starved heart failure. ATP production is mainly derived from fatty acid oxidation in the heart . Heart failure with hypertension or ischemia is accompanied by decreased cardiac fatty acid oxidation . Similarly, glucose oxidation, another pathway for ATP production, is also suppressed in heart failure . As a failing heart lacks energy due to decreased glucose and fatty acid oxidation, targeting cardiac energy metabolism is the main research focus of many studies . Although subtypes differ between sexes, the overall heart failure risk is comparable between men and women . Some beneficial effects of androgen and estrogen on heart failure have been previously reported . While synthetic progestin is considered to have deleterious effects, the influence of progesterone or canonical progesterone receptors in heart failure is neither beneficial nor deleterious . One of the progesterone receptors, progesterone receptor membrane component 1 (Pgrmc1), has been reported to suppress obesity/diabetes-mediated cardiac lipotoxicity . Pgrmc1 is a non-canonical progesterone receptor associated with reproductive functions, such as decidualization and female fertility . Recent studies have revealed the metabolic function of Pgrmc1, beyond the reproductive relationships, in liver and adipose tissue , focusing on the anabolism of glucose and lipids. Regulation of insulin, a major anabolic hormone, by Pgrmc1 has also been reported in the pancreas . Although Pgrmc1-related anabolisms have been extensively studied, the mechanism of Pgrmc1-related catabolism remains ambiguous. Furthermore, the regulation of cardiac health by Pgrmc1 has been investigated only in the energy-enriched state in diabetes. In this study, we investigated how Pgrmc1-related catabolism affects cardiac health during energy starvation. Based on previous reports on the apoptosis and necrosis of cardiomyocytes during glucose starvation in vivo and in vitro , we used glucose starvation mouse models (72 h fasting) to mimic cardiac ischemia under physiological conditions in this study. Additionally, an adrenergic stimulation model using isoproterenol injection was introduced to induce energy starvation in the heart based on previous studies indicating lowered ATP production from ADP in the isoproterenol model . Unlike the overnutrition state, Pgrmc1 loss increased fatty acid and pyruvate oxidation in the heart during malnutrition. Our results indicated that maintenance of the major energy production pathway protected the Pgrmc1-ablated heart from energy starvation-induced injury. 2. Materials and Methods 2.1. Animals Wild-type (WT) and Pgrmc1 global knockout (PKO) littermate mice (8-week-old; C57BL/6 background) were grown in a pathogen-free facility at Chungnam National University under a standard 12:12 h light:dark cycle and fed standard chow diet with water provided ad libitum. The mice were fasted to starvation, and unexpected deaths during the experiment were recorded to assess the survival rate. Isoproterenol (230 mg/kg, subcutaneous) was injected for two weeks to induce adrenergic heart damage. To observe cardiac pumping in WT and PKO mice, fluorescent dye-labeled (DyLight 680 antibody labeling kit, Thermo Scientific, Waltham, MA, USA, 53056) bovine serum albumin (BSA) was intravenously injected into the mice. After 1 h, the mice were anesthetized and placed in an in vivo imaging system (IVIS; FOBI, Vancouver, BC, Canada). A video was recorded to observe cardiac pumping. Images of cardiac contraction/relaxation were also captured. All animal experiments were approved by the Chungnam Facility Animal Care Committee (CNU-00606) and adhered to their ethical guidelines. 2.2. Gene Expression Omnibus (GEO) Datasets Public datasets (GEO) were used to determine PGRMC1 transcription levels in patients with cardiomyopathy. GSE29819 and GSE36961 datasets were selected, and all patients were included in the analysis. 2.3. Comprehensive Laboratory Animal Monitoring System (CLAMS) CLAMS was used to assess the metabolic status of starved mice. Oxygen consumption (VO2) and carbon dioxide production (VCO2) rates were measured using an Oxymax system (Columbus Instruments, Columbus, OH, USA). Mice were placed at least 50 min before experiment for acclimation. The respiratory exchange ratio (RER) and respiratory quotient (RQ) were calculated as the ratio of VCO2 to VO2. The mice were fasted from midway through the light cycle to midway through the dark cycle. 2.4. RNA Isolation, Reverse Transcription, and Quantitative Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) RNA pellets were collected from the hearts of mice and H9c2 cells using TRIzol, chloroform, and isopropanol. RNA pellet was washed with ethanol and dissolved in diethyl pyrocarbonate-treated water. RNA concentration was measured, and the same RNA amounts for each sample were used for cDNA synthesis using an Excel RT Reverse transcriptase kit (SG-cDNAS100; Smartgene, Daejeon, Republic of Korea). Real-time PCR was carried out using specific primers (Table 1), Excel Taq Q-PCR Master Mix (SG-SYBR-500; Smartgene), and Stratagene Mx3000P (Agilent Technologies, Santa Clara, CA, USA) in a 96-well optical reaction plate. Negative controls containing water instead of the sample cDNA were used in each plate. 2.5. Western Blotting Protein samples were resolved on 8-12% sodium dodecyl sulfate (SDS) polyacrylamide gels (running buffer: 25 mM Tris, 192 mM Glycine, 0.1% SDS, and D.W.). After electrophoresis, the gels were blotted onto a polyvinylidene difluoride membrane (IPVH 00010; Millipore, Burlington, MA, USA) at 350 mA for 1-2 h with the transfer buffer (25 mM Tris, 192 mM Glycine, and 20% (v/v) methanol). Membranes were blocked in 3% BSA and incubated with primary antibodies overnight at 4 degC. Membranes were washed thrice with TBS-T to remove the excess antibodies and incubated overnight at 4 degC with the following secondary antibodies: goat anti-rabbit IgG horseradish peroxidase (HRP) (Catalog #31460) and goat anti-mouse IgG HRP (Catalog #31430; Thermo Fisher Scientific, Waltham, MA, USA) antibodies. After washing thrice with TBS-T, immunoreactive proteins were observed with ECL solution (Eta C Ultra 2.0; Cyanagen, Bologna, Italy) using a ChemiDoc system (Fusion Solo, Vilber Lourmat, Eberhardzell, Germany). The following primary antibodies were used: PGRMC1 (13856; Cell Signaling Technology, Danvers, MA, USA), ribosomal protein lateral stalk subunit P0 (RPLP0; A13633; Abclonal, Woburn, MA, USA), poly(ADP ribose) polymerase (PARP; 9532; Cell Signaling Technology), C/EBP homologous protein (CHOP; #MA1-250; Invitrogen, Waltham, MA, USA), b-actin (sc-47778; Santa Cruz, Dallas, TX, USA), glycolysis antibody sampler kit (8337; Cell Signaling Technology), pAMPK, tAMPK (9957; Cell Signaling Technology), LC3B (L7543, Sigma-Aldrich, St. Louis, MO, USA), and a-tubulin (66031-1-Ig; Proteintech, Rosemont, IL, USA). 2.6. Blood and Plasma Measurements For blood glucose measurement, the tail was snipped, and the blood glucose levels were measured using an Accu-Chek Active kit (Roche, Basel, Switzerland). During necropsy, blood was collected from the IVC. Plasma samples were analyzed to determine the levels of free fatty acids (FFAs; BM-FFA100, Biomax, Planegg, Germany), triglycerides (TGs; TG-1650, Fuji Film, Tokyo, Japan), and total cholesterol (TCHO; TCHO-1450). 2.7. Cell Culture All the cell culture reagents were purchased from Welgene (Gyeongsan, Republic of Korea). H9c2 rat cardiomyocytes were maintained in Dulbecco's modified Eagle's medium (LM001-05; Welgene) supplemented with 5% (v/v) fetal bovine serum (FBS, Punjab, Pakistan), penicillin (100 U/mol), and streptomycin (100 mg/mL). To reflect the plasma profile of mice, cells were incubated with a low-glucose/fatty acid medium (500 mg/L glucose, 110 mM palmitic acid, 220 mM oleic acid) for 24 h. For Pgrmc1 knockdown/overexpression experiments, cells were incubated with Opti-MEM (31985070; Gibco; without FBS) for 0.5 h and treated with the siRNA/plasmid and lipofectamine 2000 (11668027; Thermo Fisher Scientific). The siRNA sequence used was: 5'-CAGUUCACUUUCAAGUAUCA-U-3'. Medium containing FBS was later added after 6 h. 2.8. Cardiac Fibrosis Measurement Tissues were fixed with neutral-buffered formalin, and trimmed tissues were washed with tap water. Tissues were subjected to serial dehydration and embedded in paraffin. The paraffin block was cut (5 mm) using a microtome, and the cut sections were attached to a silane-coated slide. Slides were immersed in xylene overnight and processed using a commercial kit (MST-100T; Biognost, Zagreb, Croatia), according to the manufacturer's protocol, for Masson's Trichrome staining. Regions of interest were observed under a light microscope. 2.9. Terminal Deoxynucleotidyl Transferase-Mediated dUTP Nick End-Labeling (TUNEL) Staining and Immunostaining Frozen tissues were embedded in an optimal cutting temperature compound and cut (8 mm) using a cryostat. Slides were dried overnight and washed with TBS-T. TUNEL assay (11684795910; Roche, Basel, Switzerland) was performed according to the manufacturer's protocol. After 4',6-diamidino-2-phenylindole staining, the region of interest was observed under a fluorescence microscope. For immunostaining, frozen tissue slides were dried overnight and heated in oven (65 degC) for 10 min. Slides were immersed in distilled water and subsequently TBS-T. After blocking with 3% BSA, slides were incubated with primary antibody (CD31, ab56299; Abcam, Cambridge, UK) overnight at 4 degC. The next day, slides were washed with TBS-T and incubated with secondary antibody (A21202, Life Technologies, Carlsbad, CA, USA) for 4 h at room temperature. The region of interest was observed under a fluorescence microscope. 2.10. Statistical Analysis Data are reported as the mean +- standard deviation. Differences between means were analyzed via Student's t-test and one-way analysis of variance followed by Tukey's multiple comparison test using the Graph Pad Software (GraphPad Inc., San Diego, CA, USA). Statistical significance was set at p < 0.05. 3. Results 3.1. PGRMC1 Expression Is Associated with Energy-Starved Cardiomyopathy Using public clinical datasets, we collected data to investigate the relationship between PGRMC1 expression and cardiomyopathy. In GSE29819, both ventricles from patients with dilated cardiomyopathy showed lower PGRMC1 expression levels than those from non-failing donor hearts . In GSE36961, the hearts of patients with dilated cardiomyopathy with left ventricular systolic dysfunction showed decreased PGRMC1 expression levels compared to those of normal individuals . Interestingly, the expression levels of key enzymes involved in fatty acid oxidation and glycolysis were lower in the hearts of patients with dilated cardiomyopathy . Through several in vitro and in vivo experiments, we attempted to delineate the effects of energy starvation on cardiomyocyte health. We induced energy starvation in H9C2 cardiomyocytes and mice via glucose starvation (glucose 0 mg/L, FBS 1%) and fasting (72 h), respectively. As shown in Figure 1B, cells under glucose starvation were predisposed to apoptotic cell death. Furthermore, hearts from mice under starvation (72 h) showed increased protein levels of apoptotic markers (cleaved PARP) and endoplasmic reticulum stress markers (CHOP) compared to those under resting conditions (Con) . PGRMC1 protein expression was markedly suppressed by fasting . These results indicate that PGRMC1 levels are closely related to energy starvation-induced cardiomyocyte injury. 3.2. Loss of PGRMC1 Maintains the Whole-Body Metabolism during Starvation Since there is no information on the physiological profile of PKO mice under starvation, we used CLAMS for comprehensive assessments. In CLAMS, VO2 levels were markedly reduced from 14 h fasting and reached baseline after 20 h fasting in WT mice. In contrast, VO2 levels were generally maintained at high levels in PKO mice during fasting. VCO2 levels showed a similar pattern as the VO2 levels. Levels of VCO2 markedly decreased after 14 h of fasting and reached baseline after 20 h of fasting in WT mice. In contrast, PKO mice maintained high VCO2 levels during fasting . Additionally, the RER (VO2/VCO2) ratios were lower in PKO mice than in WT mice during prolonged fasting . RQ calculation revealed that PKO mice are more likely to consume fat than glucose during prolonged fasting . The heat production of PKO mice was highly maintained during fasting, notably from 14 h fasting, compared to that of WT mice . The physical activity of PKO mice was also maintained during the prolonged fasting period, while that of WT mice was substantially diminished during the same period . When mice were starved for a long period, some died unexpectedly due to an energy deficit. PKO mice were resistant to starvation-induced death compared to WT mice . These results indicate that PKO mice are physiologically resistant to energy starvation. 3.3. Pgrmc1 Loss Increases Fatty Acid/Pyruvate Oxidation and Decreases Starvation-Induced Cardiac Injury To investigate how Pgrmc1 will affect the heart under starvation, WT and PKO mice were starved for 72 h and exposed to cardiac malnutrition. Blood glucose levels were at baseline in both starved WT and PKO mice, showing no difference between the two groups . Plasma lipid profiles increased in starved PKO mice. Notably, plasma FFA and TG levels were significantly higher in starved PKO mice than in starved WT mice . Heart weight (HW) decreased in starved PKO mice, while the ratio of HW per body weight (BW) was similar . Western blotting showed that starved PKO hearts had decreased cleaved PARP levels, which is an apoptotic marker, compared to starved WT hearts . Concordantly, PKO hearts showed seemingly increased cardiac contractions in the IVIS using fluorescence . Most hearts with hypertrophy or failure undergo metabolic alterations characterized by decreased fatty acid oxidation . Fatty acid oxidation accounts for almost 70% of cardiac energy production . PKO hearts under starvation conditions showed significantly increased expression levels of mitochondrial fatty acid oxidation enzymes (carnitine palmitoyltransferase 2 (Cpt2) and very long-chain acyl-CoA dehydrogenase (Vlcad)) and peroxisomal fatty acid oxidation enzyme (acyl-CoA oxidase 1 (Acox1)) compared to WT hearts under starvation conditions . Glycolysis is a rapidly induced cardiac metabolism process associated with heart failure . PKO hearts under starvation had markedly decreased protein levels related to glycolysis (hexokinase (HK)-1, HK2, and pyruvate kinase M2 (PKM2)) . Glucose oxidation accelerates cardiac function recovery following myocardial injury . Likewise, dichloroacetate, a pyruvate dehydrogenase (PDH) activator, increases myocardial efficiency . Cardiac PDH was higher in PKO than in WT plants under starvation conditions . These results indicate that starved PKO hearts increase their main energy production and fatty acid/pyruvate oxidation and do not need to be exposed to metabolic alterations. As plasma FFA levels were highly maintained in PKO mice, it should be tested whether these metabolic alterations are influenced by the levels of physiologically induced substrates. To limit the influential factors in vivo, we introduced H9c2 rat cardiomyocytes and knocked down Pgrmc1 by siRNA. The cells were exposed to low glucose (500 mg/L) and fatty acids (palmitic acid (110 mM)/oleic acid (220 mM)). PGRMC1 protein levels were lower in the PK (Pgrmc1 knockdown) group than in the CK (control knockdown) group . Cleaved PARP levels were lowered in PK group . Metabolic alterations followed in vivo results. The mRNA expression levels of Cpt2, Vlcad, and Acox1 were higher in the PK group than in the CK group . The protein levels of HK1 and HK2 decreased in the PK group . PDH levels increased in the PK group . Collectively, in vitro Pgrmc1 knockdown in low-energy cardiomyocytes induced fatty acid/pyruvate oxidation and decreased cellular injury. To investigate whether metabolic alterations in the PK group increased energy production compared to that in the CK group under energy deficit, we introduced a seahorse flux analyzer system to measure cellular respiration. H9c2 cells were knocked down and starved in a medium containing low glucose (500 mg/L) and fatty acids (palmitic acid (110 mM)/oleic acid (220 mM)). In the mitochondrial stress test, the PK group had a higher maximal respiration rate than that of the CK group . We also measured the mitochondrial fusion/fission gene expression levels to assess the mitochondrial balance . PKO hearts had a mildly increased fission gene (dynamin-related protein 1; Drp1) expression level compared to WT hearts . These results confirm that fatty acid/pyruvate oxidation by PK increases energy production even under reduced glycolysis. 3.4. AMPK Activation Is Associated with Pgrmc1-Induced Metabolic Alteration in the Heart We investigated the possible mechanism of metabolic alterations induced by Pgrmc1. AMPK is a multi-functional protein kinase involved in the oxidation and uptake of metabolites . Western blotting revealed that starved PKO hearts had increased phosphorylated AMPK (pAMPK) levels and decreased total AMPK (tAMPK) levels. Starved PKO hearts showed a higher p/t AMPK ratio than WT hearts . In H9c2 cells, PK cells showed higher pAMPK and lower tAMPK levels than CK cells. Concordantly, PK cells showed an increased p/t AMPK ratio compared to that in CK cells . Metabolic effects of AMPK activation and inactivation in cardiomyocytes were assessed. PGRMC1 levels were not directly regulated by AMPK activation because treatments with 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR; AMPK activator) and compound C (Com C; AMPK inactivator) suppressed PGRMC1 expression. AMPK phosphorylation was increased by AICAR and decreased by Com C treatment . HK1 levels were lowered by AICAR, whereas HK2 and PKM2 levels were increased by Com C. PDH levels were decreased by Com C . In contrast, the expression levels of fatty acid oxidation enzymes were markedly increased by AICAR treatment . Com C treatment decreased Cpt2 and Vlcad expression levels . In summary, AMPK activation was related to the induction of fatty acid/pyruvate oxidation and decreased glycolysis. As Pgrmc1 loss increased AMPK activation and showed similar metabolic alterations to AMPK-activated cells, AMPK may be linked to metabolic modulation by PGRMC1 in starved hearts. 3.5. Pgrmc1 Ablation Protects the Heart from Isoproterenol-Induced Damage We introduced isoproterenol cardiac injury model according to previous studies . Mice were injected with isoproterenol (five times, total 230 mg/kg, 14 days) and sacrificed . Masson's trichrome staining revealed that isoproterenol-WT hearts showed large positive areas with fibrosis . In contrast, isoproterenol-PKO hearts showed decreased fibrotic areas compared with WT hearts . Transforming growth factor-beta mRNA expression levels decreased in isoproterenol-PKO hearts . As heart failure markers, mRNA expression levels of actin alpha 1 and brain natriuretic peptide were decreased in isoproterenol-PKO hearts compared to those in WT hearts . In metabolic assessments, isoproterenol-PKO hearts showed higher levels of fatty acid oxidation enzymes (Cpt2) than isoproterenol-WT hearts . Furthermore, isoproterenol-PKO hearts had decreased glycolysis enzyme levels and increased PDH levels. Additionally, isoproterenol-PKO hearts showed an increased p/t ratio of AMPK . Hence, isoproterenol-PKO hearts had altered cardiac metabolism, such as fasting-PKO cardiac metabolism, increased fatty acid/pyruvate oxidation and AMPK phosphorylation, and decreased glycolysis. Maintenance of the ATP-producing pathway, i.e., fatty acid/pyruvate oxidation, may provide cardioprotection under ischemic injury. 4. Discussion Ischemic heart failure is prevalent worldwide . Beyond traditional surgery, various methods using protein, cell, and gene therapeutics have been suggested for treatment . Notably, several regulators of cardiac metabolism have been identified . The heart relies heavily on long-chain fatty acids and utilizes glucose low-proportionally for energy production in the normal state . Both fatty acid oxidation and glucose oxidation produce acetyl-CoA, which directly participates in the tricarboxylic acid cycle and electron transport chain and accounts for 95% of myocardial ATP production . In failing hearts, fatty acid availability substantially affects the myocardial function and efficiency . Additionally, pyruvate oxidation, leading to the production of acetyl-CoA from glucose-derived pyruvate, is limited in heart failure, resulting in impaired ATP production . Thus, failing hearts are etiologically or resultantly associated with impaired energy production via fatty acid/pyruvate oxidation. During cellular stress, AMPK phosphorylation downregulates fatty acid synthesis but upregulates fatty acid oxidation . Although fatty acid oxidation itself can suppress pyruvate oxidation, AMPK activation increases glycolysis and pyruvate oxidation. Due to its diverse effects, whether AMPK improves or deteriorates the cardiac health may differ according to the physiological state of the patient . AMPK has been reported to increase overall ATP production to respond to the energy demand and provide tolerance against cardiac ischemia . When the hearts were exposed to fasting or isoproterenol-induced energy starvation, PKO increased AMPK phosphorylation. Catabolic activation by PKO differed according to metabolic pathways; fatty acid and pyruvate oxidation increased, but glycolysis decreased. Fatty acid oxidation takes place predominantly in the mitochondria and peroxisomes in less magnitude . Mitochondrial fatty acid oxidation enzymes , namely Cpt2 and Vlcad, and the peroxisomal fatty acid oxidation enzyme Acox1 increased in PKO hearts. The high availability of plasma fatty acids in PKO may influence catabolic processes. However, exposure to the same amount of fatty acids in in vitro experiment also increased fatty acid oxidation in PK cells. Conversely, Pgrmc1-overexpressing (POE) cells exhibited decreased fatty acid oxidation . Hence, an increase in the fatty acid oxidation pathway affects cardiac energy metabolism in PKO. Paradoxically, PKO hearts have decreased levels of glycolytic enzymes, hexokinases, and pyruvate kinase but increased PDH . When cells are exposed to the same amounts of glucose and fatty acids, PK cells still increase pyruvate oxidation but suppress glycolysis. Similarly, POE cells showed a mild increase in glycolysis . We speculated that the lactate source must be induced to increase pyruvate substrate and pyruvate dehydrogenase in limited sources from glycolytic products. Our results (data not shown) also showed the induction of lactate dehydrogenase in starved PKO hearts. Further studies on the regulation of lactate metabolism by Pgrmc1 should be performed. Glycolysis only accounts for <10% , while the oxidation of fatty acids (50-70%) and pyruvate (20-40%) comprises the majority of cardiac ATP production. Hence, starved PKO hearts may have increased overall ATP production. Mechanistically, PKO hearts showed increased AMPK phosphorylation, and AMPK inhibitor (Com C) treatment resulted in the opposite cardiac metabolism pattern compared to that of PKO. In line with this, AMPK activator (AICAR) treatment showed a cardiac metabolism pattern similar to that of PKO. Concordantly, PKO-altered cardiac energy metabolism may be linked to AMPK phosphorylation during cardiac injury. We also measured the cardiac autophagy, as AMPK is an autophagy promoter , but observed significantly down-regulated LC3B levels in PKO hearts. As Pgrmc1 is an autophagy promoter , cardiac autophagy was mainly affected by Pgrmc1 compared to AMPK. This is in accordance with our results, as autophagy is up-regulated in ATP-depleted and ischemic hearts . We insist on the interpretation of conflicting metabolic alterations and functions of PKO hearts in light of a previous study. In our previous study, PKO hearts in diabetic conditions showed increased TG and fatty acyl-CoA accumulation , leading to lipotoxicity. However, TG deposits play an ATP-providing role , and fatty acyl CoA is directly related to oxidative phosphorylation in the heart . In contrast to overnutrition hearts, the large pool of lipids in PKO can be the ATP pool for energy-deficient hearts. Additionally, in our previous study, cardiac glycolysis was induced only in overnutrition PKO and slightly decreased in normal PKO hearts . In the energy-deficient state, glycolysis was significantly decreased in PKO hearts. In contrast, fatty acid oxidation was decreased in normal and overnutrition PKO hearts but increased in malnutrition PKO hearts. We concluded that cardiac metabolic alteration by Pgrmc1 depends on glucose availability. In re-fed and diabetic mice, blood glucose levels were approximately 200 mg/dL , which were higher than those in starved mice (approximately 60 mg/dL). Pgrmc1 may be a physiological switch that regulates the preference of cardiac substrates for ATP production depending on the body's nutrition. In energy-deficit conditions, Pgrmc1 reduces oxidation of fatty acids/pyruvates, thereby limiting ATP production in the heart. The failing heart possesses a nearly 30% ATP volume and reduces the ATP-supplementing flux from the reserve (creatine kinase) by 50% compared to the normal heart . ATP depletion in the failing heart directly leads to contractile dysfunction because continuous ATP production/turnover is necessary for cardiac function . Fatty acid oxidation is the major cardiac ATP-producing pathway, but it suppresses glucose oxidation, as per the Randle cycle . Since glucose oxidation is a much more efficient ATP-production and less-oxygen-consuming pathway than fatty acid oxidation , its activation is therapeutically effective in a failing heart . The fatty acid oxidation inhibitor etomoxir has been reported to exert cardioprotective effects by switching from energy metabolism to glucose oxidation . However, adverse effects of fatty acid oxidation inhibition can also be observed in experimental/clinical reports . Based on our results, Pgrmc1 inhibition increases both fatty acid and pyruvate oxidation and improves overall ATP production during energy starvation. Therefore, improvement in ATP-production via a Pgrmc1 inhibitor can be used as a novel therapeutic approach for energy-starved failing hearts. Additionally, PKO hearts reduced CD31 abundance in immunostaining . This result is of clinical importance, as CD31 levels are markedly observed in the necrotic myocardium of deceased patients under ischemic heart disease . Furthermore, CD31 blockade reduces damage in ischemia/reperfusion heart injury . As Pgrmc1 promotes cellular processes of microvascular endothelial cells of the brain , further study is expected regarding Pgrmc1 and the cardiovascular system. Acknowledgments This work was supported by the NRF (National Research Foundation of Korea) Grant funded by the Korean Government (NRF-2019-Global Ph.D. Fellowship Program). Supplementary Materials The following supporting information can be downloaded at: Figure S1. IVIS monitoring of WT and PKO mice. Figure S2. Cardiac autophagy, mitochondrial fusion/fission, and vascularization enzyme levels. Figure S3. Influence of Pgrmc1 overexpression in cardiac metabolism. Click here for additional data file. Author Contributions Conceptualization, S.R.L. and E.-J.H.; methodology, S.R.L., M.M., K.J.J. and I.-J.B.; software, S.R.L., M.M., K.J.J. and I.-J.B.; validation, S.R.L., M.M. and K.J.J.; formal analysis, S.R.L., M.M., K.J.J. and I.-J.B.; investigation, S.R.L., M.M., K.J.J., S.H.P., H.J.S., S.W.K., Y.S.W. and H.-J.K.; resources, Y.S.W., H.-J.K., E.-J.H. and I.-J.B.; data curation, S.R.L. and E.-J.H.; writing--original draft preparation, S.R.L. and E.-J.H.; writing--review and editing, S.R.L. and E.-J.H.; visualization, S.R.L. and E.-J.H.; supervision, E.-J.H.; project administration, E.-J.H.; funding acquisition, E.-J.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal experiments were approved by the Chungnam Facility Animal Care Committee (CNU-00606) and adhered to their ethical guidelines. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Progesterone receptor membrane component 1 (PGRMC1) expression is associated with energy-starved heart failure. Public Gene Expression Omnibus (GEO) datasets were used for analysis. Patients data for analyses were from 12 non-failing hearts and 14 dilated cardiomyopathy cases in one dataset (GSE29819) and from 39 normal and 106 hypertrophic cardiomyopathy cases in another dataset (GSE36961). (A) mRNA expression levels of PGRMC1 (GSE29819 and GSE36961) and metabolic enzymes (GSE36961) were analyzed. (B) Terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) immunostaining of H9C2 cells in a growth medium (Con; glucose 4500 mg/L, 5% fetal bovine serum (FBS)) and starvation medium (glucose 0 mg/L, 1% FBS). Notably, 4',6-diamidino-2-phenylindole (DAPI) was used to stain the nucleus control. (C) Western blotting analysis and quantification of the expression levels of PGRMC1, poly(ADP ribose) polymerase (PARP), cleaved PARP (Cl. PARP), and C/EBP homologous protein (CHOP) in hearts of resting and 72-h-starved mice. Ribosomal protein lateral stalk subunit P0 (RPLP0) was used as an internal control. Five mice from each group were used for the experiment. Student's t-test was used for analysis. Values represent the mean +- standard deviation (SD). * p < 0.05. Figure 2 Pgrmc1 knockout (PKO) protects the heart from energy starvation-induced metabolic suppression. (A) Oxygen consumption (VO2; l/kg/h) and carbon dioxide production (VCO2; l/kg/h). (B) Respiratory exchange ratio (RER) was calculated as VCO2/VO2. (C) Respiratory quotient (RQ) was calculated as the proportion of VCO2 to VO2. (D,E) Heat generation and activity measurements. Comprehensive lab animal monitoring system (CLAMS) was adopted for all assessments. Mice (wild-type (WT); n = 6, PKO; n = 8) were fasted during the tests. Student's t-test was used for analysis. (F) Survival rate of WT (n = 9) and PKO (n = 5) mice during fasting. Mice under fasting died spontaneously. Values represent the mean +- SD. * p < 0.05. Figure 3 PKO increases fatty acid/pyruvate oxidation and restrains cardiac injury under energy starvation. (A) Levels of blood glucose (mg/dL), plasma free fatty acids (FFAs; mM), plasma triglycerides (TGs; U/I), and plasma total cholesterol (TCHO; U/I) in starved WT and PKO mice. (B) Heart weight (HW), body weight (BW), and HW/BW ratio in starved WT and PKO mice. (C) Western blotting analysis and quantification of the expression levels of PGRMC1, PARP, and Cl. PARP in the starved hearts of WT and PKO mice. b-Actin was used for an internal control. (D) mRNA expression levels of fatty acid oxidation enzymes in the starved hearts of WT and PKO mice. Rplp0 was used as an internal control. (E) Western blotting analysis and quantification of the levels of glycolysis and pyruvate oxidation enzymes in the starved hearts of WT and PKO mice. b-Actin was used as an internal control. Mice used for the experiments: 8 (WT) and 4 (PKO). Student's t-test was used for analysis. Values represent the mean +- SD. * p < 0.05. Figure 4 Pgrmc1 knockdown in cardiomyocytes reduces cardiac damage with induction of fatty acid/glucose oxidation in a low-glucose medium supplemented with fatty acids. (A) Western blotting analysis and quantification of the levels of PGRMC1, PARP, and cleaved PARP in H9c2 cells treated with the control small interfering RNA (siRNA) (control knockdown, CK) and Pgrmc1 siRNA (Pgrmc1 knockdown, PK). b-Actin was used as an internal control. (B) mRNA expression levels of fatty acid oxidation enzymes in H9c2 cells treated with the control siRNA (CK) and Pgrmc1 siRNA (PK). Rplp0 was used as an internal control. (C) Western blotting analysis and quantification of the levels of hexokinase (HK)-1, HK2, pyruvate kinase M2 (PKM2), and pyruvate dehydrogenase (PDH) in H9c2 cells treated with the control siRNA (CK) and Pgrmc1 siRNA (PK). b-Actin was used as an internal control. (D) Oxygen consumption rate (OCR) of CK and PK cells during mitochondrial stress test. ATP production and maximal respiration rates were calculated by changing the OCR after oligomycin and rotenone/antimycin (Rot/Ant) treatments, respectively. Cells were incubated in a medium containing low glucose (500 mg/L) and fatty acids (palmitic acid (110 mM)/oleic acid (220 mM)). All experiments were repeated at least three times. Student's t-test was used for analysis. Values represent the means +- SD. * p < 0.05. Figure 5 Loss of Pgrmc1 increases the phosphorylation of AMP-activated protein kinase (AMPK) in the heart under energy starvation. (A) Western blotting analysis and quantification of the levels of pAMPK, tAMPK, and p/t AMPK in starved hearts of WT and PKO mice and H9c2 cells treated with the control siRNA (CK) and Pgrmc1 siRNA (PK). b-Actin was used as an internal control. Mice used for experiments were eight (WT) and four (PKO) in number. Cells were incubated in a medium containing low glucose (500 mg/L) and FAs (palmitic acid (110 mM)/oleic acid (220 mM)). (B) Western blotting analysis and quantification of the levels of PGRMC1, pAMPK, tAMPK, p/t AMPK, HK1, HK2, PKM2, and PDH in H9c2 cells treated with AICAR (200 mM) and Com C (5 mM). b-Actin was used for an internal control. (C) mRNA expression levels of fatty acids oxidation enzymes in H9c2 cells treated with 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR; 200 mM) and compound C (Com C; 5 mM). Rplp0 was used as an internal control. All experiments were repeated at least three times. Student's t-test was used for analysis. Values represent the mean +- SD. * p < 0.05. Figure 6 PKO protects against cardiac injury induced by isoproterenol treatment. (A) Experimental scheme for isoproterenol-induced cardiac injury. Isoproterenol was injected five times (total 230 mg/kg) via a subcutaneous injection for two weeks. (B) Masson's Trichrome staining of isoproterenol-injected WT and PKO hearts. Cardiac fibrosis was calculated by the ratio of blue area to brown area. Scale bar: 600 mm. (C) mRNA expression levels of transforming growth factor (Tgf)-b in isoproterenol-injected WT and PKO hearts. Rplp0 was used as an internal control. (D) mRNA expression levels of heart failure markers, i.e., actin alpha 1 (Acta1) and brain natriuretic peptide (Bnp), in isoproterenol-injected WT and PKO hearts. Rplp0 was used as an internal control. (E) mRNA expression levels of fatty acid oxidation enzymes, carnitine palmitoyltransferase 2 (Cpt2), very long-chain acyl-CoA dehydrogenase (Vlcad), and acyl-CoA oxidase 1 (Acox1), in isoproterenol-injected WT and PKO hearts. Rplp0 was used as an internal control. (F) Western blotting analysis and quantification of the levels of pAMPK, tAMPK, p/t AMPK, HK1, HK2, PKM2, and PDH in isoproterenol-injected hearts of WT and PKO mice. b-Actin was used as an internal control. Mice used for experiments were six (isoproterenol-WT) and six (isoproterenol-PKO) in number. Student's t-test was used for analysis. Values represent the mean +- SD. * p < 0.05. cells-12-00752-t001_Table 1 Table 1 Primers used for qRT-PCR. Gene Name Upper Primer (5'-3') Lower Primer (5'-3') Species Cpt2 CAG CAC AGC ATC GTA CCC A TCC CAA TGC CGT TCT CAA AAT Mouse Vlcad TAT CTC TGC CCA GCG ACT TT TGG GTA TGG GAA CAC CTG AT Mouse Acox1 TTG GAA ACC ACT GCC ACA TA AGG CAT GTA ACC CGT AGC AC Mouse Tgfb GAC GTC ACT GGA GTT GTA CG GGT TCA TGT CAT GGA TGG TG Mouse Anp CCA TAT TGG AGC AAA TCC TGT G CGG CAT CTT CTC CTC CAG GT Mouse Bnp GGG AGA ACA CGG CAT CAT TG ACA GCA CCT TCA GGA GAT CCA Mouse Mfn2 GCC AGC TTC CTT GAA GAC AC GCA GAA CTT TGT CCC AGA GC Mouse Drp1 AGA AAA CTG TCT GCC CGA GA GCT GCC CTA CCA GTT CAC TC Mouse Cpt2 ACT AAG AGA TGC TCC GAG GC GCA GAG CAT ACA AGT GTC GG Rat Vlcad TGA CCC TGC CAA GAA TGA CT GTC ATG CAT GCC CAC AAT CT Rat Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000469 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050674 healthcare-11-00674 Perspective A Summary of Current Guidelines and Future Directions for Medical Management and Monitoring of Patients with Cystinuria Azer Sarah M. 1 Goldfarb David S. 12* Shiri Rahman Academic Editor 1 Department of Medicine, NYU Grossman School of Medicine, New York, NY 10016, USA 2 NYU Langone Medical Center, Nephrology Section, New York Harbor VA Healthcare System, New York, NY 10010, USA * Correspondence: [email protected]; Tel.: +1-212-686-7500 (ext. 3877); Fax: +1-212-951-6842 24 2 2023 3 2023 11 5 67404 12 2022 17 2 2023 20 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Cystinuria is the most common genetic cause of recurrent kidney stones. As the result of a genetic defect in proximal tubular reabsorption of filtered cystine, increased urine levels of the poorly soluble amino acid result in recurrent cystine nephrolithiasis. Recurrent cystine stones not only adversely affect the quality of patients suffering from cystinuria but also may result in chronic kidney disease (CKD) from recurrent renal injury. Thus, the mainstay of medical management revolves around prevention of stones. Recently published consensus statements on guidelines for managing cystinuria were released from both the United States and Europe. The purpose of this review is to summarize guidelines for medical management of patients with cystinuria, to provide new insight into the utility and clinical significance of cystine capacity--an assay for monitoring cystinuria, and to discuss future directions for research on treatment of cystinuria. We discuss future directions, including the potential use of cystine mimetics, gene therapy, V2-receptor blockers, and SGLT2 inhibitors, topics which have not appeared in more recent reviews. It is notable that in the absence of randomized, controlled trials, the recommendations cited here and in the guidelines are based on our best understanding of the disorder's pathophysiology, observational studies, and clinical experience. cystine/metabolism genetics kidney calculi nephrolithiasis renal aminoaciduria urolithiasis This research received no external funding. pmc1. Introduction Cystinuria is a rare autosomal recessive genetic disease that impairs reabsorption of cystine and dibasic amino acids (ornithine, lysine, arginine) by the proximal tubule of the kidney and epithelial cells of the gastrointestinal tract. It occurs because of mutations in SLC3A1 and SLC7A9 genes that encode the components of the cystine transporter. SLC7A9 encodes the functional amino acid transporter b0,+AT, which transports neutral and dibasic amino acids. SLC3A1 encodes rBAT, a trafficking protein that helps direct the b0,+AT transporter to the apical membrane of proximal tubular epithelial cells. Mutations in either SLC3A1 or SLC7A9 lead to defective reabsorption and intra-tubular and urinary accumulation of cystine and dibasic amino acids . Increased urine levels of poorly soluble cystine are of clinical significance as they result in recurrent cystine nephrolithiasis. While rare, the disorder accounts for 1% of nephrolithiasis in adults and 7% in children . Recurrent cystine stones not only adversely affect the quality of patients suffering from cystinuria but also may result in chronic kidney disease (CKD) from recurrent renal injury . Thus, the mainstay of medical management revolves around prevention of stones. Recently published consensus statements on guidelines for managing cystinuria were released from groups in both the United States and Europe . The purpose of this review is to summarize guidelines for medical management of patients with cystinuria, to provide new insight into the utility and clinical significance of cystine capacity--an assay for monitoring cystinuria, and to discuss future directions for research on treatment of cystinuria. Such future directions include the potential use of cystine mimetics, gene therapy, V2-receptor blockers, and SGLT2 inhibitors, topics which have not appeared in more recent reviews. Other reviews which summarize discussions of genetics and pathophysiology are available. We concentrate here on the recent guidelines and newer topics as well . 2. Treatment 2.1. Conservative Management Medical management of cystinuria begins with a series of core conservative measures aimed at stone prevention--high fluid intake, minimizing intake of dietary sodium and animal protein, and urinary alkalinization . Patients should consume enough fluids to maintain 24-h urine cystine concentrations of less than 250 mg/L (1 mmol/L), usually equating to greater than 3 L urine output each day in adults . Through a mechanism that is poorly understood, dietary sodium restriction has been shown to decrease levels of cystine in the urine . It is therefore recommended to decrease sodium intake to less than 2.5 g/day or less than 100 mEq of sodium/day by US guidelines, or about 6 g of NaCl/day or 1 to 1.5 mEq/kg, by European guidelines . Restriction of consumption of dietary animal protein also lowers levels of cystine excretion by reducing the intake of cystine and its precursor, methionine. In addition, less animal protein intake reduces the intake of protons, yielding higher urinary pH and increased cystine solubility . There is no consensus as to how much to restrict animal protein, with suggestions of less than 8 ounces/day and less than 1 g/kg ideal body weight . The former may seem high and the latter low, with the message of both guidelines being that less animal protein is preferred. There are also concerns raised in the pediatric population regarding the effect of animal protein restriction on growth, so significantly limiting animal protein consumption in this population is generally not advised . Urinary alkalinization is also recommended to increase urinary cystine solubility . Potassium citrate, with 40-80 mEq per day divided into two or three doses, is recommended as a first-line agent to reach the goal urinary pH of 7.0 or up to 8.0 . The European Association of Urology guidelines on urolithiasis suggests that going as high as 8.5 may be appropriate . The guidelines offer slightly different ranges. We aim initially for values greater than 7.0 and further increase if stone growth is persistent. The increased risk of calcium phosphate nephrolithiasis with higher urinary pH is often discussed but rarely seen . Alkalinization of the urine increases citrate excretion, which, in turn, inhibits calcium stone formation . We postulate that the lack of randomized control trials leads to the differences in values recommended when comparing both consensus statements. Furthermore, while there are studies that demonstrate decreased urinary cystine levels with alterations of these parameters, there currently are no studies that demonstrate decreased incidence of cystine nephrolithiasis with modification of dietary sodium and animal protein or urinary alkalinization . Nevertheless, given the effects on urine chemistry, these are reasonable recommendations, though strict patient adherence to the above parameters is often challenging. 2.2. Pharmacotherapy Therapy for cystinuria should be escalated in a stepwise fashion, with pharmacotherapy with cystine binding thiol drugs (CBTD) added for patients who continue to have recurrent cystine nephrolithiasis despite implementation of and adherence to conservative therapy . These drugs, alpha-mercaptopropionylglycine (tiopronin) and D-penicillamine, work through the reduction of the disulfide bond of cystine, yielding a more soluble drug-cysteine complex and reducing free urinary cystine levels . The use of CBTDs has been demonstrated to be effective in reducing cystine stone growth, new stone formation, and incidence of urologic intervention in retrospective studies . However, their use is limited to cases refractory to conservative therapy given their high cost, adverse effect profile, including drug sensitivity reactions, nephrotic range proteinuria secondary to membranous nephropathy, and very rare liver abnormalities and hematologic disturbances, such as neutropenia and thrombocytopenia . Of note, the U.S. Food and Drug Administration (FDA) recently removed a recommendation to monitor complete blood counts and liver function tests when administering tiopronin. Oral vitamin B6 is sometimes recommended for patients on CBTDs to prevent pyridoxine deficiency . Recent data suggest that in vitro tiopronin is more effective at more alkaline pH values. Although this effect has not been demonstrated in people because of a lag in getting urine from the bladder, we recommend that all patients taking CBTDs also remain on alkali regardless of their clinical status . Tiopronin is currently not widely available outside the United States. Early literature demonstrated decreased incidence of adverse effects with tiopronin compared with penicillamine , thus it is generally considered the first-line agent. The starting dose of tiopronin is 15 to 40 mg/kg/day, which generally equates to about 600 to 900 mg daily, divided into three doses . No maximal dose is cited. The average dose in clinical trials has been about 800 mg/d. Higher doses may be appropriate if stone formation persists. However, a recent study on 442 patients with cystinuria on CBTDs in France demonstrated a similar incidence of adverse effects with both drugs . The starting dose of D-penicillamine is 20 to 30 mg/kg/day, around 500 to 1500 mg/day in adults, divided into four doses. Kidney stones, regardless of composition, negatively affect health-related quality of life. Cystine stone formers are more frequent and severe stone formers compared with non-cystine stone formers, resulting in a greater, direct effect on the quality of life in cystinuria . In a recent study, we showed that patients taking tiopronin generally had a better quality of life than patients with cystinuria not taking CBTDs . 3. Surveillance Recommended surveillance for patients with cystinuria focuses on monitoring urine and serum chemistries, periodic renal imaging, and screening of family members. Both American and European guidelines recommend obtaining a 24 h urine sample upon initiation of therapy and annually thereafter in patients with stones to monitor the effectiveness of therapies implemented. These samples should be monitored for urine volume, pH, sodium, and creatinine. Spot urine testing on freshly voided samples for pH, the presence of crystalluria, and specific gravity can be helpful in the clinic. Self-monitoring and reporting of at-home measurements of urine pH and specific gravity are also desirable. Measurement of protein/creatinine ratios is appropriate for patients on CBTDs, with history of frequent urologic interventions, or chronic kidney disease (CKD). Monitoring of 24 h urine cystine concentrations is also recommended with the goal concentration of less than 250 mg/L. However, the measurement is consistently noted to have inherent flaws . Most frequently reported is the inability of the assay to differentiate between cystine and the cystine-thiol drug complex, lending to inaccurate measurements in patients on CBTDs . However, even in patients not on CBTDs, measurements are still not reliable, given how variable the solubility of urinary cystine is at different pH values. A solid phase assay, called cystine capacity, has been proposed as a more reliable method for quantifying urine cystine levels . The assay works through the addition of a known amount of solid cystine to patient urine samples, which are then spun for 48 h at 37 degC, and the crystals harvested. In undersaturated urine, the crystals will dissolve, and the urine is said to have a "positive" capacity as it dissolves more of the solid cystine with less solid cystine recovered. Supersaturated urine has a "negative" capacity as the solid cystine grows, taking cystine up from the urine, with more solid cystine recovered . Studies have demonstrated the accuracy of cystine capacity in the presence of CBTDs and less urinary supersaturation in patients on CBTDs, as demonstrated by more-positive or less-negative capacities . Only recent literature has studied cystine capacity relative to stone events. Therefore, its sensitivity and specificity as a predictor of clinical outcomes are uncertain. A recent study on 48 patients with cystinuria demonstrated significantly increased cystine capacity in patients without stone events when compared to patients with stone events, with a strong inverse correlation between cystine capacity and stone activity . Similarly, an ongoing study has preliminary data released on 26 patients with cystinuria enrolled in the Rare Kidney Stone Consortium. Patients with positive cystine capacity were found to have significantly higher urine volumes, lower 24 h urine cystine excretion levels, and higher urine pH. Additionally, patients with positive cystine capacity were found to have a significantly lower incidence of stone events--defined as a development of a new stone, urologic stone removal, and stone passage without intervention . Overall, cystine capacity appears to be a more reliable and accurate way to monitor patients with cystinuria and assess their response to therapy. A recent study demonstrated liquid chromatography/mass spectroscopy may be superior for measurement of cystine-drug complexes . Additionally, both American and European guidelines recommend periodic kidney imaging with either computed tomography (CT) or ultrasonography at least annually in patients with stone events, with a frequency determined on a case-by-case basis. While CT is more sensitive, ultrasonography is generally preferred to minimize exposure to radiation, especially in the pediatric population . Screening for cystinuria in siblings of patients with cystinuria is also universally recommended. American guidelines also advise at least yearly measurement of serum creatinine in all patients with cystinuria to monitor for the development of CKD . European guidelines advise that patients self-monitor urinary pH with urine dipsticks, test strips, or electronic devices to ensure adequate alkalinization . 4. Future Directions While recent literature on cystinuria has helped shed light on already established therapeutics and methods of surveillance, treatment options have generally not changed over the past few decades. Despite challenges in adherence to conservative measures and pharmacotherapy with CBTDs due to adverse effects, there remains a paucity of clinical trials testing new pharmacotherapeutic options in humans. A recent proposal suggests that glucosuria may interfere with the cystine bond that precipitates cystine stones in the urine. Thus, a phase 2 clinical trial is underway to test the efficacy of dapagliflozin, an inhibitor of the proximal tubule's sodium-glucose cotransporter 2 (SGLT-2), in patients with cystinuria . Time and further studies will reveal whether dapagliflozin or other SGLT-2 inhibitors may serve as potential treatment options for patients with cystinuria. Tolvaptan, which blocks the effect of vasopressin by binding to the V2 receptor in the collecting duct, prevented cystine stone growth through increased fluid intake and urine volume in cystinuric mice . A pilot clinical trial is currently underway testing the effect of this aquaretic on cystine capacity in urine from patients with homozygous cystinuria . Another recent study demonstrated that orally administered alpha-lipoic acid inhibited cystine stone growth in Slc3a1 knockout mice by increasing the solubility of cystine . The mechanism of action of this readily available, over-the-counter supplement is not known. However, a pilot clinical trial is now ongoing to test its effects on cystinuric patients . A suggestion of benefit was offered by a case report on two pediatric patients . An approach that has been proposed as a promising area for new therapeutics to treat cystinuria is gene therapy--a method by which genetic material is changed, removed, or added into human cells to treat the disease . Cystinuria appears to be an ideal candidate for gene therapy given its known and established monogenic basis, the localized expression of defective cystine transporter by cells of the proximal tubule, and the likelihood that even partial reduction in tubular cystine wasting would have a large impact on stone events clinically . Whether this approach could be used for both mutations in SLC3A1 and SLC7A9 or how these specific genes will be targeted is not yet known. Another innovative approach that has demonstrated efficacy for decreasing cystine stone burden in animal models is the inhibition of cystine stone growth through the use of cystine-mimetic agents. The concept was introduced by an in vitro study using atomic force microscopy (AFM) to reveal decreased growth velocity of cystine stones through binding of cystine-mimetic agents, such as cystine dimethyl ester (CDME), to cystine stone surfaces . CDME was thereafter utilized in a study on Slc3a1 knockout mice, demonstrating decreased stone burden by 50% and small stones formed, but it did not reduce the number of stones . These results, while novel and groundbreaking, would be of limited use in humans, given CDME would have poor bioavailability after degradation by intestinal and plasma esterases. In response, Hu et al. designed a series of cystine diamides with greater stability, and thus, bioavailability, with L-cystine bis(N'-methylpiperazide) (CDNMP, LH708) in particular demonstrating efficacy in halting stone growth in Slc3a1 knockout mice . Additional improvements in diagnostics and therapy could arise from in silico analysis of how specific mutations affect disease pathophysiology . The potential of computational predictions of mutation severity and effects on protein function to correlate with patient phenotypes may also lead to more personalized therapies , 5. Conclusions Cystinuria is a rare genetic disorder that impairs the cystine transporter from reabsorbing cystine, leading to increased urine cystine levels and cystine nephrolithiasis. Recurrent nephrolithiasis in patients with cystinuria negatively affects the quality of life and may lead to the need for frequent urologic intervention and/or CKD from recurrent kidney injury. Thus, it is important to initiate treatment early and closely monitor patients with cystinuria. Treatment is centered around stone prevention and escalated in a stepwise manner, starting with conservative measures--high fluid intake, minimizing intake of dietary sodium and animal protein, and urinary alkalinization. In patients with recurrent cystine nephrolithiasis, despite conservative measures, pharmacotherapy with CBTDs may be initiated under close monitoring. Surveillance of patients with cystinuria focuses on interval monitoring of serum and urine chemistries and periodic renal imaging, with specific timing dependent on individual patients' frequency of stone occurrence. While cystine concentration in 24 h urine samples is still used for monitoring, we highlight numerous inaccuracies with the assay that render it unreliable. Instead, the solid phase assay cystine capacity may provide a more reliable and accurate method to monitor urinary cystine levels, with recent studies demonstrating more positive cystine capacity with a lower incidence of cystine nephrolithiasis. While there remains an overall paucity of studies testing new therapeutics for cystinuria in humans, a few ongoing human pilot trials are testing the effects of dapagliflozin, tolvaptan, and alpha-lipoic acid on patients with cystinuria. Meanwhile, in vivo studies on knockout mouse models have demonstrated efficacy of molecular imposters in halting cystine stone growth, strongly directing the future of cystinuria therapeutic trials towards this model. Author Contributions Writing--original draft preparation, S.M.A. and D.S.G.; writing--review and editing, S.M.A. and D.S.G. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Institutional review board approval was not required for the preparation of this review. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. 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PMC10000470 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050984 foods-12-00984 Article Relative Bioavailability of Cadmium in Rice: Assessment, Modeling, and Application for Risk Assessment Yang Likun Formal analysis Investigation Resources Data curation Visualization Zhang Xiaoyue Investigation Zhao Di Conceptualization Methodology Software Validation Resources Writing - original draft Writing - review & editing Supervision Project administration Funding acquisition * Wang Peng Writing - review & editing Zhao Fangjie Writing - review & editing Rubio Carmen Academic Editor Olivero-Verbel Jesus Academic Editor College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China * Correspondence: [email protected] 26 2 2023 3 2023 12 5 98417 1 2023 24 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Rice consumption is the primary route of cadmium (Cd) exposure to the populations with rice as the staple food. To accurately assess the potential health risks of Cd exposure via rice consumption, determination of Cd relative bioavailability (RBA) in rice is necessary. However, large variations exist in Cd-RBA, hindering the application of source-specific Cd-RBA values to different rice samples. In this study, we collected 14 rice samples from Cd contaminated areas and determined both rice compositions and Cd-RBA using in vivo mouse bioassay. Total Cd concentration varied from 0.19 to 2.54 mg/kg in the 14 rice samples, while Cd-RBA in rice ranged from 42.10% to 76.29%. Cadmium-RBA in rice correlated positively with calcium (Ca) (R = 0.76) and amylose content (R = 0.75) but negatively with the concentrations of sulfur (R = -0.85), phosphorus (R = -0.73), phytic acid (R = -0.68), and crude protein (R = -0.53). Cd-RBA in rice can be predicted by Ca and phytic acid concentrations in a regression model (R2 = 0.80). Based on the total and bioavailable Cd concentrations in rice, weekly dietary Cd intake for adults was estimated to be 4.84-64.88 and 2.04-42.29 mg/kg bw/week, respectively. This work demonstrates the possibility of Cd-RBA prediction based on rice compositions and provides valuable suggestions for health risk assessment with consideration of Cd-RBA. cadmium rice relative bioavailability risk assessment food safety National Natural Science Foundation of China42107430 Jiangsu Provincial Natural Science FoundationBK20200547 Fundamental Research Funds for the Central UniversitiesKYQN2022029 Jiangsu Provincial Double-Innovation Doctor ProgramJSSCBS20210294 This research was funded by National Natural Science Foundation of China (42107430), Jiangsu Provincial Natural Science Foundation (BK20200547), Fundamental Research Funds for the Central Universities (KYQN2022029), and Jiangsu Provincial Double-Innovation Doctor Program (JSSCBS20210294). pmc1. Introduction Cadmium (Cd) is a toxic element present in the environment from both geogenic and anthropogenic sources . Among multiple exposure pathways, dietary intake is the primary route of Cd exposure for the general non-smoking population, accounting for ~90% of the total Cd exposure . Chronic Cd exposure via oral ingestion has been linked to increased risk of hypertension, osteoporosis, kidney damage, and even cancers , raising concerns about the potential adverse health effects of Cd exposure via food consumption. Among different food categories, rice is the largest contributor to the dietary Cd intake in China . In some polluted areas, the average Cd concentration in rice was up to 0.69 mg/kg (range: 0.005-4.80 mg/kg), with 56-87% of the rice samples exceeding the Chinese food limit of 0.20 mg/kg . These Cd concentrations in rice are similar or even higher than those 2,446 rice samples (mean Cd: 0.38 mg/kg) collected from the Jinzu River basin in Toyama prefecture, Japan, where the "itai-itai" disease (kidney failure and softening of bones) occurred. "Itai-itai" disease is the most severe stage of chronic Cd poisoning in humans caused by prolonged oral ingestion of rice, which was contaminated with Cd from irrigation waters polluted by mining activities upstream . These surveys highlight the serious pollution status of Cd in some polluted areas and the urgent need to evaluate the potential health risks of Cd exposure for local residents. Traditional risk assessment typically considers only total Cd concentration in rice, resulting in overestimation of the potential health risks. Recently, relative bioavailability (RBA) of Cd (the percentage of Cd in rice that is absorbed into the systemic circulation after oral ingestion) has been incorporated into risk assessment to improve the accuracy of the risk assessment . For example, a one-compartment toxicokinetic model has been frequently used to predict urinary Cd level based on dietary Cd intakes . When total Cd concentration in rice was used for 119 non-smokers from a Cd-contaminated area who consume rice as the staple food, their predicted urinary Cd (geometric mean: 4.14 mg/g creatinine) was 3.5-fold higher than the measured urinary Cd (geometric mean: 1.20 mg/g creatinine) . After incorporating Cd-RBA in rice (17-57%), the predicted urinary Cd was close to the measured value (1.07 vs. 1.20 mg/g creatinine), highlighting the importance of bioavailability in accurately estimating human Cd exposure and related health risks. However, large variations in Cd-RBA among different rice samples have been reported , hindering the application of determined Cd-RBA values in rice from specific sources to different rice samples. Due to the expensive cost and ethical considerations of in vivo animal bioassays, simple, rapid, and inexpensive in vitro methods have been developed as a substitute for in vivo bioassays once they were validated using in vivo animal studies . However, for Cd in rice, correlations between determined Cd-RBA using in vivo mouse bioassays and determined Cd bioaccessibility using four in vitro methods were poor (R2 = 0.0006 - 0.52), indicating that the current in vitro methods may be unreliable to predict Cd-RBA for rice . Therefore, in addition to in vitro assays, an alternative approach is to develop reliable predictive models based on rice compositions as a rapid screening tool for the assessment of Cd-RBA in rice. In this study, a total of 14 rice samples were collected from Cd-contaminated areas in southern China. The specific objectives of this study were to (1) determine Cd-RBA in rice samples from Cd-contaminated areas; (2) develop a prediction model of rice Cd-RBA using rice compositions as predictors; (3) and assess the potential health risks of Cd exposure for local populations via rice consumption. 2. Materials and Methods 2.1. Collection and Preparation of Rice Samples Rice samples were collected from local farmers living in two villages contaminated with Cd due to nearby mining activities or the prolonged irrigation of Cd-contaminated water in Hunan Province, China. After excluding those rice samples insufficient for in vivo mouse bioassays and those purchased from supermarkets and farm markets, only 14 locally grown rice samples were included in this study. The Cd concentrations in the rice samples (0.19 to 2.54 mg/kg) included in this study are similar to those previously reported, which is typical of the region . Once the 14 whole grains were transferred to the lab, they were dehusked and then polished using a laboratory rice milling machine. For each rice sample, ~120 g of polished rice was washed thoroughly with Milli-Q water three times. Following washing, the rice was cooked with 240 mL of Milli-Q water using an intelligent germinated rice machine for ~25 min. Cooked rice samples were then removed from the cooker, stored at -80 degC, and freeze-dried. All the rice samples were ground to a fine powder and mixed thoroughly. 2.2. Chemical Analysis of Rice Samples Briefly, 0.20 g cooked rice powder were digested with 5 mL of high purity HNO3 in a microwave digestion system . The concentrations of Cd and other elements, including calcium (Ca), iron (Fe), zinc (Zn), sulfur (S), and phosphorus (P), in the digests were determined based on inductively coupled plasma mass spectrometry (ICP-MS, Perkin Elmer NexION 300X, USA). Quality assurance and control were conducted during metal analysis. Briefly, indium isotope (114In) was used as an internal standard, which was added to the blanks, calibration standards, and samples to compensate for the long-term signal drift of the instrument and the matrix effects. The accuracy of the ICP-MS method used for Cd analysis was validated using a standard reference material for rice (GBW10045), with a measured Cd concentration of 0.31 +- 0.02 mg/kg in rice GSB-23 compared to the standard concentration of 0.32 +- 0.04 mg/kg. Furthermore, spikes and duplicates were included in every 20 samples during analysis using ICP-MS, with recoveries being 92-103% and 93-105%, respectively. The content of phytic acid in rice was determined based on the method of GB 5009.153-2016 . In brief, phytic acid was extracted by shaking 10 g of rice flour in 40 mL sodium sulfate-hydrochloric acid (0.10 g/mL) for 2 h. The extract was centrifuged at 500 r/min for 5 min, and the supernatant was collected and made up to 50 mL using sodium sulfate-hydrochloric acid. The filtered solution was then eluted and purified by anion exchange resin. The phytic acid concentration in the eluate was determined by a colorimetric method after reaction with the ferric trichloride-sulfosalicylic acid mixture. The absorbance at a wavelength of 500 nm was measured using a spectrometer (Shimadzu UV-1800), and the content of phytic acid was quantified against standard curves of sodium phytate. Rice powders were analyzed with a near-infrared spectrometer (Perten DA7250) to measure the content of crude protein and amylose . 2.3. Relative Bioavailability of Cd in Rice A steady state dosing method with free access to diet was used for in vivo bioavailability study. Briefly, the 14 samples of cooked rice powder were thoroughly mixed with Milli-Q water and made into a paste by kneading. Then, the amended mouse feed was evenly divided into small pieces before being freeze-dried. In addition, CdCl2 was added into a non-contaminated rice (Cd: 0.002 mg/kg) using a similar method to produce different Cd concentrations (0.20-5.00 mg/kg) to assess the dose responses. To ensure that the amended mouse feed was thoroughly mixed, Cd concentrations in randomly selected pellets for each rice sample were determined, resulting in a relative standard deviation < 5%. A total of sixty female Balb/c mice with body weights of 18-20 g were purchased. Following acclimation for 1 week under a standard condition (25 degC, 50% humidity and 12:12 h light/dark cycle) with free access to Milli-Q water and mouse feed. Milli-Q water was used to avoid metal intakes from drinking water. For the basal mouse feed used during acclimation, Cd concentration was 0.002 +- 0.002 mg/kg. This background level of Cd is only 0.78-1.05% of those in the rice samples tested. Mice were fasted overnight, weighed, and randomly assigned to individual plastic cages. Animal care was compliant with the guide for the care and use of laboratory animals and approved by the Ethics Committee of Animal Experiments of Nanjing Agriculture University. For Cd exposure, each mouse received ~3 g of amended feed at 9:00 am every day. For each rice sample and CdCl2 dose levels, 3 mice were used as replicates. During the 10-days exposure, mice had free access to water and amended feed ad libitum. At the end of a 10-day exposure, remaining rice pellets were removed from cages, freeze-dried, and weighed to calculate the food consumption rate. Mice were fasted overnight and sacrificed to collect the liver and kidneys. The liver and kidneys were stored at -80 degC, freeze-dried, digested, and then measured for Cd concentration using ICP-MS. Non-contaminated rice was fed to mice to determine background values of Cd accumulation in mouse liver and kidneys. Cd-RBA in rice was calculated using Equation (1) (1) Cd relative bioavailability (%)=(Tissue CdriceCd dosericexCd doseCdCl2Tissue CdCdCl2) x100% where Tissue Cdrice and Tissue CdCdCl2 are Cd concentrations accumulated in mouse liver plus kidneys following the consumption of rice and CdCl2-spiked rice; Cd doserice and Cd doseCdCl2 are Cd dose levels from rice and CdCl2-spiked rice exposure . 2.4. Prediction Model of Cd-RBA in Rice The prediction model of Cd-RBA in rice was derived using rice compositions as predictors, including concentrations of Ca, Fe, Zn, S, P, Cd, amylose, crude protein, and phytic acid. Stepwise multiple linear regression analysis was conducted in R software (version 3.4.2) to determine the regression parameters, based on 14 pairs of data of Cd-RBA and rice compositions. The best-fitted regression model is presented in Equation (2):(2) lg(CdRBA)=a+bxlg(Ca)+cxlg(phytic acid) where CdRBA is the relative bioavailability of Cd in rice (%), Ca is expressed in mg/kg, and phytic acid is expressed in g/kg, respectively. 2.5. Calculation of Weekly Dietary Cd Intake To assess the potential health risks of Cd exposure via rice consumption, weekly dietary Cd intake was calculated from total or bioavailable Cd in rice following Equations (3) and (4). (3) Weekly dietary Cd intake=CxIRBW (4) Adjusted weekly dietary Cd intake=CxIRxRBABW where C is the total Cd concentration in rice (mg/kg), IR is the consumption rate of rice (g/week), BW is the body weight of consumers (kg), and RBA is the relative bioavailability of Cd in rice (%). The rice consumption rate of 218.60 g/d for the general population was obtained from the Chinese national nutrition and health survey, the average body weight of 60 kg for adults was used for calculation . The calculated weekly dietary Cd intake was compared to the provisional tolerable weekly intake for Cd of 5.80 mg/kg bw/week proposed by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). 2.6. Statistical Analysis All concentrations in rice samples and rice Cd-RBA are presented as means and standard deviations (SD) of the three replicates. A significant difference in rice Cd concentrations and Cd-RBA between rice samples was assessed using Fisher's least-significant difference (LSD) with a significance level of p < 0.05. All statistical statistics were performed using IBM SPSS Statistics, version 28. All graphs were performed using SigmaPlot (version 14.0) and Origin 2023. 3. Results 3.1. Chemical Compositions in Rice In this study, Cd concentrations in the 14 polished rice samples collected from Cd contaminated areas varied from 0.19 to 2.54 mg/kg (mean = 1.07 mg/kg) , with 93% of the samples exceeding the limit of 0.20 mg/kg. Besides Cd, the concentrations of chemical elements and compositions, such as Ca, Fe, Zn, S, P, crude protein, amylose, and phytic acid, in the rice samples were also measured (Table 1). The average concentrations of Ca, Fe, and Zn were 120.16 mg/kg, 5.07 mg/kg, and 14.33 mg/kg, respectively. The average concentrations of S and P were 1499 mg/kg and 1393 mg/kg, respectively. The average contents of crude protein and amylose were 10.66% and 26.32%, respectively. The average concentration of phytic acid was 1.59 g/kg, ranging from 0.91 to 2.69 g/kg. 3.2. Relative Bioavailability of Cd in Rice To accurately assess the potential health risks of Cd exposure via rice consumption, Cd-RBA in the 14 rice samples was assessed using a steady state in vivo mouse bioassay. A dose-response relationship was first established between Cd doses and Cd accumulations in mouse liver and kidneys. Following the administration of different concentrations of CdCl2 (0.20-5.00 mg/kg) to mice over a 10-day exposure, a strong linear relationship (R2 = 0.97) between the Cd dose and the concentration of Cd accumulated in mouse liver plus kidneys was observed , confirming the suitability of the combined end point (liver plus kidneys) to determine Cd-RBA in rice at similar Cd doses. For the 14 rice samples, Cd-RBA varied from 42.10% to 76.29%, with the average being 59.16% . In addition, the correlations between rice Cd-RBA and rice compositions were analyzed . For mineral nutrient elements in rice, Cd-RBA was significantly correlated with Ca concentrations (R = 0.76) but not with Fe or Zn concentrations (R = 0.04 and 0.03). Cadmium-RBA was strongly and negatively correlated with the concentrations of S (R = -0.85) and P (R = -0.73). No significant correlation (R = 0.24) was observed between Cd-RBA and Cd concentrations in the rice samples. For rice compositions in rice samples, Cd-RBA correlated positively with the percentage of amylose (R = 0.75) but negatively with phytic acid (R = -0.68) and crude protein (R = -0.53). 3.3. Using Rice Compositions to Predict Cd-RBA in Rice Multiple linear regression analysis was then performed between Cd-RBA and rice compositions. Rice Ca and phytic acid were found to be the two major factors influencing Cd-RBA in rice, as shown in the following Equation (5):(5) lg(CdRBA)=0.9+0.44xlg(Ca)-0.3xlg(phytic acid) (R2=0.80, p<0.05) The data highlighted a significant correlation between rice Cd-RBA and the concentrations of Ca and phytic acid, accounting for 80% of the variability in Cd-RBA for all tested rice samples. In the regression equation obtained, the influence of Ca on Cd-RBA was positive, whereas the influence of phytic acid was negative. Based on the multiple linear regression, the predicted Cd-RBA values were obtained and compared with measured Cd-RBA using linear regression. A strong significant relationship (R2 = 0.86) between predicted Cd-RBA and measured Cd-RBA was obtained , providing a reliable predictor of Cd-RBA based on rice compositions. 3.4. Health Risk Assessment Based on Total Cd and Bioavailable Cd in Rice To assess the potential health risk of Cd exposure via rice consumption, weekly dietary Cd intake for an adult with a body weight of 60 kg was estimated based on total Cd and bioavailable Cd concentrations assuming the rice consumption rate of 218.6 g/day . Based on total Cd, consumption of rice would result in a weekly Cd intake of 4.84-64.88 mg/kg bw/week . The estimated weekly dietary Cd intake from 12 of 14 rice samples exceeded the provisional tolerable weekly intake level of 5.80 mg/kg bw/week for Cd intake proposed by JECFA to protect humans from adverse health effects. When taking bioavailable Cd into consideration, the estimated weekly dietary Cd intake was reduced to 2.04-42.29 mg/kg bw/week , which is 23.71-57.90% lower compared to total Cd. 4. Discussion The 14 rice samples used in the present study contained elevated levels of Cd due to soil contamination from nearby mining activities or the prolonged irrigation of Cd-contaminated water. The Cd concentrations in the rice samples (0.19 to 2.54 mg/kg) are typical of the region and likely lead to elevated dietary Cd intakes and health risk for the local residents. Potential health risk of Cd exposure depends not only on the total amount of Cd intake but also on the bioavailability of Cd in the ingested food. The large variation in Cd-RBA (42.10-76.29%) among the 14 rice samples detected in this study is similar or higher than those of rice Cd-RBA reported by previous studies. For example, Zhao et al. first determined Cd-RBA in rice using an in vivo mouse bioassay and found large variability (17-57%) in Cd-RBA among 10 rice samples (Cd: 0.29-1.09 mg/kg) collected from Cd-contaminated areas caused by enamel pottery production. Higher Cd-RBA values of 41-84% have been reported for 11 rice samples (Cd: 0.41-1.67 mg/kg) collected from mining/smelting areas based on in vivo mouse bioassay , which is similar to the values detected in this study. Zhuang et al. collected six rice samples from supermarkets, farmer markets near mining-impacted areas, and greenhouses, which varied widely in Cd concentration (0.15-10.10 mg/kg). An in vivo mouse bioassay was conducted using these rice samples, with Cd-RBA being 15-56%, 18-56%, and 3.71-54% when kidneys, liver, and femur were used as the end point. A recent study showed large variations (36-97%) in Cd-RBA among three rice samples with relatively low Cd concentrations (0.10-0.40 mg/kg) when different end points (kidneys, liver, and liver plus kidneys) were used . These studies together showed a large variation in Cd-RBA between rice samples (3.7-97.3%), hindering the accurate health risk assessment of Cd exposure via rice consumption when incorporating of Cd-RBA. However, the main factors affecting Cd-RBA in rice is unclear, it is imperative to identify key factors influencing Cd-RBA in rice. The large variation in Cd-RBA among different rice samples may be related to differences in rice mineral element concentrations because Cd utilizes the same intestinal transporters as mineral elements, including Zn, Fe, and Ca . Higher concentrations of Ca, Fe, or Zn in rice may decrease Cd-RBA due to competitions for transporters in the intestinal epithelium . However, previous studies showed no strong correlations between Cd-RBA and nutrients elements, such as Ca, Fe, and Zn concentrations in rice . In contrast, we found a positive correlation between Cd-RBA and Ca concentration. The intestinal transporters for Ca absorption, such as Ca binding protein (CaBP), have been reported to be able to absorb Cd since the binding affinities of CaBP for Cd and Ca are similar . Rats fed on low Ca diets were found to have a ~60% higher Cd accumulation in the kidneys and liver than those fed on a normal diet of Ca intake, likely because synthesis of CaBP is intensified at low dietary Ca intake . However, contrary to the expected negative effect of Ca on Cd absorption, we found Cd-RBA in rice increased with Ca concentration. The potential mechanism underpinning the contrary effect of Ca on Cd-RBA in rice is unknown, which warrants further investigation. Besides mineral nutrient elements, the large variation in rice Cd-RBA may be accounted by differences in S and P concentrations in rice. Using synchrotron X-ray absorption spectrometry, Gu et al. showed that the majority (66-92%) of Cd in rice was combined with thiol-rich proteins, presenting as Cd-thiolate complexes. The negative correlation between Cd-RBA and rice S concentrations suggests that complexation of Cd by thiol-containing compounds in rice may reduce the bioavailability of Cd. Besides the effect of S, an in vivo mouse experiment showed that Cd accumulation in kidneys was markedly reduced by increasing the P concentration . The formation of cadmium phosphate precipitates could explain the decreased Cd-RBA in rice with an increasing P concentration, although further research is needed to elucidate the potential mechanism. Rice compositions, such as the content of amylose, phytic acid, and crude protein, may also contribute to differences in Cd-RBA in rice. Rice contains high levels of starch; the main difference in starch composition among different rice varieties is related to the variation in the proportions of its two polymers, amylopectin and amylose . There is a high possibility that higher Cd-RBA with increasing amylose is caused by the interaction with other components since amylose content was found to correlate with Ca, S, P, phytic acid, and crude protein content . It has been demonstrated that phytic acid, which is a strong chelator of divalent cations, inhibits the intestinal absorption of metal cations, such as Ca, Fe, and Zn . Lee et al. found that the content of phytic acid in rice was negatively correlated with mineral bioaccessibility, with the correlation being the highest in Ca (R = 0.60), followed by Fe (R = 0.40), and Zn (R = 0.27). The Ca-phytate complex has a strong affinity for Cd, which could lead to reduced Cd-RBA in rice. An in vitro intestinal study showed a significant reduction in Cd absorption in the presence of phytic acid , which is consistent with our study. Protein content is another factor that may affect Cd bioavailability. In a mouse bioassay using renal accumulation of Cd as the endpoint , cadmium concentration in the kidneys was significantly decreased by high protein compared to low protein diet (25% vs. 10%). Thus, rice compositions were used as predictors for Cd-RBA based on multiple linear regression analysis; Ca and phytic acid were selected as the more important parameters in the prediction model. The prediction model was validated by comparing the measured and predicted Cd-RBA in 14 rice samples. All the measured values of Cd-RBA in rice fell within the 95% prediction interval. The developed model was therefore regarded as a reliable model for predicting Cd-RBA in rice collected from other sources once the rice compositions were determined. Following determination of Cd-RBA in rice, weekly dietary Cd intake via rice consumption was estimated using total and bioavailable Cd concentrations to assess the potential health risk of Cd exposure. When total Cd in rice was used for calculation, weekly dietary Cd intake increased with an increasing rice Cd concentration, indicating increasing potential health risk with an elevated rice Cd concentration. Unlike the linear relationship between rice total Cd concentration and weekly dietary Cd intake, a higher Cd concentration in rice samples may not always lead to a higher health risk when Cd-RBA is taken into account. For example, rice #13 had a higher Cd concentration than rice #12 (2.48 vs. 1.74 mg/kg) but would lead to a lower Cd intake level when Cd-RBA is considered (31.68 vs. 33.60 mg/kg bw/week). Similar findings have been reported for other food matrices, such as leafy vegetables , highlighting the importance of incorporating Cd-RBA into the health risk assessment. Thus, Cd-RBA in rice is recommended in future risk assessment to improve the accuracy and reliability. 5. Conclusions A large variation in Cd-RBA was observed among 14 rice samples based on in vivo mouse bioassay. Cd-RBA positively correlated with Ca and amylose content in rice, while negatively correlated with concentrations of S, P, phytic acid, and crude protein. Multiple linear regression analyses showed that Ca and phytic acid concentrations are the two major factors influencing Cd-RBA, demonstrating the possibility of using rice compositions to predict Cd-RBA in rice. Further studies are required to elucidate the mechanisms underpinning the effect of Ca, amylose, S, P, phytic acid, and crude protein on Cd-RBA. As Cd-RBA varies widely, rice samples with high Cd concentrations do not always mean high health risks of Cd exposure. To improve the accuracy of a health risk assessment, incorporation of bioavailability information is strongly suggested. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Linear dose response of Cd accumulation in liver plus kidneys to Cd dose levels following 10-d consumption of CdCl2-amended diets at 0.2-5.0 mg/kg Cd. Table S1: Concentrations of Cd and nutrient elements in the 14 rice samples tested for in vivo mouse bioassay. Click here for additional data file. Author Contributions Conceptualization, D.Z.; methodology, D.Z.; software, D.Z.; validation, D.Z.; formal analysis, L.Y.; investigation, L.Y. and X.Z.; resources, L.Y. and D.Z.; data curation, L.Y.; writing--original draft preparation, D.Z.; writing--review and editing, D.Z., P.W., and F.Z.; visualization, L.Y.; supervision, D.Z.; project administration, D.Z.; funding acquisition, D.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this article are available from the corresponding authors upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Cadmium concentration (A) and Cd relative bioavailability (B) in 14 rice samples. Different letters above bars indicate significant (p < 0.05) difference among rice samples. Figure 2 Pearson rank correlation between Cd-RBA and chemical composition in rice. Significant correlations are denoted by "*" (p < 0.05). Figure 3 Correlations between measured and predicted Cd-RBA based on Ca and phytic acid concentrations in rice. Blue solid lines and green dashed lines represent 95% prediction and confidence bands, respectively. Figure 4 Weekly dietary Cd intake levels estimated using total Cd concentration in rice (A) and bioavailable Cd concentration in rice (B). Weekly dietary Cd intake via oral ingestion of rice was calculated for an adult with a body weight of 60 kg and a rice consumption rate of 1.53 kg/week. The black dashed lines indicate the tolerable intake level of 5.80 mg/kg bw/week for Cd proposed by JECFA to protect human health. foods-12-00984-t001_Table 1 Table 1 Chemical composition analysis of 14 rice samples. Compositions Mean +- SD Range Cd (mg/kg) 1.07 +- 0.78 0.19-2.54 Ca (mg/kg) 120.16 +- 31.20 79.49-165.71 Fe (mg/kg) 5.07 +- 1.32 2.60-7.37 Zn (mg/kg) 14.33 +- 2.88 11.35-21.22 S (mg/kg) 1499.72 +- 197.52 1183.81-1813.53 P (mg/kg) 1393.48 +- 434.01 878.93-2345.57 Crude protein (%) 10.66 +- 0.70 9.31-12.36 Amylose (%) 26.32 +- 4.62 18.55-32.64 Phytic acid (g/kg) 1.59 +- 0.56 0.91-2.69 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000471 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050931 diagnostics-13-00931 Article Estimation of Lewis Blood Group Status by Fluorescence Melting Curve Analysis in Simultaneous Genotyping of c.385A>T and Fusion Gene in FUT2 and c.59T>G and c.314C>T in FUT3 Soejima Mikiko Investigation Resources Writing - original draft Koda Yoshiro Conceptualization Methodology Resources Writing - review & editing Supervision * Chang Chung-Che (Jeff) Academic Editor Department of Forensic Medicine, Kurume University School of Medicine, Kurume 830-0011, Japan * Correspondence: [email protected]; Tel.: +81-942-31-7554 01 3 2023 3 2023 13 5 93128 1 2023 15 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Lewis blood group status is determined by two fucosyltransferase activities: those of FUT2-encoded fucosyltransferase (Se enzyme) and FUT3-encoded fucosyltransferase (Le enzyme). In Japanese populations, c.385A>T in FUT2 and a fusion gene between FUT2 and its pseudogene SEC1P are the cause of most Se enzyme-deficient alleles (Sew and sefus), and c.59T>G and c.314C>T in FUT3 are tag SNPs for almost all nonfunctional FUT3 alleles (le59, le59,508, le59,1067, and le202,314). In this study, we first conducted a single-probe fluorescence melting curve analysis (FMCA) to determine c.385A>T and sefus using a pair of primers that collectively amplify FUT2, sefus, and SEC1P. Then, to estimate Lewis blood group status, a triplex FMCA was performed with a c.385A>T and sefus assay system by adding primers and probes to detect c.59T>G and c.314C>T in FUT3. We also validated these methods by analyzing the genotypes of 96 selected Japanese people whose FUT2 and FUT3 genotypes were already determined. The single-probe FMCA was able to identify six genotype combinations: 385A/A, 385T/T, sefus/sefus, 385A/T, 385A/sefus, and 385T/sefus. In addition, the triplex FMCA successfully identified both FUT2 and FUT3 genotypes, although the resolutions of the analysis of c.385A>T and sefus were somewhat reduced compared to that of the analysis of FUT2 alone. The estimation of the secretor status and Lewis blood group status using the form of FMCA used in this study may be useful for large-scale association studies in Japanese populations. fluorescence melting curve analysis fusion gene FUT2 FUT3 Lewis blood group status secretor status This research received no external funding. pmc1. Introduction The expression of Lewis blood group antigens, Lewis a (Lea) and Lewis b (Leb), is determined by the activity of FUT2-encoded fucosyltransferase (Se enzyme) and FUT3-encoded fucosyltransferase (Le enzyme) . Secretors with at least one functional FUT2 allele (Se) express soluble ABH(O) antigens in saliva and other secretions, while non-secretors, homozygotes for the nonfunctional FUT2 (non-secretor) alleles (se), do not . Weak secretors are homozygous for the weak-secretor allele (Sew) or compound heterozygous for Sew/se and are characterized by very low ABH antigen expression in secretions compared to secretors. This is because the activity of the Se enzyme encoded by Sew is very low but detectable due to a single nucleotide polymorphism (SNP), c.385A>T (p.Ile129Phe, rs1047781) . In addition, Lewis-positive individuals with at least one functional FUT3 allele (Le) have Le(a-b+) red cells in their secretors, Le(a+b-) in their non-secretors, and Le(a+b+) in their weak secretors. On the other hand, Lewis-negative individuals, homozygotes for the nonfunctional FUT3 alleles (le), all have Le(a-b-) red cells . Evidence is accumulating that secretor status and/or Lewis blood group status affects the susceptibility to a variety of clinical conditions, including some infectious diseases, inflammatory bowel disease, and plasma vitamin B12 levels . To date, five se alleles resulting from non-allelic homologous recombination and several population-specific SNPs in FUT2 and FUT3 have been identified . Among these, sefus, which results from an unequal crossover between FUT2 and its pseudogene SEC1P , is present almost exclusively in Japanese populations with a frequency of 5-9% . SEC1P has high sequence similarity to FUT2 and is located near FUT2 on chromosome 19q13.3 . In addition, the causal SNP for Sew, c.385A>T, is restricted to East and Southeast Asians, including Japanese people, with a frequency of about 50% . Furthermore, three tag SNPs, c.59T>G (p.Leu20Arg, rs28362459), c.314C>T (p.Thr105Met, rs778986), and c.484A>G (p.Trp68Arg, rs28362463) in FUT3, were suggested to be useful for estimating le allele frequency in many populations . In Japanese populations, since Se enzyme-deficient alleles other than Sew and sefus are quite rare and c.59T>G and c.314C>T are tag SNPs for almost all le alleles (le59, le59,508, le59,1067, and le202,314), determining these polymorphisms could provide an accurate estimate of secretor status and Lewis blood group status. Fluorescence melting curve analysis (FMCA) is a simple, robust, and rapid closed-tube post-PCR method for detecting SNPs that analyzes the difference between the melting curve profiles of the fluorescence-labeled probe and PCR amplicon . In addition, multiplex assays can be performed by using different fluorescent dyes . Recently, we developed a triplex FMCA procedure for the genotyping of three tag SNPs, c.59T>G, c.314C>T, and c.484A>G, in FUT3 to estimate le allele frequency . In this study, we performed a FMCA that simultaneously determined the frequency of c.385A>T and sefus using a single probe. A triplex FMCA was then performed to estimate Lewis blood group status in Japanese people, adding primers and probes to detect c.59T>G and c.314C>T of FUT3 to c.385A>T and sefus assay system. 2. Materials and Methods 2.1. DNA Samples The genomic DNAs of 96 Japanese people from Fukuoka whose FUT2 haplotypes had been determined previously using established methods such as the allele specific PCR and/or DNA sequencing were used in this study. The study protocol was reviewed and approved by the ethical committee of Kurume University (approval no. 22158). 2.2. Asymmetric PCR for c.385A>T and sefus of FUT2 The nucleotide positions of the FUT2 and SEC1P genes were numbered as described previously . All primers and probes were synthesized by Eurofins Genomics K.K (Tokyo, Japan). As shown in Figure 1A, we used a pair of primers that collectively amplify FUT2, sefus, and SEC1P. The forward primer, 5'-TGGCAGAACTACCACCTGAA-3', matches exactly 337-356 bp of FUT2 and 379-398 bp of SEC1P, and is the same primer that previously detected c.385A>T by an unlabeled probe HRM analysis . The reverse primer, 5'-AGGTCCAGGAGCAGGGGTAG-3', matches exactly the reverse sequences of 414-433 bp of FUT2 and of 456-475 bp of SEC1P, and is the same primer that previously detected sefus by a TaqMan probe assay and HRM analysis . The SEC1P-FUT2 probe, HEX-5'-GGAGGAGTACCGCCACATCCCGGGG-3'-black hole quencher 1, matches exactly 411-435 bp of SEC1P, and 369-393 bp of FUT2, but differs by one base from the wild-type (385A allele) and sefus, and differs by two bases from the 385T allele. The asymmetric PCR reaction mixture with a final volume of 10 mL contained 5 mL of TaKaRa Taq HS Perfect Mix containing modified Taq DNA polymerase, which has neither 5'-3' exonuclease nor 3'-5' exonuclease activities (Takara, Tokyo, Japan), 50 nM of the forward primer, 500 nM of the reverse primer, 200 nM of the SEC1P-FUT2 probe, and 2-20 ng of genomic DNA. The PCR was conducted on LightCycler 480 Instrument II (Roche Diagnostics, Tokyo, Japan) with the following thermal conditions: 45 cycles of denaturation at 95 degC for 5 s, and annealing/extension at 60 degC for 15 s. 2.3. Triplex PCR for c.385A>T and sefus of FUT2, c.59T>G and c.314C>T of FUT3 Recently, we conducted a triplex FMCA for the genotyping of three tag SNPs, c.59T>G, c.314C>T, and c.484A>G, in FUT3 to estimate le allele frequency . However, c.484A>G is highly specific to African populations and has not yet been observed in Asian populations, including Japanese populations. Therefore, in this study, previously reported primers and probes were added to the c.385A>T and sefus of the FUT2 assay system to detect c.59T>G and c.314C>T, excluding c.484A>G. However, since a HEX-labeled probe was used to detectc.385A>T and sefus, a FAM-labeled probe was used instead of a HEX-labeled probe to detect c.59T>G in this study. The primer and probe concentrations for c.59T>G and c.314C>T were as follows: 50 nM of each forward primer, 250 nM of each reverse primer, 50 nM of a probe for c.59T>G, and 100 nM of a probe for c.314C>T. The primer and probe concentrations for c.385A>T and sefus and the thermal conditions of the asymmetric PCR were the same as described above. 2.4. FMCA for Detection of c.385A>T and sefus of FUT2, c.59T>G and c.314C>T of FUT3 The PCR products were then heated to 95 degC for 1 min and cooled to 40 degC for 1 min, and fluorescence data were acquired using the VIC/HEX/Yellow 555 filter (excitation-emission: 533-580 nm) and/or the FAM filter (465-510 nm) and/or the Cy5/Cy5.5 filter (618-660 nm) during heating from 50 to 80 degC at a 0.1 degC/s ramp rate. Melting curve genotyping and melting temperature (Tm) analyses were carried out using the LightCycler 480 gene scanning software. 3. Results 3.1. FMCA for Detection of c.385A>T and sefus of FUT2 In this study, we first attempted to detect c.385A>T and sefus with a single probe using a primer set that collectively amplified 97 bp amplicons of FUT2, sefus, and SEC1P. As shown in Figure 1B and Figure 2A, the highest Tm value around 73 degC was observed for the SEC1P amplicon because the probe sequence exactly matches that of SEC1P. On the other hand, an intermediate Tm value around 68 degC was observed for the 385A allele amplicon because the probe sequence differed by one base, and the lowest Tm value around 62 degC was observed for the 385T allele amplicon because the probe sequence differed by two bases. In addition, in sefus, the nucleotides corresponding to the positions of 375 bp and 385 bp in FUT2 (or 419 bp and 429 bp in SEC1P) were both "A", and therefore, the Tm value for the sefus amplicon was the same (around 68 degC) as that for the 385A amplicon . A chromosome with the 385A or 385T allele had two regions (413-437 bp of SEC1P and 369-393 bp of FUT2) that hybridized with the probe . On the other hand, a chromosome with the sefus allele had only one region that hybridized with the probe because sefus had been generated by an unequal crossover between the 253 and 416 bp positions of SEC1P and between the 211 and 374 bp positions of FUT2, and the position of 385 bp of FUT2 is located immediately at the 3' region of the recombination sequence . We then analyzed 96 Japanese people whose FUT2 haplotypes had already been determined by allele-specific PCR and/or DNA sequencing . Homozygotes of sefus (sefus/sefus) showing only one melting peak at around 68 degC, and homozygotes of 385T allele (385T/T) showing two melting peaks at around 73 degC and 62 degC were completely separated by the default settings of the LightCycler 480 gene scanning software (normal sensitivity, score threshold 0.70, resolution threshold 0.10). On the other hand, homozygotes of the 385A allele (385A/A) and heterozygotes of 385A/sefus with two melting peaks at around 73 degC and 68 degC, or heterozygotes of c.385A>T (385A/T) and heterozygotes of 385T/sefus with three melting peaks at around 73 degC, 68 degC, and 62 degC, were classified into the same group in the default settings. However, it was possible to separate 385A/A from 385A/sefus and 385A/T from 385T/sefus by changing the settings to normal sensitivity with a score threshold of 0.85 and a resolution threshold of 0.00 . The reason for this is that the peak height corresponding to SEC1P for sefus heterozygotes are relatively lower than that corresponding to SEC1P for subjects without sefus . Although one weak secretor with the genotype Sew/se628, determined by a Sanger sequencing analysis, was misclassified as Se/Sew in this FMCA because the nucleotide at position 385 of se628 was an "A", the other results were completely in accordance with previous ones . The FUT2 genotyping results of conducting a FMCA of 96 Japanese people were as follows: 23 were 385A/A, 38 were 385A/T, 22 were 385T/T, 9 were 385A/sefus, 2 were 385A/sefus, and one was sefus/sefus. In addition, the repeatability the results was confirmed because the results of two independent assays were identical. 3.2. Triplex FMCA for Detection of c.385A>T and sefus of FUT2, c.59T>G and c.314C>T of FUT3 We then attempted a triplex FMCA that could estimate the Lewis blood group status of the Japanese people by adding primers and probes that detect c.59T>G and c.314C>T in FUT3 and c.385A>T and adding the sefus assay system. The melting curve genotyping results for c.385A>T and sefus from the triplex FMCA were similar to those from the single-probe FMCA with the default settings; however, unlike the single-probe FMCA, some melting peaks were divided into unknown groups when the score threshold was increased. Therefore, automatic discrimination by a software is difficult, but it seems possible to separate them by manual visual discrimination. This was possible because, as described above, the peak height corresponding to SEC1P in sefus heterozygotes was relatively lower than the peak height corresponding to SEC1P in subjects without sefus. On the other hand, c.59T>G and c.314C>T were clearly separated automatically, as described previously . The FUT3 genotyping results of conducting a FMCA of 96 Japanese people were as follows: 35 were 59T/T, 43 were 59T/G, and 18 were 59G/G, while 93 were 314C/C and three were 314C/T. Table 1 shows the FUT2 and FUT3 genotypes, secretor status, and Lewis blood group status of the 96 Japanese subjects estimated by the present triplex FMCA. Thus, by the FMCA, 60 of the 96 Japanese subjects were estimated to be Lewis-positive secretors with a Lewis phenotype of Le(a-b+); 16 were Lewis-positive weak secretors of Le(a+b+), one was a Lewis-positive non-secretor of Le(a+b-), and 19 were Lewis-negative subjects of Le(a-b-). In addition, 11 of the 19 people with a phenotype of Le(a-b-) were estimated to be secretors and 8 were estimated to be weak secretors.. Incidentally, conventional serological Lewis phenotyping is somewhat difficult because it depends largely on the strength and specificity of the anti-Lea and anti-Leb antibodies used and the skill of the observer . In fact, in a previous study in which we analyzed the FUT2 of the same subjects used in this study, we misdiagnosed the serological Lewis phenotype Le(a+b+) as Le(a+b-) . This may have been due to the specificity of the anti-Leb antibody used. Thus, we classified Le(a+b-) subjects as being of the Se enzyme-deficient phenotype, which includes both weak secretors and non-secretors. In any case, with the exception of one subject (as mentioned above), the previous Lewis phenotyping results were also compatible with the estimate of the Lewis phenotype made by the FMCA. 4. Discussion Several real-time PCR based methods were developed to identify c.385A>T or sefus individually, including high-resolution melting (HRM) analysis and a TaqMan (hydrolysis probe) assay . In this study, we developed an FMCA method to detect c.385A>T and sefus by an asymmetric PCR using a single probe. The probe-based FMCA showed significant Tm change (about 5-6 degC) between a wild type (385A) allele and/or sefus, and between a mutant type (385T) allele and SEC1P. Thus, this single-probe assay accurately determined 385A>T substitution. sefus was found almost solely in the Japanese population with a frequency of 5-9% , and thus, 11 of the 96 Japanese subjects were sefus heterozygotes (nine subjects were 385A/sefus, two subjects were 385T/sefus) in this study. As described previously, an artificial recombinant of SEC1P and FUT2 was generated during PCR amplification when a relatively small fragment specific to the sefus sequence was amplified . To avoid the production of an artificial recombinant of SEC1P and FUT2, we selected primers that had amplified sefus and SEC1P in the previous studies , and that amplified sefus, SEC1P, and FUT2 in the present study. The present method has an advantage over the previous methods, which could only detect c.385A>T or sefus, in that it can simultaneously detect sefus and the c.385A>T of FUT2 in a single assay. Because the sefus allele contains the 3' region of the wild-type FUT2 sequence, it was previously misidentified as a functional 385A allele when c.385A>T was genotyped using primers that specifically amplified the FUT2 sequence surrounding 385A>T . In the present study, in fact, the Tm value of the sefus signal was also the same as that of the 385A allele signal, but since a chromosome with sefus lacks SEC1P, it appeared that the zygosity of sefus could be determined by the peak height of the SEC1P signal. Namely, sefus/sefus lacked the SEC1P signal and sefus heterozygotes had relatively lower peak SEC1P signal height. The relatively lower peak SEC1P signal height of in the sefus heterozygotes could not be detected by the software of the real-time PCR instrument used with the default settings for melting curve genotyping. According to the instrument manual (LightCycler 480 Instrument Operator's Manual), 'score' is an index of the similarity between the melting curves of a sample and the melting curve of the standard that is most similar to the sample, and 'resolution' is the index of the dissimilarity between the melting curve of the sample and the melting curve of the second most similar standard. Therefore, subtle differences in the relatively lower peak SEC1P signal height in the sefus heterozygotes could have been detected by increasing the score threshold and decreasing the resolution threshold from the default settings. In addition, we developed a triplex FMCA prodcedure that could simultaneously detect the c.385A>T and sefus of FUT2 and the c.59T>G and c.314C>T of FUT3. Because the resolution was somewhat lower for the triplex FMCA than for the single-probe FMCA, it was difficult to automatically separate the six genotype combinations using the software. Nevertheless, it was possible to first separate them into four groups, sefus/sefus, 385T/T, 385A/A plus 385A/sefus, and 385A/T plus 385T/sefus, by the default settings, and then 385A/A was further separated from 385A/sefus and 385A/T from 385T/sefus by manually observing the relative peak SEC1P signal heights. Therefore, we could estimate not only secretor status but also Lewis blood group status in a single assay. The c.375A>G (synonymous SNP, rs1800026) of FUT2 has been observed in African and Oceanian populations . The FUT2 allele with this SNP would be determined as SEC1P in the present method. However, in other populations, including the Japanese population, this SNP seems to be rarely observed. Therefore, such a misdiagnosis is unlikely to occur in the genotyping of Japanese subjects. A limitation of the present method is that it cannot detect rare known se alleles such as se571 and se628 and rare unknown se and le alleles. In fact, we misdiagnosed one se628 allele as a functional allele by the present method. In addition, this method is useful almost exclusively for Japanese populations. Sanger sequencing, the golden standard for the determination of SNPs, can detect these rare se alleles. However, compared to Sanger sequencing, for the whole coding region of FUT2, the present FMCA method is simple, cost-effective, and rapid, making it suitable for high-throughput analysis . In addition, it is impossible to detect se alleles generated by non-allelic homologous recombination such as sefus by Sanger sequencing for the whole coding region of FUT2. Therefore, the probe-based FMCA procedure used in this study may have some advantages over Sanger sequencing. The association between phenotypic polymorphisms of blood types, as represented by the ABO blood group, and specific diseases has been analyzed in the past by case-control studies, but few reports have shown an association of those with specific symptoms such as the presence of duodenal ulcers . On the other hand, recent large-scale analyses using genomic DNA, including genome-wide association studies (GWAS), have revealed associations between SNPs in blood group genes and various unexpected diseases. Typical examples include the association of the ABO blood group gene polymorphisms with pancreatic cancer and thromboembolic and arterial disease . Although the mechanisms by which blood group polymorphisms are involved in the pathogenesis of each of these diseases remain to be elucidated, the identification of associations with known genetic polymorphisms that seem to be unrelated to disease is one of the advantages of large-scale GWAS. As further analyses are conducted, it is possible that more diseases or clinical conditions will be found to be associated with secretor status and Lewis blood group. Furthermore, while serological Lewis phenotyping could not determine the secretory status of Lewis-negative subjects, i.e., those without Le(a-b-), FUT2 genotyping could determine the secretory status of Lewis-negative subjects. A recent study suggested that red cells with Lewis a phenotype displayed strongly reduced SARS-CoV2-susceptibility . However, as mentioned above, serological Lewis phenotyping is somewhat difficult. Thus, the estimation of Lewis phenotypes by reliable FUT2 and FUT3 genotyping is a useful alternative method for phenotyping, and the FMCA method used here appears to be a valid and feasible method for large-scale association studies of both secretor status and Lewis blood group status in Japanese populations. Acknowledgments We thank Katherine Ono for editing the English in this manuscript. Author Contributions Conceptualization, Y.K.; methodology, Y.K.; investigation, M.S.; resources, M.S. and Y.K.; writing--original draft preparation, M.S.; writing--review and editing, Y.K.; supervision, Y.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the ethical committee of Kurume University (approval no. 22158, approved date: 31 October 2022). Informed Consent Statement The need for patient consent was waived due to the use of existing and already anonymized DNA samples. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Genomic structure of FUT2, SEC1P, and sefus, and primer and probe positions used (A). The protein coding region of FUT2 (FUT2-385A and FUT2-385T) is indicated by a blue box, that of SECIP is indicated by a green box, and that of sefus is indicated by green and blue boxes. The relative positions of the primers and probe anneal are indicated by black arrows, and the probe is indicated, in black combined with a fluorophore labeled at the 5' end and a quencher labeled at the 3' end. Nucleotides that differ from the sequence of the probe are indicated by red letters. Alignment of DNA sequences of amplified regions in FMCA; DNA sequences of FUT2 (FUT2-385A: allele of A at rs1047781; FUT2-385T: allele of T at rs1047781; FUSION: sefus allele) and corresponding regions of SEC1P, are indicated (B). Forward primer and reverse primer sequences are shown in bold. The probe sequence is indicated by orange boxes and nucleotides that differ from the sequence of probe are uncolored. Figure 2 Melting peak profiles of FMCA for detection of c.385A>T and sefus. Six Japanese (A) and 96 Japanese subjects (B) whose FUT2 genotypes were already determined were selected. The subjects with genotypes 385A/A (red), 385T/T (green), sefus/sefus (gray), 385A/T (blue), 385A/sefus (pink), and 385T/sefus (yellow) were clearly identified. The negative control is shown in light blue. Figure 3 Melting peak profiles of FMCA for four selected subjects with or without sefus. Melting peak profiles of 385A/A (A), 385A/sefus (B), 385A/T (C), and 385T/sefus (D). The copy number ratio of each peak is indicated. Figure 4 Melting peak profiles of triplex FMCA of 96 Japanese subjects. (A) Results for detection of c.385A>T and sefus of FUT2. The subjects with genotypes between 385A/A and 385A/sefus and between 385A/T and 385T/sefus were not completely separated automatically. The unknown group is indicated in brown. Light blue indicates the negative control. (B) Results of detection of c.59T>G of FUT3. The subjects with genotypes of 59T/T are shown in red, those with genotypes of 59T/G in blue, those with genotypes of 59G/G in green. The negative control is shown in light blue. (C) Results for detection of c.314C>T of FUT3. The subjects with genotypes of 314C/C are shown in blue, those with genotypes of 314C/T in red. The negative control is shown in light blue. diagnostics-13-00931-t001_Table 1 Table 1 FUT2 and FUT3 genotypes and secretors and Lewis blood group phenotypes estimated by the triplex FMCA. c.385A>T Fusion Gene FUT2 Genotype Secretor Phenotype c.59T>G c.314C>T FUT3 Genotype Lewis Phenotype Number A/A - Se/Se Secretor T/T C/C Le/Le Le(a-b+) 11 C/T Le/le202,314 Le(a-b+) 2 T/G C/C Le/le59 Le(a-b+) 7 C/T le59/le202,314 Le(a-b-) 1 G/G C/C le59/le59 Le(a-b-) 3 A/T - Se/Sew Secretor T/T C/C Le/Le Le(a-b+) 13 T/G C/C Le/le59 Le(a-b+) 19 * G/G C/C le59/le59 Le(a-b-) 6 T/T - Sew/Sew Weak secretor T/T C/C Le/Le Le(a+b+) 9 T/G C/C Le/le59 Le(a+b+) 5 G/G C/C le59/le59 Le(a-b-) 8 A/A one copy Se/sefus Secretor T/T C/C Le/Le Le(a-b+) 2 T/G C/C Le/le59 Le(a-b+) 6 G/G C/C le59/le59 Le(a-b-) 1 T/T one copy Sew/sefus Weak secretor T/G C/C Le/le59 Le(a+b+) 2 A/A two copies sefus/sefus Non-secretor T/G C/C Le/le59 Le(a+b-) 1 * One weak secretor with genotypes Sew/se628, estimated by Sanger sequencing analysis, was misdiagnosed as Se/Sew by this FMCA because the nucleotide at position 385 of se628 is an "A"; le59 includes le59, le59,508, and le59,1067. 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PMC10000472 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050687 cells-12-00687 Article Sulforaphane Potentiates Gemcitabine-Mediated Anti-Cancer Effects against Intrahepatic Cholangiocarcinoma by Inhibiting HDAC Activity Tomooka Fumimasa Methodology Formal analysis Investigation Data curation Writing - original draft Kaji Kosuke Conceptualization Methodology Validation Resources Data curation Writing - review & editing Visualization Supervision * Nishimura Norihisa Formal analysis Investigation Writing - review & editing Kubo Takahiro Investigation Writing - review & editing Iwai Satoshi Investigation Writing - review & editing Shibamoto Akihiko Investigation Writing - review & editing Suzuki Junya Investigation Writing - review & editing Kitagawa Koh Software Writing - review & editing Namisaki Tadashi Formal analysis Writing - review & editing Visualization Akahane Takemi Methodology Writing - review & editing Mitoro Akira Writing - review & editing Supervision Yoshiji Hitoshi Conceptualization Resources Writing - review & editing Supervision Cruz-Martins Natalia Academic Editor Department of Gastroenterology, Nara Medical University, Kashihara, Nara 634-8521, Japan * Correspondence: [email protected]; Tel.: +81-744-22-3051; Fax: +81-744-24-7122 22 2 2023 3 2023 12 5 68731 1 2023 19 2 2023 20 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Intrahepatic cholangiocarcinoma (iCCA), the second most common primary liver cancer, has high mortality rates because of its limited treatment options and acquired resistance to chemotherapy. Sulforaphane (SFN), a naturally occurring organosulfur compound found in cruciferous vegetables, exhibits multiple therapeutic properties, such as histone deacetylase (HDAC) inhibition and anti-cancer effects. This study assessed the effects of the combination of SFN and gemcitabine (GEM) on human iCCA cell growth. HuCCT-1 and HuH28 cells, representing moderately differentiated and undifferentiated iCCA, respectively, were treated with SFN and/or GEM. SFN concentration dependently reduced total HDAC activity and promoted total histone H3 acetylation in both iCCA cell lines. SFN synergistically augmented the GEM-mediated attenuation of cell viability and proliferation by inducing G2/M cell cycle arrest and apoptosis in both cell lines, as indicated by the cleavage of caspase-3. SFN also inhibited cancer cell invasion and decreased the expression of pro-angiogenic markers (VEGFA, VEGFR2, HIF-1a, and eNOS) in both iCCA cell lines. Notably, SFN effectively inhibited the GEM-mediated induction of epithelial-mesenchymal transition (EMT). A xenograft assay demonstrated that SFN and GEM substantially attenuated human iCCA cell-derived tumor growth with decreased Ki67+ proliferative cells and increased TUNEL+ apoptotic cells. The anti-cancer effects of every single agent were markedly augmented by concomitant use. Consistent with the results of in vitro cell cycle analysis, G2/M arrest was indicated by increased p21 and p-Chk2 expression and decreased p-Cdc25C expression in the tumors of GEM-treated mice. Moreover, treatment with SFN inhibited CD34-positive neovascularization with decreased VEGF expression and GEM-induced EMT in iCCA-derived xenografted tumors. In conclusion, these results suggest that combination therapy with SFN with GEM is a potential novel option for iCCA treatment. chemoresistance angiogenesis EMT cell cycle arrest apoptosis This research received no external funding. pmc1. Introduction Intrahepatic cholangiocarcinoma (iCCA) is the second most common hepatic malignancy arising from intrahepatic bile duct epithelium . The prognosis of iCCA is poor because of early local invasion; metastasis to the liver, lymph nodes, and other organs; and insufficient early diagnosis . Currently, only a small number of patients with iCCA can undergo curative resection. Meanwhile, the treatment landscape of unresectable advanced iCCA has primarily been limited to chemotherapy. At present, the first-line chemotherapy for unresectable iCCA is gemcitabine (GEM) and cisplatin (CDDP) based on the ABC-02 study, and second-line chemotherapy includes 5-fluorouracil, folinic acid, and oxaliplatin (FOLFOX) based on the ABC-06 study . However, median overall survival, even with these options, is limited to just one year . Additionally, combination treatment with multiple anti-cancer drugs often results in severe adverse effects . Currently, several approaches are employed to find novel combinatory treatments with standard chemotherapeutic drugs, including GEM for other types of cancer, such as the highly aggressive diffuse malignant peritoneal mesothelioma and pancreatic ductal adenocarcinoma . Likewise, there is an urgent need to identify novel therapeutic targets for iCCA with less adverse event profiles by combining GEM. Histone deacetylases (HDACs) play a key role in epigenetically regulating the expression and activity of various factors relevant to carcinogenesis and cancer development . HDACs comprise a family of enzymes categorized into four classes in humans based on their homology to yeast HDAC analogs: classes I (HDAC1, 2, 3, and 8), II (HDAC4, 5, 6, 7, 9, and 10), III (sirtuins), and IV (HDAC11). Class I, II, and IV HDACs require zinc-dependent cofactors for their enzymatic activity, and class III HDACs require nicotinamide adenine dinucleotide-dependent cofactors . Histone acetyltransferases (HATs) catalyze the transfer of an acetyl group from acetyl coenzyme A, while HDACs remove acetyl groups from histones and organize a non-permissive chromatin conformation, leading to interference with the transcription of cancer-related genes . Aberrant HDAC activity leads to diverse transcriptional gene regulation relevant to cancer cell differentiation, angiogenesis, proliferation, apoptosis, migration, and metastasis . HDAC activity represses p53 and BAX and induces BCL-2, which promotes cell cycle progression and regulates apoptosis in cancer cells . Morine et al. have reported that intratumor HDAC expression is positively correlated with HIF-1a, a stimulus factor for local hypoxia and increased angiogenesis in resected iCCA tissues . Thus, HDAC inhibitors have the potential to thwart cell growth, accelerate differentiation, and induce apoptosis, and they have been proposed as novel therapeutic options for a variety of malignancies, including iCCA . Sulforaphane (SFN), an isothiocyanate cleavage product of glucoraphanin, can be obtained from damaged cruciferous vegetables such as broccoli, cauliflower, cabbage, and Brussels sprouts . SFN possesses anti-oxidative properties with multiple pharmacological actions, including anti-diabetic and anti-microbial effects . Remarkably, SFN has been suggested to display anti-cancer and chemopreventive properties by inhibiting HDAC activity and epigenetically modifying the expression of critical cytoprotective genes involved in the regulation of the cell cycle and apoptosis . A recent report revealed that SFN could inhibit total HDAC activity in cancer cells . Moreover, recent findings indicated that SFN augments the response to several carcinostatic agents by enhancing the sensitivity and suppressing the resistance of cancer cells to these agents . Based on these findings, the present study investigated the combinatorial effect of SFN and GEM on human iCCA cell growth and malignant potential using iCCA-derived murine xenograft models. 2. Materials and Methods 2.1. Compounds and Cell Culture d,l-sulforaphane (1-isothiocyanate-4-methylsulphinylbutane, purity >= 98%) was purchased from Toronto Research Chemicals Inc. (Toronto, ON, Canada), and gemcitabine (2'-deoxy-2',2'-difluorocytidine, purity >= 98%) was purchased from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan). Two human iCCA cell lines, HuCCT-1 (cat: JCRB0425) and HuH28 (cat: JCRB0426) were obtained from the Japanese Collection of Research Bioresources Cell Bank (Osaka, Japan). These cells were cultured in RPMI-1640 (Nacalai Tesque, Inc., Kyoto, Japan) supplemented with 10% fetal bovine serum (FBS) and 1% ampicillin/streptomycin. The primary human biliary epithelial cell line (HIBEpiC, cat: #5100) was purchased from ScienCell Research Laboratories, Inc. (Carlsbad, CA, USA). HIBEpiC cells were cultured in Epithelial Cell Medium (ScienCell Research Laboratories) supplemented with 2% FBS and 1% epithelial cell growth supplement (ScienCell Research Laboratories), and 1% ampicillin/streptomycin. The cells were grown at 37 degC in a 5% CO2 atmosphere. 2.2. Human iCCA Xenograft Model Six-week-old male athymic nude mice (BALB/cSlc-nu/nu) (Japan SLC, Inc., Shizuoka, Japan) were housed in stainless steel mesh cages (2/cage) under controlled conditions (temperature: 23 +- 3 degC, relative humidity: 50 +- 20%, 10-15 air changes/h, illumination: 12 h/d). The animals were allowed tap water access ad libitum throughout the study period. Eighty mice were used in total for the xenograft assay, and tumor inoculation was performed as described . Briefly, a million cells were suspended in 200 mL of medium containing Matrigel (Corning, Tewksbury, MA, USA; 1:1), and the same type of million cells was inoculated subcutaneously into the bilateral flanks of each mouse. Tumors were measured with a caliper, and the tumor volume was calculated using the following formula:(1) 12[(Width)2xLength] Five days after inoculation, mice were orally administered with SFN (50 mg/kg/day) or intraperitoneally injected with GEM (100 mg/kg) twice a week or concomitant administration (n = 10). Saline solution was equivalently given to the vehicle group (n = 10). The condition and health of mice were monitored daily after the injection of tumor cells, and all mice were sacrificed 30 days after drug administration under anesthesia with barbiturate overdose (intravenous injection, 150 mg/kg pentobarbital sodium). All the animal procedures were performed as per the recommendations of the Guide for Care and Use of Laboratory Animals (National Research Council, Washington, DC, USA). The study was approved by the animal facility committee of Nara Medical University (Authorization number: #12853). 2.3. Detection of HDAC/HAT Activity and Total Histone H3 and H4 Acetylation HuCCT-1 and HuH28 cells were treated with different concentrations of SFN (0-80 mM) or GEM (0-10 mM) for 3 h. To measure HDAC activity, nuclear extracts were obtained from cultured cells or 20 mg of subcutaneous tumor samples using an EpiQuikTM Nuclear Extraction Kit (Epigentek, Farmingdale, NY, USA) according to the manufacturer's protocol. HDAC activity was measured in 10 mg of nuclear extract using an EpiQuikTM HDAC activity/inhibition assay kit (Epigentek) according to the manufacturer's instructions. HAT activity was also measured in 10 mg of nuclear extract from cultured cells using an EpiQuikTM HAT activity/inhibition assay kit (Epigentek) according to the manufacturer's instructions. To detect total histone H3 and H4 acetylation, histone extracts were obtained from cultured cells using an EpiQuikTM Total Histone Extraction Kit (Epigentek). Histone H3 and H4 acetylation was detected in 100 ng of histone extract using an EpiQuikTM Total Histone H3 Acetylation Detection Fast Kit and an EpiQuikTM Total Histone H4 Acetylation Detection Fast Kit (Epigentek) according to the manufacturer's instructions, respectively. Dimethyl sulfoxide (DMSO, Nacalai Tesque, Inc.) was used as a vehicle, and HDAC activity and total histone H3 acetylation in cells treated with SFN and/or GEM were measured relative to that in the vehicle treatment group. 2.4. Histone H3 Peptide Array HuCCT-1 and HuH28 cells were treated with a concentration of dimethyl sulfoxide (DMSO, Nacalai Tesque, Inc.) as a vehicle or SFN (20 mM) for 3 h. Nuclear extracts were obtained from cultured cells using an EpiQuikTM Nuclear Extraction Kit (Epigentek, Farmingdale, NY, USA) according to the manufacturer's protocol. To profile the binding specificity of histone H3 acetylation, we used a Pre-SureTM Histone H3 Peptide Array ELISA Kit (Epigentek) according to the manufacturer's instructions and previous report . Total nuclear extracts were diluted to 1 ug/mL, added to the array plate and incubated for 2 h at room temperature. Histone H3 Acetylation Antibody Panel Pack I and Pack II (Epigentek) were applied as primary antibodies to detect the binding of H3 lysines (K)9, K14, K18, K27, K36, K56, and K79 to histone peptides. Following the incubation with primary antibodies at 37 degC for 60 min, samples were incubated with secondary antibodies (0.4 mg/mL) at room temperature for 60 min and then developed at room temperature for 10 min away from light. Arbitrary units were measured at the absorbance (450 nm) to represent the relative levels of binding specificity and calculated the ratio to the values of Veh treatment. 2.5. Cell Viability Assay and Analysis of Cytotoxic Synergy HuCCT-1 and HuH28 cells were seeded in 96-well plates with RPMI-1640, as previously described. Then, the cells were treated with different doses of SFN (0-80 mM) or GEM (0-10 mM) for 24 h. Cell viability was evaluated by The Premix Water-Soluble Tetrazolium salt (WST)-1 Cell Proliferation Assay system (Takara Bio, Kusatsu, Japan) according to the manufacturer's protocol. Cell viability was assessed relative to that in the groups without each treatment, and half-maximal inhibitory concentration (IC50) was calculated via non-linear regression analysis using GraphPad Prism 9 ver 9.3.1 (GraphPad Software Inc., La Jolla, CA, USA) . To assess the synergy of drug combinations, a combination index (CI) was calculated by the Chou-Talalay method using CompuSyn software version 1.0 (ComboSyn, Inc., New York, NY, USA) . CI gives a quantitative definition of synergism (CI < 1), additive effect (CI = 1), and antagonism (CI > 1). For this purpose, the cells were also exposed to different concentrations of SFN and GEM for 24 h. 2.6. Statistical Analysis All data were statistically analyzed using GraphPad Prism 9 software. Data were indicated as the mean +- standard deviation (SD). Means were compared between two groups by Student's t-test. A one-way analysis of variance followed by Bonferroni's post hoc test was performed for multiple comparisons. p < 0.05 denoted a statistically significant difference. Additional methods can be found online in the Supplementary Material. 3. Results 3.1. SFN Attenuates HDAC Activity and Promotes Histone H3 Acetylation in Human iCCA Cells We initially examined the effects of SFN and GEM on HDAC activity, moderately differentiated HuCCT-1 cells and undifferentiated HuH28 cells. As presented in Figure 1A,B, SFN concentration-dependently reduced HDAC activity in both HuCCT-1 and HuH28 cells, and the suppressive effects were significant at concentrations exceeding 20 mM. On the contrary, GEM did not alter HDAC activity in these cells at any concentration . Meanwhile, the activity of HAT, a key enzyme that acetylate conserved lysine amino acids on histone proteins, was significantly increased by treatment with SFN at concentrations exceeding 20 mM . Reflecting the reduced HDAC activity, total histone H3 acetylation in both iCCA cell lines was increased by treatment with SFN in a concentration-dependent manner . On the other hand, total histone H4 acetylation was not altered by treatment with SFN . We further determined the acetylation patterns of specific lysine residues on the tails of histone H3 modified by treatment with SFN in iCCA cells. To this end, nuclear protein extracts of both HuCCT-1 and HuH28 cells treated with SFN (20 mM) were utilized for the identification of the acetylation profile of H3 on K9, K14, K18, K27, K36, K56 and K79. As shown in Figure 1I,J, treatment with SFN particularly increased acetylation as compared to vehicle treatment at H3K9 and H3K27 in both HuCCT-1 and HuH28 cells. Moreover, we confirmed that SFN did not affect HDAC activity in normal HIBEpiC cells . 3.2. SFN Has a Synergistic Effect with GEM-Mediated Cell Growth Inhibition in Human iCCA Cells Next, we investigated the impact of SFN and GEM at different concentrations on the viability of HuCCT-1 and HuH28 cells. As presented in Figure 2A,B, SFN efficiently ameliorated HuCCT-1 and HuH28 cell viability with IC50 values of 27.4 and 34.2 mM, respectively. Meanwhile, GEM attenuated the viability of both cell lines (IC50 of 0.57 mM for HuCCT-1 cells and 0.71 mM for HuH28 cells) as expected . Both agents did not affect the cell viability of normal HIBEpiC at this range of concentrations . Based on the optimal concentrations, we calculated CI to evaluate whether the cytotoxic effect of combined SFN and GEM against iCCA cell growth is synergistic against iCCA cell growth. As shown in Figure 2C, the CI values calculated by CompuSyn software were 0.552/0.624/0.497, 0.228/0.406/0.183, and 0.227/0.136/0.119, when SFN (6.8 mM) and GEM (0.14/0.28/0.57 mM), SFN (13.7 mM) and GEM (0.14/0.28/0.57 mM), and SFN (27.4 mM) and GEM (0.14/0.28/0.57 mM) were concurrently administered to HuCCT-1 cells, respectively. These CI values were less than 1.0, indicating that the combination of SFN with GEM has synergistic effects on suppressing the viability of HuCCT-1 cells. Combination treatment with SFN and GEM also exerted a synergistic effect against HuH28 cell viability. The CI values were 0.699/0.738/0.628, 0.519/0.714/0.487, and 0.323/0.414/0.299 when SFN (8.5 mM) and GEM (0.17/0.35/0.71 mM), SFN (17.1 mM) and GEM (0.17/0.35/0.71 mM), and SFN (34.2 mM) and GEM (0.17/0.35/0.71 mM) were concurrently cultivated . We further confirmed that the combination of SFN and GEM at IC50 significantly suppressed the proliferative activity of HuCCT-1 and HuH28 cells in a time-dependent manner . 3.3. SFN Induces G2/M Arrest and Promotes Apoptosis in Human iCCA Cells SFN-mediated HDAC inhibition has been reported to enhance histone acetylation and derepress p21 and BAX gene expression, resulting in the induction of cell cycle arrest/apoptosis in several types of cancer cells . Based on these findings, we examined the effects of SFN on the cell cycle/apoptosis and the expressions of associated genes, including these key targets in human iCCA cells. As presented in Figure 3A,B, SFN or GEM significantly blocked both HuCCT-1 and HuH28 cells in the G2 phase compared to the effects of the vehicle, and the drugs in combination had significantly stronger effects than either agent alone. The mRNA expression of CDKN1A and BAX were significantly increased by treatment with SFN as compared to vehicle treatment in both HuCCT-1 and HuH28 cells . Treatment with SFN as well as GEM upregulated p21 and p-Chk2 and downregulated p-Cdc25C at the protein level, corresponding to the induction of G2/M arrest, in both cell lines . GEM-treated HuCCT-1 and HuH28 cells also increased pro-apoptotic BAX expression and decreased anti-apoptotic BCL-2 expression . In both cell lines, combination treatment augmented the upregulation of BAX compared to the effect of every single agent . SFN and GEM further enhanced the cleavage of caspase-3, reflecting the induction of cell apoptosis in both HuCCT-1 and HuH28 cells . 3.4. SFN Inhibits Cancer Cell Invasion, Migration, Angiogenic Activity, and Epithelial-Mesenchymal Transition (EMT) in Human iCCA Cells Next, we investigated the effects of SFN and GEM on malignant potential, including cell invasion, migration, angiogenic activity, and EMT in human iCCA cells. First, the effects of both agents on the invasiveness of HuCCT-1 and HuH28 cells were evaluated using a Matrigel invasion assay. Either drug alone significantly reduced the invasiveness of both HuCCT-1 and HuH28 cells . It was noteworthy that concomitant treatment with SFN and GEM extensively reduced cell invasion to less than 20% of the control, exceeding the effects of each drug . Correspondingly, cell migration was also suppressed by treatment with SFN or GEM in both iCCA cells . Moreover, combination treatment enhanced the suppressive effect of every single agent . We next examined the effects of SFN on the angiogenic activity of iCCA cells. Treatment with SFN significantly reduced the mRNA expression of pro-angiogenic markers, including VEGFA, VEGFR2, HIF1A, and NOS3 in both HuCCT-1 and HuH28 cells . Moreover, we assessed the effects of both agents on the EMT status. There were differences in EMT-related markers between HuCCT-1 and HuH28 cells, which have different levels of differentiation. Specifically, HuCCT-1 cells, which are moderately differentiated, exhibited higher expression of the epithelial markers CDH1 and KRT19 and lower expression of the mesenchymal markers CDH2, VIM, MMP2, and MMP9 than undifferentiated HuH28 cells, consistent with a previous report . As presented in Figure 4G,H, treatment with GEM downregulated the epithelial markers and upregulated the mesenchymal markers in HuCCT-1 and HuH28 cells, indicating the EMT progression. Notably, SFN efficiently inhibited the GEM-induced progression of EMT in iCCA cells . 3.5. SFN Potentiates the GEM-Mediated Reduction of the Human iCCA-Derived Xenograft Tumor Growth Given the suppressive effects of SFN and GEM on human iCCA cell growth, the anti-cancer property of both agents was examined using iCCA-derived xenograft models . Initially, we determined the experimental dose of SFN for in vivo study. As SFN is also known to exert anti-oxidative effects via Nrf2 activation, we measured the hepatic mRNA levels of anti-oxidative markers in nude mice treated with different doses of SFN to identify a dose that could exert bioactivity in mice . As presented in Figure S2, oral administration of SFN for four weeks increased the hepatic mRNA expression of Hmox1, Nqo1, and Gstm3 in a dose-dependent manner even with concomitant GEM treatment (100 mg/kg twice a week), and we identified 50 mg/kg/day as the minimal dose that significantly induced these anti-oxidative genes. Based on this result, we employed 50 mg/kg/day as the experimental dose for the xenograft assay. Serological assessments revealed that this dose of SFN did not cause hepatocellular, biliary, or renal damage in mice, even when used together and combined with GEM . In mice treated with either SFN (50 mg/kg/day) or GEM (100 mg/kg twice a week), the HuCCT-1 and HuH28-grafted subcutaneous tumor growth was markedly attenuated . After treatment for 30 days, the subcutaneous tumor volumes and weights were significantly reduced in mice treated with either SFN or GEM relative to the findings in vehicle-treated mice . Notably, concomitant treatment with both agents significantly potentiated their inhibitory effects on tumor growth relative to every single agent . H&E staining illustrated that the viable cancer area in resected subcutaneous tumors was decreased by treatment with SFN and GEM . We confirmed that the utilized dose of SFN effectively decreased HDAC activity in the resected subcutaneous tumor tissues to less than 60% of that in the vehicle group . 3.6. SFN Suppresses Cell Proliferation and Induces Apoptosis in Human iCCA-Derived Xenograft Tumors We next quantitatively investigated cancer cell viability in xenograft tumors derived from HuCCT-1 and HuH28 cells . In HuCCT-1-derived xenograft tumors, Ki67-positive cancer cell proliferation was attenuated by each drug alone, and the effect was enhanced by using the drugs in combination . Quantitative analysis revealed the potent reduction of proliferative cells to less than 20% of the control level by combination treatment . Treatment with SFN and GEM significantly increased the nuclear expression of p21 and cytosolic expression of p-Chk2 and conversely decreased the expression of p-Cdc25C . These findings aligned with the observation of G2/M arrest following treatment with SFN and GEM in iCCA cells. Meanwhile, we found that TUNEL-positive cell apoptosis was simultaneously increased by treatment with SFN and GEM in HuCCT-1-derived xenograft tumors . Notably, the effects of SFN and GEM on intratumor cancer cell viability were also observed in the HuH28-derived xenograft tumors 3.7. SFN Attenuates Intratumor Angiogenesis and GEM-Mediated EMT in Human iCCA-Derived Xenograft Tumors Moreover, the effects of SFN and GEM on malignant potential, including pathological angiogenesis and EMT in the xenograft tumors, were examined according to the findings of the in vitro study. As presented in Figure 7A, CD34-positive neovascularization in xenograft tumors derived from both HuCCT-1 and HuH28 was significantly reduced by treatment with SFN. However, these anti-angiogenic effects were not observed in GEM-treated mice . The semi-quantitative analysis illustrated that the number of new CD34-positive intratumor vessels was decreased by 50% in SFN-treated mice compared to that in vehicle-treated mice . In parallel with reduced neovascularization, the intratumor expression of VEGFA and VEGFR2 was decreased in SFN-treated mice . Regarding EMT-related markers, we found that the intratumor mRNA expression of epithelial markers (CDH1 and KRT19) was decreased in GEM-treated mice, and this effect was efficiently inhibited by SFN treatment . In contrast, treatment with SFN considerably attenuated the GEM-mediated increases in mesenchymal markers . Moreover, the effects of both agents on EMT-related markers were similarly observed at the protein levels . These findings indicate that SFN ameliorated resistance to GEM by suppressing tumor angiogenesis and EMT in iCCA cells. 4. Discussion This study first demonstrated that SFN, a phytochemical isothiocyanate agent, effectively augmented the inhibitory effect of GEM on iCCA growth. Our results demonstrated that SFN exerted multifunctional properties against the malignant potential of iCCA, including anti-proliferative, pro-apoptotic, anti-invasive/migratory, anti-EMT and anti-angiogenic effects. As the functional mechanism underlying these effects of SFN, we suggested the inhibitory action on HDAC activity as well as the inductive action on HAT activity leading to enhancement of histone H3, particularly H3K9 and H3K27 acetylation. Previous studies reported that the dysfunction of HDAC enzymes and altered acetylation status is relevant to the growth and malignant progression of CCA, including iCCA, and several HDAC inhibitors have displayed suppressive effects on iCCA . For instance, chidamide, an HDAC inhibitor, has been reported to exert antitumor activities in iCCA by promoting HDAC3-mediated forkhead box O1 acetylation . Another report has shown that peanut testa possessing HDAC inhibitory activity induces apoptosis in iCCA cells . Moreover, a recent report has demonstrated that SFN increases HAT activity in human malignant melanoma cells . These pieces of evidence support the possible involvement of epigenetic modification in the SFN-mediated anti-cancer property against human iCCA cells in our study. On the other hand, we found that SFN did not affect histone H4 acetylation. The present study did not identify a pharmacological mechanism to explain the differential effect of sulforaphane on H3 and H4 acetylation. Thus, a detailed analysis is required in the future. The present study primarily elucidated that SFN effectively suppressed cell proliferation in both moderately differentiated and undifferentiated iCCA lines. Several reports have shown that SFN-mediated anti-cancer effects were involved in an increase of acetylated histone H3 specifically associated with the promoter region of the p21 and BAX genes in cancer cells . Consistently with this evidence, our results showed that SFN increased p21 expression leading to the phosphorylation of Chk2 and dephosphorylation of Cdc25C, and consequently, it blocked cell cycle progression in the G2/M phase in human iCCA cells. SFN also upregulated BAX expression, downregulated BCL-2 expression, and suppressed the cleavage of caspase-3, indicating the activation of the mitochondrial apoptotic pathway. It is known that H3K9ac and H3K27ac are highly correlated with transcriptional activation . Therefore, we hypothesized that SFN-mediated HDAC inhibition possibly promoted the transcriptional activity of p21 and BAX by binding to both genes, enhancing the binding of active modification of histones such as H3K9ac and H3K27ac to regulate the expressions of both genes, thereby suppressing cell proliferation and augmenting cell apoptosis. However, further investigation is necessary to clarify the histone acetylation in the promoters of p21 and BAX, as well as the possible targets downstream of decreased HDAC in SFN-treated human iCCA cells. Of note, present results showed that a combination of SFN and GEM was likely to ameliorate xenograft iCCA tumor progression more potently than cultured cell growth. This discrepant finding is suggested to be attributable to the impact of SFN on other malignant phenotypes, including cell invasion, angiogenesis, and EMT. The combination treatment of SFN and GEM effectively suppressed cell invasion and migration at the doses with tolerable cytotoxicity, consistent with the results from Wang et al. that co-treatment of iCCA cells with several types of HDAC inhibitors (trichostatin A and valproic acid) and GEM inhibited cell invasion, migration . Moreover, we found that treatment with GEM accelerated EMT, as indicated by the downregulation of epithelial markers and upregulation of mesenchymal markers in both cultured iCCA cells and xenografted tumors. It was noteworthy that SFN effectively inhibited GEM-induced EMT in both iCCA cell lines. Among the malignant phenotypes, EMT has recently gained attention as a potential mechanism of chemoresistance because of its ability to promote the acquisition of cancer stemness and confer resistance to chemotherapy . Indeed, resistance to GEM in iCCA is also associated with EMT phenotype and cancer stem-like properties in the tumor . EMT is regulated by epigenetic changes, including histone modifications, and HDAC inhibitors are considered to modify EMT-related factors' expression depending on the cancertype . Meanwhile, SFN is reported to inhibit EMT in several cancer cell types by molecular mechanisms independently of histone modification . Recent studies illustrated that SFN could suppress the EMT in lung cancer cells by inhibiting the GSK3b/b-catenin pathway and ERK5 activation . Li et al. also demonstrated that SFN-mediated inhibition of the sonic hedgehog-GLI pathway resulted in the suppression of EMT in pancreatic cancer . These findings evoke a hypothesis that the SFN-mediated suppression of EMT in iCCA cells involves mechanisms beyond the inhibition of HDACs. Thus, additional analyses are needed to clarify the underlying mechanism. Furthermore, tumor-associated angiogenesis and VEGF expression are known to be correlated with iCCA cancer progression, metastasis, and prognosis . A previous observational study found that VEGF was expressed in 53.8% of 106 patients with iCCA, and it was significantly associated with intrahepatic metastasis . Notably, SFN exerts anti-angiogenic effects by inhibiting hypoxia-induced HIF-1a and VEGF expression in several cancers, including prostate, colon, and liver cancers . Moreover, SFN has been demonstrated to directly suppress proliferation, tubular formation, and matrix metalloproteinase production in vascular endothelial cells . We substantiated that SFN reduced the expression of pro-angiogenic genes such as VEGFA, VEGFR2, HIF-1a, and eNOS in iCCA cells and attenuated CD34-positive neovascularization in xenografted tumors. As the inhibition of angiogenesis has been reported to abolish chemoresistance to GEM, this anti-angiogenic property of SFN is potently associated with the augmentation of GEM-mediated anti-cancer effects on iCCA . The empirical results reported in this study should be considered in light of some limitations. First, we demonstrated that the combination of SFN and GEM synergistically augmented the anti-cancer effect on human iCCA cells by calculating the CI. However, our study did not fully elucidate the pharmacological interaction between both agents to explain this synergistic effect. Although the inhibition of GEM-induced EMT by SFN is likely to be associated with this synergy, we will probably need further detailed research by comprehensive molecular profiling. Second, although we defined the dose of SFN (50 mg/kg/day) for the in vivo study, optimization is performed by evaluating the anti-oxidative property of SFN in the liver. We confirmed that this dose efficiently reduced HDAC activity in the xenografted tumors. Additionally, we observed that the doses of SFN and GEM did not cause hepatic, biliary, or renal toxicity in mice. Thus, these doses are assumed to be within the tolerance range for in vivo experiments. Third, the current first-line chemotherapy for iCCA is based on GEM and CDDP. Therefore, additional study is necessary to substantiate the enhanced efficacy of GEM and CDDP in combination with SFN in the latest clinical setting. In summary, the present study demonstrated that combination with SFN synergistically augments the tumor suppressive effects of GEM on human iCCA cell growth. This effect of SFN is based on the inhibition of HDACs, leading to G2/M arrest; apoptosis; and suppressed invasion, migration, EMT, and angiogenesis. As a less-toxic phytochemical, SFN might eventually emerge as a viable modulator of GEM for patients with advanced iCCA. Supplementary Materials The following supporting information can be downloaded at: Figure S1: HDAC activity and cell viability in normal biliary epithelial cells; Figure S2: Effect of SFN on hepatic expression of anti-oxidative genes; Figure S3: Liver, biliary and renal function in the HuCCT-1 and HuH28-xenografted mice; Figure S4: Cell proliferation and apoptosis in iCCA-derived xenograft tumors by treatment with SFN and GEM; Figure S5: Protein levels of EMT-related markers in human iCCA-derived xenograft tumors;Table S1: List of primers for quantitative RT-PCR; Supplementary materials and methods . Click here for additional data file. Author Contributions F.T.: Data curation (lead); Investigation (lead); Formal analysis (lead); Methodology (supporting); Writing--Original Draft Preparation (lead). K.K. (Kosuke Kaji): Conceptualization (lead); Data curation (equal); Methodology (supporting); Resources (equal); Supervision (supporting); Validation (supporting); Visualization (lead); Writing--Review and Editing (lead). N.N.: Formal analysis (equal); Investigation (supporting); Writing--Review and Editing (supporting). T.K., S.I., A.S. and J.S.: Investigation (supporting); Writing--Review and Editing (supporting). K.K. (Koh Kitagawa): Software (lead); Writing--Review and Editing (supporting). T.N.: Formal analysis (supporting); Visualization (equal); Writing--Review and Editing (supporting). T.A.: Methodology (lead); Writing--Review and Editing (supporting). A.M.: Supervision (equal); Writing--Review and Editing (supporting). H.Y.: Conceptualization (equal); Resources (lead); Supervision (lead); Writing--Review and Editing (equal). All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal procedures complied with the recommendations of the Guide for Care and Use of Laboratory Animals (National Research Council of Japan), and the study was approved by the ethics committee of Nara Medical University, Kashihara, Japan (Authorization No. 12853). Informed Consent Statement Not applicable. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. These funders had no role in the main experimental equipment, supply expenses, study design, data collection and analysis, decision to publish, or preparation of this manuscript. Figure 1 HDAC activity and histone H3 acetylation by treatment with SFN in iCCA cells. (A-H) HDAC activity (A,B), HAT activity (C,D), total histone H3 acetylation (E,F), and total histone H4 acetylation (G,H) in HuCCT-1 and HuH28 cells treated with SFN (0-80 mM). The values are shown as fold changes relative to 0 mM for each treatment group. Data are mean +- SD (n = 3 independent experiments with n = 8 samples per condition). ** p < 0.01 compared with the group treated with vehicle (Veh) at the same concentration. (I,J) Graphical analysis of the binding intensity of H3K9ac, H3K14ac, H3K18ac, H3K27ac, H3K36ac, H3K56ac, and H3K79ac in HuCCT-1 (I) and HuH28 (J) cells treated with SFN (20 mM) by using Histone H3 Peptide Array ELISA Kit. The values are shown as fold changes relative to Veh treatment at the same concentration. Figure 2 Cell viability and proliferation by treatment with SFN and GEM in iCCA cells. (A,B) Cell viability and IC50 in HuCCT-1 (A) and HuH28 (B) cells treated with SFN (0-80 mM) or GEM (0-10 mM). (C,D) The synergism of SFN and GEM on HuCCT-1 (C) and HuH28 (D) was evaluated by the combination index (CI) values. CI gives a quantitative definition of synergism (CI < 1), additive effect (CI = 1), and antagonism (CI > 1) (E,F). Cell proliferation of HuCCT-1 and HuH28 cells incubated with SFN and/or GEM at each IC50 for 0-48 hrs. The values are shown as fold changes relative to 0 mM for each treatment group (A,B) and the values at the start of each treatment (E,F). Data are mean +- SD (n = 3 independent experiments with n = 8 samples per condition) (A,B,E,F). * p < 0.05, ** p < 0.01 compared with the values of 0 mM for each treatment group (A,B). a p < 0.01, b p < 0.01, c p < 0.01 compared with the group treated for 48 h with Veh, SFN or GEM, respectively (E,F). Figure 3 Cell cycle and apoptosis by treatment with SFN and GEM in iCCA cells. (A,B) Representative images of flow cytometric analysis for cell cycle distribution and percentages of cells at different cell cycle phases (G0/G1, S and G2/M) in HuCCT-1 (A) and HuH28 (B) cells treated with SFN and/or GEM. After the incubation with both agents for 12 h, cells were stained with propidium iodide (PI) and subjected to flow cytometry. (C) Relative mRNA levels of CDKN1A and BAX in HuCCT-1 and HuH28 cells. (D,E) Western blots for the markers related to G2/M arrest, p21, p-Chk2(Thr68) and p-Cdc25C(Ser216) (D), and the markers related to apoptosis, BAX and BCL-2 (E). (F) Cleaved caspase-3 level in HuCCT-1 or HuH28-cultured media. The mRNA expression levels were measured by quantitative RT-PCR (qRT-PCR), and GAPDH was used as an internal control for qRT-PCR (C). Actin was used as an internal control for western blotting (D,E). The values are shown as fold changes relative to the vehicle-treated group (Veh) (C,F). Data are mean +- SD (n = 3 independent experiments with n = 3 for A and B, n = 8 for C,F). a p < 0.01, b p < 0.01, c p < 0.01 compared with the group treated with Veh, SFN or GEM, respectively. Figure 4 Cell invasion, pro-angiogenic property and EMT by treatment with SFN and GEM in iCCA cells. (A) Representative images of invasive HuCCT-1 and HuH28 cells treated with SFM and/or GEM. Scale bar; 50 mm. Red arrow; invasive cells. (B) Quantification of both cell lines invasion. (C) Quantification of both cell lines migration. (D,E) Relative mRNA expression of pro-angiogenic markers (VEGFA, VEGFR2, HIF1A, and NOS3) in HuCCT-1 and HuH28 treated with SFN and/or GEM. (F) Comparison between HuCCT-1 and HuH28 in the relative mRNA expression of the epithelial markers (CDH1 and KRT19) and mesenchymal markers (CDH2, VIM, MMP2 and MMP9) related to EMT. (G,H) Relative mRNA expression of epithelial markers (G) and mesenchymal markers (H) in HuCCT-1 and HuH28 treated with SFN and/or GEM. GAPDH was used as an internal control for qRT-PCR. The values are shown as fold changes relative to the vehicle-treated group (Veh) (B-E,G,H) or the values of the HuCCT-1 group (F). Data are mean +- SD (n = 3 independent experiments with n = 6 for B and n = 8 for B-G samples per condition); a p < 0.01, b p < 0.01, c p < 0.01 compared with the group treated with Veh, SFN or GEM, respectively (B-E,G,H). ** p < 0.01, indicating a significant difference between groups (F). Figure 5 iCCA-derived xenograft tumor growth by treatment with SFN and GEM.(A) Experimental protocol. (B) Time course of HuCCT-1 and HuH28-grafted tumor volumes. (C) Representative images and weights of resected tumors at the end of the experiment. (D) Representative pictures of HuCCT-1 and HuH28-grafted subcutaneous tumors stained with H&E. C; cancerous lesions, Scale bar; 100 mm. (E) HDAC activity in the resected subcutaneous tumor tissues. The values are shown as fold changes to the vehicle-treated group (E). Data are mean +- SD (n = 20 tumors/10 mice; B,C,E). a p < 0.01, b p < 0.01, c p < 0.01 compared with the group treated with Veh, SFN or GEM, respectively at the end of the experiment (B). * p < 0.05, ** p < 0.01, indicating a significant difference between groups (C,E). Figure 6 Cell proliferation and apoptosis in iCCA-derived xenograft tumors by treatment with SFN and GEM. (A,C,F) Representative images of HuCCT-1-grafted tumors stained with Ki67 (A), p21, p-Chk2, and p-Cdc25C (C), TUNEL (F). Red triangles indicate intratumor apoptotic cells. Scale bar; 100 mm. (B) Quantification of Ki67+ proliferative cancer cells. The values are indicated as Ki67+ cancer cells/total cancer cells (%) in high power field (HPF). (D) Quantification of p21+ cancer cells. Quantitative values are indicated as p21+ cancer cells/total cancer cells (%) in HPF. (E) Semi-quantitation of p-Chk2+ or p-CdC25C+ cancer cells in HPF. The values are shown as fold changes relative to the vehicle-treated group. (G) Quantification of TUNEL+ apoptotic cancer cells. The values are indicated as TUNEL+ cancer cells/total cancer cells (%) in HPF. Each quantitative analysis was performed for 10 fields per section. Data are mean +- SD (n = 20 tumors/10 mice; B,D,E,G). * p < 0.05, ** p < 0.01, indicating a significant difference between groups. Figure 7 Intratumor angiogenesis and EMT in iCCA-derived xenograft tumors by treatment with SFN and GEM. (A) Representative images of CD34+ neovascularization in the HuCCT-1 and HuH28-grafted tumors. Scale bar; 100 mm. (B) Semi-quantitation of CD34+ vessels in the high-power field (HPF) by ImageJ software. Quantitative analysis included 10 fields per section. (C,D) Relative mRNA expression of pro-angiogenic VEGFA and VEGFR2 (C) and epithelial CDH1 and KRT19/mesenchymal CDH2, VIM, MMP2 and MMP9 (D) in the HuCCT-1 and HuH28-grafted subcutaneous tumors. GAPDH was used as an internal control for qRT-PCR. 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PMC10000473 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050908 diagnostics-13-00908 Article A Novel Strategy to Fit and Validate Physiological Models: A Case Study of a Cardiorespiratory Model for Simulation of Incremental Aerobic Exercise Sarmiento Carlos A. 1* Serna Leidy Y. 23 Hernandez Alher M. 1 Mananas Miguel A. 23 Tehrani Fleur T. Academic Editor 1 Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Department, Engineering Faculty, Universidad de Antioquia UdeA, Calle 70 # 52-51, Medellin 050016, Colombia 2 Departament d'Enginyeria de Sistemes, Automatica i Informatica Industrial (ESAII), Universitat Politecnica de Catalunya, 08028 Barcelona, Spain 3 CIBER de Bioingenieria, Biomateriales y Nanomedicina (CIBER-BBN), 28040 Madrid, Spain * Correspondence: [email protected] 27 2 2023 3 2023 13 5 90824 1 2023 17 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Applying complex mathematical models of physiological systems is challenging due to the large number of parameters. Identifying these parameters through experimentation is difficult, and although procedures for fitting and validating models are reported, no integrated strategy exists. Additionally, the complexity of optimization is generally neglected when the number of experimental observations is restricted, obtaining multiple solutions or results without physiological justification. This work proposes a fitting and validation strategy for physiological models with many parameters under various populations, stimuli, and experimental conditions. A cardiorespiratory system model is used as a case study, and the strategy, model, computational implementation, and data analysis are described. Using optimized parameter values, model simulations are compared to those obtained using nominal values, with experimental data as a reference. Overall, a reduction in prediction error is achieved compared to that reported for model building. Furthermore, the behavior and accuracy of all the predictions in the steady state were improved. The results validate the fitted model and provide evidence of the proposed strategy's usefulness. fitting mathematical modeling sensitivity analysis parameter estimation cardiorespiratory system aerobic exercise Administrative Department of Science, Technology, and Innovation (Colciencias), ColombiaMinisterio de Ciencia, Tecnologia e Innovacion (MINCIENCIAS), Colombia111593093015 Ministry of Science and Innovation (MICINN), SpainPID2020-117751RB-I00 This research was funded by the Administrative Department of Science, Technology, and Innovation (Colciencias), Colombia, scholarship 647 of 2014; Ministerio de Ciencia, Tecnologia e Innovacion (MINCIENCIAS), Colombia, under the project "Desarrollo y validacion de un dispositivo para la terapia y el monitoreo de pacientes con enfer-medad pulmonar obstructiva cronica en manejo domiciliario e intrahospitalario", code 111593093015; and the Ministry of Science and Innovation (MICINN), Spain, under contract PID2020-117751RB-I00. pmc1. Introduction Mathematical modeling is an interdisciplinary field that, applied to medicine, has allowed a better understanding of physiological functions and relationships. Its support in this field has been related to the education and training of clinical staff, the identification, monitoring, and treatment of diseases, and equipment development . Mathematical models of physiological systems constitute approximations fitted to bounded populations and specific sets of physiological events or stimuli, so their practical and conceptual utility depends on their ability to predict experimental measurements of physiological variables . Its mathematical complexity increases with accuracy and physiological relevance, so the number of parameters and equations is considerably high for describing the regulation mechanisms of the most complex physiological systems . The cardiorespiratory system stands out as one of the most relevant physiological systems regarding the diagnosis, treatment, monitoring, and prevention of diseases, mainly due to the importance and usefulness of their related variables for the identification of the correct state and functioning of the organism . The cardiorespiratory variables result from different and complex regulatory mechanisms focused on maintaining correct physiological functioning, even under different external conditions, such as diseases . Different mathematical models have focused on the cardiorespiratory system, highlighting its support for personalized diagnosis applications due to its ability to be fitted to a subject or population under a specific stimulus . Physical exercise is a natural stimulus that generates significant cardiorespiratory variations that cannot be evidenced under resting conditions and constitute a well-defined characteristic pattern in healthy human subjects . Several mathematical models of the cardiorespiratory system have been proposed, but few of them can correctly represent the human response to exercise. The handicaps of those reported models to simulate the cardiorespiratory response to this stimulus are diverse. For instance, although some physiological models detail some behaviors, they do not consider important mechanisms of neuronal regulation and omit the prediction of essential variables related to the exercise response. In contrast, other more complete models , despite including a complete description of the systems and allowing the prediction of variables useful for exercise analysis, are not adequate for predicting the human response under the stimulus due to the lack of related physiological mechanisms. For this aspect, models of the respiratory and cardiovascular controller, and even more recent works such as the model by , involve mechanisms and dynamics related to the response under aerobic exercise. However, the application of these models in a complex study is limited by their specificity and specialization in only one of the systems involved. Although mathematical models can describe the physiological response under a specific stimulus, their computational simulation using parameters' nominal values constrains their use in populations with the same characteristics and conditions used during their development . Fitting processes allow the personalization of physiological models to a specific subject or population by estimating the parameter values that minimize the difference between predictions and experimental observations . Applying these techniques to physiological models could involve high complexity due to the large number of parameters that need to be identified. In addition, the restricted number of experimental observations could imply multiple solutions, and several parameter values could not have a physiological sense . Different techniques to solve the fitting problem of models with many parameters have been proposed. They all focused on identifying the minimum number of parameters that must be fitted to correctly predict the experimental response. In , a deterministic sensitivity analysis focused on those parameters that are resolvable in the presence of noise, based on the effect of parameter value variations on the interest variables, was described. In a different approach, Ref. validated a subset selection method that focused on finding the well-conditioned independent parameters for reliable identification using experimental measurements. Refs. do not consider the evaluation of different levels of stimulus. In contrast, Ref. proposed a classification technique based on the overall sensitivity of the model regarding parameter variations and considering different stimulus levels . However, this proposal underestimates sensitivity measures by considering the sum of changes in different directions and assuming that all variables contribute equally to the error. Although the subsequent fitting could be designed for a steady state, its sensitivity computation includes time lags that are not consistent. The validation procedure aims to verify whether the model predictions agree with the experimental data for the defined conditions and disturbances. For this purpose, measures that consider the transient and steady-state response features of the analyzed physiological variables are usually implemented. Although there is no consensus on the proper methodology for validating mathematical models of physiological systems, different works coincide with the criteria proposed by . Such criteria allow validating a model when the dynamic of its responses is consistent with the expected behavior and the values in the steady state are accurate. This work aims to propose a fitting and validation strategy for physiological models with many parameters that consider different populations and stimuli. This strategy includes several techniques and approaches to classify, select, and optimize model parameters under steady-state conditions. A model validation methodology is also presented. Some described methods are new proposals or correspond to improvements to previously reported methods. The strategy application in a cardiorespiratory model during dynamic aerobic exercise is presented and described as a case study. This paper is structured as follows. First, the fitting and validation strategies are presented. It describes in detail the procedures for the classification, selection, and optimization of parameters and methodology validation. Second, a case study is presented. It includes a qualitative description of the cardiorespiratory model and the simulation, fitting, and validation. Third, predictions at different levels of aerobic exercise, both with the fitted model and the nominal values, are compared with experimental data obtained from healthy subjects under a cardiopulmonary exercise test . Finally, the proposed strategy and the model performance results are discussed. 2. Materials and Methods 2.1. Fitting and Validation Strategy The strategy proposed in this work consists of applying three main procedures or steps that must be done sequentially: (a) classification and selection of parameters, (b) model fitting, and (c) model validation. The first procedure involves classifying the model parameters according to some predefined roles in the model (gain, threshold, initial conditions, etc.) and selecting the most relevant ones according to different model-fitting approaches. The second one consists of four sequential stages of parameter value identification related to the model fitting regarding the available experimental information, the overall accuracy, the specific prediction of each variable, and the predictions' behavior concerning the evaluated stimulus. The final procedure focuses on validating the fitted model regarding its predictions' accuracy, behavior, and transient and steady-state regimes. Each procedure is presented in Section 2.1.1, Section 2.1.2 and Section 2.1.3, and its application is described according to the case study. Figure 1 shows a schematic summary of the strategy, in which the main procedures and their respective stages are shown. 2.1.1. Classification and Selection of Parameters This procedure aims to highlight and select the parameters that can be considered best-fit candidates. The selection of parameters is justified according to their relationship to available experimental data, role in the model, identifiability, sensitivity to variations, and their relationship to the stimulus evaluated. Initially, it reduces the number of parameters depending on their role in the model and the objective of fitting predictions in steady-state conditions. Subsequently, the resulting parameters are classified and selected according to two reported techniques and established criteria regarding the model fitting approaches. Classification and Selection of Parameters by Role It consists of an initial classification of the model parameters according to their roles. It comprises five parameter classes generally found in structured models of physiological systems. They correspond to (i) time constants, i.e., parameters related to transient response; (ii) conversion parameters, which are constant values related to equivalences among measurement units; (iii) covariates, corresponding to values that allow defining simulation conditions regarding external disturbances, environment conditions, and features of the population to be simulated; (iv) initial values, corresponding to initial conditions of the model variables, usually required as initial states of integrators and whose action mainly affect the temporal characteristics of the responses before reaching the model steady state; and (v) gain and thresholds, that either module or saturate variables related to model mechanisms, i.e., the weighting of the chemoreceptors response to set the parasympathetic and sympathetic activity regarding the regulation of peripheral resistances in cardiovascular control models. The selection of parameters comprises choosing those parameters that mainly define the steady-state behavior of the cardiorespiratory system response and, therefore, can be used to fit the model response in such a condition. The time constant parameters and initial values are discarded, considering that the proposed fitting procedure focuses on the response once the steady state is reached. Conversion parameters do not need fitting because of their nature and meaning. Therefore, only gain and threshold parameters, whose variations have physiological sense, and are correlated with experimental conditions, and covariates will be considered for the subsequent selection procedures and fitting process. Covariates are only used for the standardization of the simulation conditions. Parameter Classification Techniques The proposed strategy involves modifying and implementing two of the most widely implemented parameter classification techniques for fitting physiological models . A detailed description of each is presented below. Subset Selection of Parameters It is a technique based on the classification of model parameters according to how well-conditioned or ill-conditioned they can be identified . Well-conditioned parameters correspond to those that can be reliably estimated from the constrained experimental data, while ill-conditioned ones are those for which there are multiple fitting solutions. In this study, the subset selection of parameters is based on QR Factorization with the Column Pivoting method . It was selected because it has been widely implemented in different physiological models , presented one of the best results regarding cardiorespiratory models among the other methods reported , and considers the difference between model predictions and experimental data as a reference . This technique is based on the solution of optimization problems using gradient techniques. It establishes a ranking of the well-conditioned parameters for identification by analyzing the interdependencies in the Jacobian. This technique is complemented by integrating the different stimulus exercise levels (according to the experimental data) and variations in the parameters previously selected in the appropriate physiological range (around their nominal values). These additions would allow the selection of parameters that are more consistent with the desired fit. According to the above, the Jacobian is calculated according to Equation (1). (1) rkl'(ujl)=rikl(ujl)ujl, where the indexes i, j, and k represent the variable, parameter, and stimulus level to be evaluated, respectively; l is an index that identifies the parameter variation regarding its nominal value. rkl' is the Jacobian for a specific stimulus level and parameter value variation, formed as the matrix of variations of the differences for each variable rikl regarding the change of each parameter for a specific variation level ujl; r corresponds to the difference between each experimental data and the model prediction given each parameter's change for a particular level of variation. The singular value decomposition is calculated for rkl', according to Equation (2). (2) rkl'(ujl)=UjklSjklVjklT, where Ujkl is the matrix of left singular vectors, Sjkl is the diagonal matrix of singular values of rkl'(ujl) in decreasing order, Vjkl is the matrix of the right singular vectors, and T denotes the matrix transpose. Matrix Vjkl must be partitioned, as expressed in Equation (3). (3) Vjkl=[Vjkl,r(j,k,l)Vjkl,W-r(j,k,l)], where W is the total number of parameters analyzed, and r(j,k,l) is a numerical rank that indicates the number of maximally independent columns of rkl'(ujl). r(j,k,l) is equivalent to the number of parameters that can be identified given the model output and can be determined by the selection of the smallest allowed singular value according to the relation expressed in Equation (4) . (4) sjkl,r(j,k,l)sjkl,1=sNjkl,r(j,k,l)>e, where sjkl,r(j,k,l) is the singular value for r(j,k,l), sjkl,1 is the largest singular value, sNjkl,r(j,k,l) is the normalized singular value for r(j,k,l), and e is a tolerance value that allows differentiating the most significant eigenvalues. The parameters associated with the r(j,k,l) highest singular values are found using QR decomposition with column pivoting, according to Equation (5). (5) Vjkl,r(j,k,l)TPjkl=QjklRjkl, where Pjkl is a permutation matrix, Qjkl is an orthogonal matrix and the first r(j,k,l) columns of Rjkl form an upper triangular matrix with diagonal elements in decreasing order. Pjkl is then used to reorder the parameters according to Equation (6). (6) u^jkl=PjklTuI, where uI is an identification vector of the parameters and u^jkl is the vector of the parameters reordered, which is partitioned regarding r(j,k,l), as presented in Equation (7). (7) u^jkl=[u^jkl,r(j,k,l)u^jkl,W-r(j,k,l)], where u^jkl,r(jk,l) is a vector containing the r(j,k,l) estimable parameters and u^jkl,W-r(k,l) are the parameters that would be fixed at nominal values. The standard 2-norm of the normalized singular value for each parameter in each ranking obtained for each parameter variation must be determined to obtain a general ranking independent of the stimulus level, as presented in Equation (8). (8) Zjl=||Zjlk||2=1Kk=1K(Zjkl)2, where Zjl corresponds to the standard 2-norm of the normalized singular value of the parameter j for the variation level l, Zjkl is the normalized singular value of the parameter j for the stimulus level k and the parameter variation level l, and K is the number of stimulus levels. Finally, the result of this technique corresponds to the presented in Equation (9). (9) Zj=||Zjl||2=1Ll=1L(Zjl)2, where Zj is the standard 2-norm of Zjl of the parameter j, and L is the total number of parameter variations. This technique is usually implemented with sensitivity analysis techniques because their approaches complement each other regarding the problem solution. QR decomposition identifies the parameters to which the model is sensitive as a group, while sensitivity analysis finds the parameters to which the model is individually sensitive . Sensitivity Analysis Sensitivity analysis involves the integration and improvement of the techniques introduced by . It comprises a deterministic analysis that evaluates the global model and variables' sensitivity to variations in model parameters and stimulus levels. It also involves an experimental data dependency term that weighs such sensitivity by the error reached by the model at each parameter variation and stimulus level. The model variable's sensitivity regarding each parameter variation is based on the standard local differential equation described by and used by to calculate time-dependent sensitivities in cardiovascular and respiratory models. Equation (10) shows the computation of this sensitivity. (10) sij(t,u)|u=un=Yi(t,uj)ujujYi(t,u)|u=un;uj,Yi(t,u)0 , where sij represents the relative sensitivity of the variable Yi to parameter uj, which is dimensionless by the ratio between the parameter uj and the variable Yi values at nominal conditions (no parameter variation). n refers to the parameter's nominal value. This work proposes modifying the measurement of relative sensitivity to make it independent of the time and dependent on the stimulus. Therefore, an approach based on steady-state conditions at different stimulus levels is used. Relative sensitivity is evaluated by varying each parameter over a range around its nominal value, while the others are kept at their nominal values. Equation (11) shows the proposed relative sensitivity measure. Time independence avoids significant differences between sensitivity measures due to time lags, considering that the fitting model procedure is focused on minimizing the steady-state differences between the experimental measurements and the model predictions. The evaluation of the stimulus is included by considering the influence of its variations on sensitivity measures. (11) sijk=|Yik(uj)(uj)||ujnYik (un)|, where, i, j, and k are indexes that refer to the analyzed variable, parameter, and stimulus level. sijk is a scalar value of the relative sensitivity; Y is the variable value in the steady state; u is the parameter value; n refers to the parameter's nominal value. Therefore, Equation (11) evaluates changes in the variable Yi regarding variations in the parameter uj at the stimulus level k (first quotient), which is dimensionless by the ratio between the parameter's nominal values ujn and the variable Yi at the stimulus level k (second quotient). Deriving sensitivity equations can be tedious and error-prone for large systems, mainly when they involve nonlinear features, such as those analyzed in this case study. Alternatively, Equation (11) can be solved using a computational approach consisting of a simple finite difference method. A numerical approximation of the derivatives, which also considers the variation of the parameter relative to its nominal value, is expressed in Equation (12). (12) sijlk|Yik(ujn+hlujn)-Yik(un)(ujn+hlujn)-(ujn)||ujnYik (un)|, where sijkl is a scalar value of the sensitivity for the variable Yi regarding the variation hl in the parameter uj at the stimulus level k. h is the vector of change proportions of the parameter regarding its nominal value. This expression can be reduced and organized as expressed in Equation (13). (13) sijlk|Yik((hl+1)ujn)-Yik(un)Yik (un)||1hl|=DYijlk|1hl|, where the first quotient of the equation, also identified as DYijkl, is a dimensionless term representing the rate of change of the variable Yi when a percentual variation hl in the parameter uj is applied at the stimulus level k. The second quotient is a dimensionless term representing a weighting factor, giving heavier importance to slight parameter variations. Therefore, the sensitivity sijlk corresponds to a dimensionless scalar value that measures the weighted relative variations of the analyzed variables according to four degrees of freedom. Standard 2-norm is applied to sijlk to obtain a measure of the relative sensitivity independent of the parameter variations, as expressed in Equation (14). As a result, a positive dimensionless scalar value related to the relative sensitivity's mean trend is obtained for all parameters. (14) sijk=||sijlk||2=1Ll=1L(DYijlk|1hl|)2, where L is the total number of parameter variations or elements of the vector h. The stimulus level independency relative sensitivity is calculated according to Equation (15). (15) sij=||sP,ijkmax(sik)||2=1Kk=1K(Pik*sijkmax(sik))2, where K is the total number of stimulus levels; max(sik) is the maximum relative sensitivity obtaining for the variable i at the stimulus level k considering all parameters; sP,ijk is the weighted relative sensitivity; and Pik is a weighting factor representing the variable error at the stimulus level k. Sij corresponds to the standard 2-norm of sijk normalized by its maximum value at each stimulus level k and weighted by Pik. Normalization of sijk allows comparing the sensitivity measures between different stimulus levels, whereas the inclusion of the weighting factor Pik prioritizes the sensitivity obtained at the stimulus levels for which the variable's error is more significant (i.e., errors obtained from predictions resulting from using parameter's nominal values). As a result, a ranking of the model parameters concerning their variation impact for each variable is obtained. Pik is calculated according to Equation (16). (16) Pik=EikK*EiT, where Eik is the error of the variable Yi at the stimulus level k, and EiT is the total error for the variable Yi (considering all stimulus levels). Equations (17) and (18) are proposed to calculate the mentioned errors. (17) Eik=|Yexp,ik-Yik(un)Yexp,ik|, (18) EiT=1Kk=1KEik, where Yexp,ik represent the experimental value of the variable Yi at the stimulus level k. The model's total sensitivity to each parameter is calculated according to Equation (19). (19) sj=||sP,ijmax(si)||2=1Ii=1I(Pi*sijmax(si))2, where I is the total number of variables evaluated; max(si) is the maximum value of sensitivity among all the parameters for the variable Yi; sP,ij is the weighted sensitivity of each parameter uj for the variable Yi; Pi is the weighting factor related to the variable and it is calculated according to the Equation (20). (20) Pi=EiI*ET, where Ei is the error of the variable i, and ET is the total model error. Equations (21) and (22) are proposed to calculate the mentioned errors. (21) Ei=1Kk=1K(Yexp,ik-Yik(un)Yexp,ik)2, (22) ET=1Ik=1KEi, Sj corresponds to the standard 2-norm of Sij normalized by the maximum sensitivity obtained in each variable and weighted by Pi. Normalization of sij allows comparing the sensitivity measures of the parameters among different variables, whereas Pi prioritizes the sensitivities of the parameters for which the variable's error is more significant. As a result, a ranking of the model parameters representing the effect of their variation on the model's whole output is obtained. Parameter Selection Criteria This procedure focuses on applying the selection criteria of the classified parameters concerning four different fitting approaches. Selection for the Standardization of Simulation Conditions It consists of selecting the model's parameters, which can be determined from the available experimental data. It involves those related to the subjects' characteristics, the stimulus evaluated, or the environmental conditions. They can be established by direct equivalence or by applying previously validated equations. Selection for the Base Fitting Approach It comprises selecting the set of parameters for which the model has the highest global sensitivity. This selection aims to reduce the model's total prediction error by considering the parameter's overall effect on model behavior. They correspond to the union of the set of parameters obtained in subset selection (i.e., those parameters that have been identified as well-conditioned to be adjusted, Equation (9)) and total sensitivity techniques (i.e., those parameters whose variations generate significant changes in the model output, Equation (19)). In this work, this selection is defined according to the following criteria. Parameters from the subset selection ranking are chosen according to the criterion defined in Equation (4), considering e as the square root of the termination tolerance on the function evaluation defined for the fitting procedure (Table 1). Parameters from the total sensitivity ranking are chosen in descending order until at least one is obtained for each system and controller of the model, including those already selected in the previous step. Selection for a Specific Fitting Approach It corresponds to the set of parameters for each variable's highest sensitivity at the individual level. Its optimization aims to modify each variable's predictability to bring it closer to the respective experimental data without significantly affecting the other predictions. It is based on relative sensitivity measures independent of the stimulus level (Equation (15)). Based on the following criteria, only one parameter is selected by each ranking obtained for the evaluated physiological variables. Remove the parameters selected for the base fitting approach from each variable ranking. Remove the parameters of systems and controllers that are not directly related to regulating the variable of interest. Select only those parameters whose sensitivity is high for the variable of interest and low for the remaining ones. Parameters with high sensitivity for other variables could be selected if those variables belong to or are dependent on the same system or controller of the variable of interest. Selection for the Stimulus-Related Fitting Approach This corresponds to the parameter selection criteria that relate the stimulus to the regulation mechanisms addressed in the model under study. Their selection is based on the parameters' role concerning the mechanisms mainly associated with the stimulus, highlighting the weighting factors or gains that link them to regulatory activities. Eight mechanisms directly related to the exercise stimulus were evaluated in this work. Only one parameter per mechanism was selected. 2.1.2. Model Fitting Fitting a parametric model involves solving an optimization problem in which the values of the set of parameters minimizing the differences between experimental data and model predictions are identified . The identification of the parameter values in this strategy results in applying an optimization algorithm in three stages that must be carried out sequentially: first, a base optimization; second, a specific optimization; and third, a stimulus-related optimization. Each stage focuses on the value identification of a specific and reduced number of parameters. It is proposed to apply the following procedures before the mentioned optimization stages to obtain correct, fast, and physiological meaning results: the standardization of simulation conditions, the selection and parameterization of the optimization algorithm, the definition of the parameter evaluation ranges, and the choice of a metric to evaluate the model's goodness of fit . Each procedure and optimization stage is detailed below. Standardization of Simulation Conditions Its objective is to bring the simulation conditions close to the data used as a fitting reference. To do this, it proposes modifying some model parameters using the values obtained from the experimental data. It replaces the selected parameters' values with the direct equivalences or results of applying previously validated equations. Its implementation has been previously presented in works on the design and fitting of physiological models, e.g., for the estimation of blood volumes and mechanical characteristics of cardiovascular and respiratory systems . It reduces the number of fitting candidates and, therefore, the complexity of the optimization problem and the possibility of multiple solutions. Optimization Algorithm Different optimization algorithms reported could be applied for the fitting of physiological models. They are divided into those that use deterministic or stochastic methods. Their correct selection depends on the model's specific characteristics under study and the validation requirements . In this paper, an evolutionary strategy with a covariance matrix and adaptation (CMA-ES) was selected. It is a stochastic global optimization algorithm based on adaptive and evolutionary strategies . This algorithm was selected considering the best convergence speed, precision, and accuracy results reported in a comparative study concerning a physiological model similar to the case study . Parameterization of the Optimization Algorithm This corresponds to the parameter assignment of the selected optimization algorithm. It is generally related to the number of evaluations, iterations, and error tolerances. These parameters are specific to the algorithm and must be defined based on the fitting's strictness and computational cost. The parameter values used for implementing the CMA-ES algorithm are presented in Table 1. These values are similar to those reported by , considering the similarity regarding the case study model and that the fitting's strictness is analogous to the desired one. Evaluation Ranges of the Parameters The optimization algorithms seek to identify model parameters through strategic variations of their values. The variation ranges should depend on the parameter's specific function concerning the associated model mechanism since not all possible values provide a consistent result. For physiological models, in addition to obtaining predictions close to experimental data, it is desirable to find optimized values that reflect consistent physiological conditions or characteristics, further constraining the optimization problem . According to the above, this work proposes the following criteria to determine the evaluation range for each selected parameter:Determine an initial variation range for each parameter in proportion to its nominal value. The range bounds depend on the expected closeness between the optimized and nominal values. Such closeness can be estimated overall by considering the parameter's relationship with the condition for which its nominal value was defined and the nature of the experimental dataset for which it is intended to optimize, e.g., variation of respiratory mechanics parameters during rest and exercise . The variation range is recommended to contain the values evaluated in the parameter selection techniques. Evaluate the values' constraints from the equations describing the model mechanisms associated with each parameter and redefine the previously established bounds. Redefine the variation range's bounds if the reported information relates the parameter to the experimental conditions. Since not all model parameters are directly related to physiological measures, i.e., those from empirical equations that have been fitted to experimental data, evaluating their variations considering different works in which it has been used is necessary. Performance Evaluation It uses a metric that compares the model's predictions with the experimental data. The optimization algorithm uses this measure as a criterion function to identify the goodness of fit of the model predictions for each parameter's optimization. Different metric options have been applied in several works related to physiological models. However, the most commonly used is based on the root mean square error (RMSE) , and its application is justified because it is considered more suitable for revealing differences in model performance . This paper modified the RMSE metric to consider all analyzed variables at different stimulus levels, as expressed in Equation (23). (23) CF=1Ii=1I1Kk=1K(yexpi,k-ysimi,kyexpi,k)2 , where CF denotes the cost function for the optimization algorithm; yexp and ysim represent the variable's experimental and simulated values; I and K indicate the number of variables and stimuli levels; the subscripts i and k denote each variable and stimulus level. The error between predictions and experimental data is initially computed by obtaining a dimensionless measurement of each variable's difference at each stimulus level. Subsequently, the standard 2-norm is calculated regarding stimulus levels to measure each variable's mean trend. Finally, the global error is calculated as the mean value of every variable's errors. Fitting Stages This work proposes fitting the model using three approaches. They involve those presented in the parameter selection procedure's subsections and represent stages sequentially applied to obtain a complete fit of the case study model. In one stage, the previously fitted parameters remained fixed, and only those selected for the current one are optimized. The first stage corresponds to a base fitting approach. It optimizes the parameters with the highest total sensitivity, whose variations have the most significant overall impact on the controllers and system outputs. The second stage corresponds to a specific fitting approach. Each variable comprises the parameters' optimization with the highest relative sensitivity and the least side effect for the remaining variables. This is focused on minimizing the prediction error of each variable individually. The third stage involves a model mechanisms' fitting approach. It optimizes the mechanisms' parameters, mainly associated with the evaluated stimulus, to improve the predictions' behavior. 2.1.3. Validation Methodology This procedure assesses the model predictions under conditions and disturbances that match the experimental data. Although there is no consensus on a defined validation methodology for mathematical models of physiological systems, most of the evaluations described in related works generally coincide with the criteria proposed in . Therefore, model simulation results are evaluated using directional, accurate, and consistent approaches. Different metrics can be used to evaluate the performance of a model in steady-state conditions, highlighting mean absolute error (MAE) and RMSE as the most common ones. Their selection must be related to the critical interpretation of the results and the statistical distribution of errors. However, there is no consensus on which of these is most appropriate . In this work, the measure presented in Equation (24) was used to calculate the model's prediction error of PE. (24) PE=1Nv=1N(Medians,l(|yexps,v,l-ysims,v,lyexps,v,l|))x100%, where yexp and ysim represent the experimental and predicted values; N indicates the number of variables; and s, v, and l are used to distinguish the subject, variable, and stimulus level. The PE measurement was selected because (a) it corresponds to the PE measure used in the structural evaluation work of the case study model , (b) it allows straightforward interpretation of differences as proportions of experimental data, and (c) it considers median values due to the non-normal distribution of the experimental data. Regarding dynamic transitions, changes in magnitude and response speed are usually implemented to evaluate predictions under stimulus changes . Due to the above, and considering the measures adopted in previous evaluation and characterization works under the stimulus of exercise , this study considers evaluating each variable's percentage change regarding its rest conditions and the settling time of the obtained predictions. 2.2. Case Study 2.2.1. Cardiorespiratory Model The cardiorespiratory model follows a multi-compartmental structure comprised of subsystems for cardiovascular circulation, respiratory mechanics and gas exchange processes, and controllers that allow cardiac and respiratory self-regulation. It results from adapting different published models to achieve a model that can correctly mimic the main cardiorespiratory variables of a healthy adult under incremental aerobic exercise. Its development, nominal parameter values, and complete description of mechanisms are not reported here for brevity. The reader can refer to the previous paper for full details . The cardiovascular system includes systemic circulation, pulmonary circulation, and the heart. Systemic circulation is divided into large arteries, peripheral and venous vessels, and the vena cava. Pulmonary circulation involves the pulmonary arteries, peripheral vessels, and veins. The heart differentiates elements of the left and right compartments, where the atriums are modeled as passive compliance and the ventricles' activity as a variable-elastance model. Changes in the pressures, resistances, blood flows, and blood volumes of the different vascular beds are regulated in response to cardiovascular regulation and exercise stimulus. The cardiovascular control response is initially mediated by the activity of afferent pathways (baroreceptors, lung stretch receptors, and peripheral chemoreceptors), the blood flow local control, the central nervous system to acute ischemic conditions, the central respiratory neuromuscular drive, and the mechanism of the central command (evaluated as the metabolic regulation response). The efferent pathways modulate their actions as sympathetic and parasympathetic activities. Subsequently, these results, together with the central command response (I), allow the effector mechanisms to regulate heart rate (HR), peripheral resistances (Rjp), unstressed venous volumes (Vu,jv), and maximum end-systolic elastance of the ventricles (Emax,jv). The respiratory system comprises respiratory mechanics, gas exchange, and a respiratory controller. Respiratory mechanics are divided into upper airway mechanics and pulmonary mechanics. Signals such as respiratory muscle pressure (Pmusc(t)), pleural pressure (Ppl), alveolar pressure, ventilatory flow (V ) and tidal volume (VT) are generated in the pulmonary mechanics' compartment according to variables of the upper airway mechanics and the parameters regulated by the respiratory controller (Nd). The upper airway compartment describes the dynamics of air from the mouth to the lungs. It allows calculating the conductance of the upper airway (Gaw), necessary for determining V and VT according to the air movement equation. The gas exchange system describes the exchange, mixing, and transport of O2 and CO2. The gas exchange and mixing compartment described the alveolar gas partial pressures (PACO2 and PAO2), the arterial gas partial pressures (PaCO2 and PaO2) and the gas concentrations in the arterial blood (CaCO2 and CaO2). They are determined by the blood flow signals, blood flow of each peripheral compartment (Qjp) and blood flow from the pulmonary peripheral compartment (Qpp), respiratory mechanics waveforms (V and VT) and environmental conditions such as the atmospheric pressure (Patm) and inspired fractions of dry gas (FiCO2 and FiO2). The gas transport compartment describes the gas concentrations in the venous blood (CvCO2 and CvO2), the venous gas partial pressures (PvCO2 and PvO2), the brain gas partial pressure (PbCO2) and the tissues gas metabolic ratios (MRTCO2 and MRTO2). It also involves a metabolically related neural drive component to ventilation (MRV), from which information related to metabolic changes during exercise for respiratory regulation processes is provided. The respiratory controller performs regulation processes based on the chemical and mechanical optimization approaches described by a ventilatory controller and a respiratory pattern optimizer. The ventilatory controller estimates the ventilatory demand at the end of each respiratory cycle in response to the average activity of the central and peripheral chemoreceptors for CO2 and O2, the neural drive ventilation related to metabolism (MRV) and the basal alveolar ventilation. The respiratory pattern optimizer estimates the variables related to the global breathing pattern, specifically the breathing frequency (BF) and the inspiratory time (TI), and the parameters defining the respiratory mechanics' waveforms according to the ventilatory demand and the minimization of the mechanical work of breathing. The model has different parameters that can be configured as inputs to simulate a healthy human subject's response with specific characteristics under several stimuli, e.g., at different levels of aerobic exercise and environmental conditions. Carbon dioxide output (V CO2) and oxygen uptake (V O2) can be used to represent different aerobic exercise levels due to their direct relationship with the body tissues' metabolic rates involved in the gas exchange system. The fractions of inspired CO2 (FiCO2) and O2 (FiO2) define environmental gas concentrations, helping to simulate ventilatory stimuli, such as hypoxia and hypercapnia. Atmospheric pressure (Patm) provides information about the environment reference pressure, which helps simulate different altitude conditions. The pressure at the airway opening (Pao) is assumed to be equal to Patm for spontaneous breathing conditions, but its value can be varied to simulate different ventilatory therapies. The total time of the muscular contraction (Tc) and the period of the muscular contraction-relaxation cycle (Tim) are parameters related to muscle contraction times involved in systemic circulatory activity and characterize different physical activity protocols. Other parameters can also be used to characterize the population or the subject whose cardiorespiratory system tries to be simulated, highlighting the anaerobic threshold (AT) and basal respiratory tidal volume (VTn) for the exercise stimulus. 2.2.2. Experimental Data The experimental data correspond to those recorded to build and evaluate the cardiorespiratory model. The records comprise signals of V O2, V CO2, V E, TI, VT, BF, HR, PAO2 and PACO2; systolic (PS), diastolic (PD) and mean (PM) arterial blood pressures; and environment and subjects' features such as Patm, FiCO2, FiO2, AT and VTn. The procedures and characteristics are reported in a previous paper 2.2.3. Simulation, Fitting, and Validation The simulations performed for fitting and validation processes correspond to a healthy human under rest and aerobic exercise. The parameters' nominal values correspond to those reported in the model-building work . The experimental values of V O2 and V CO2 corresponded to the simulation inputs of the model to establish the stimulus levels. This approach has been used to simulate aerobic exercise in physiological models . It is justified because the physiological response under this stimulus is directly related to metabolic rates of O2 consumption and CO2 production. In addition, the model does not consider workload as a model input. The simulation time was set at 3000 s for each exercise level to guarantee steady-state reach in all variables under study . Steady-state values were calculated as the signal average at the last minute of each simulated stimulus level. The experimental data were restricted to AT because the model is constrained to aerobic exercise. The cardiorespiratory variables evaluated for the selection and fitting procedures correspond to V E, TI, BF, HR, PS, PD, PM, PAO2 and PACO2. These variables were selected because they are the available experimental measurements most commonly reported in cardiopulmonary exercise tests. They also provide information about the mechanisms and controllers of the involved systems . All the subjects' measurement trends were used to calculate the PE and CF in the parameter selection and fitting procedures. Regarding the validation process, the same variables were evaluated together with VT. Although VT is part of the available records, it was not considered for the selection and fitting processes due to its direct relationship with V E and BF (VT=V E/BF), which are output variables of the model's respiratory controller . Model simulations and data processing were carried out in SIMULINK/MATLAB(r). The computational characteristics for the simulation were the same as those reported in the model building , corresponding to the numerical solver ODE23 with a variable step size lower than 0.01 s. Simulations were run once because all model equations are determinists. The specific implementation characteristics for each procedure are described below. Classification and Selection of Parameters Steady-state predictions under different stimulus levels and parameter values were used for subset selection and sensitivity analysis techniques. The stimulus levels corresponding to rest, intermediate exercise, and anaerobic threshold were sequentially evaluated as steps of the same duration to cover the entire range of aerobic exercise. The steady-state model predictions corresponded to each variable's mean values at the last minute of each simulated stimulus level. Five variations in the parameters resulting from the selection by role procedure were applied. The variations were uniformly distributed in a range of +-5% regarding the nominal values, since a close variation is expected, considering that the experimental data also correspond to healthy adult subjects. Experimental data average measurements of all registered subjects were used for each variable in the three stimulus levels. Model Fitting This corresponds to the adjustment of the model parameters following the approaches presented in Section 2.1.2. The boundaries for the searching space are defined around the nominal values of the model parameters. The evaluated model predictions corresponded to the steady-state simulation results under variations of V O2 and V CO2. These variations consisted of the same three consecutive, equidistant, and incremental steps previously described for classifying and selecting parameters. The experimental data for comparison were also the same, and the CF implemented corresponds to Equation (23). Validation Methodology Steady-State Simulation PE values obtained from the steady-state model response to the exercise stimulus were used to evaluate the model's performance (Equation (24)). The model predictions were obtained under simulated variations of V O2 and V CO2 as eight incremental, successive, and equidistant steps from rest to the mean experimental value of AT. Regarding the experimental data, the model predictions were evaluated by considering the differences concerning each subject. Transient Simulation The experimental data dynamic responses of the first exercise phase load step were compared with the simulation results under equivalent variations of V O2 and V CO2. All variables' simulation results are shown as proportional changes concerning their initial value to evaluate the change in magnitude due to the stimulus without considering PE. The settling time was calculated as the time elapsed from the stimulus onset to the time for which the model response reached the tolerance band of +-5% of its final value. Systemic arterial pressures were not included here because transient-state experimental values were unavailable. 3. Results 3.1. Classification and Selection of Parameters Descriptions of the model parameters are presented in this section in order to elucidate their selection according to the different fitting approaches. The reader can see the model equations in the Supplementary Material for detail. 3.1.1. Selection by Role The cardiorespiratory model has 316 parameters (78 of the cardiovascular system, 155 of the cardiovascular controller, 14 of the respiratory mechanics, 13 of the respiratory controller, and 56 of the gas exchange system) distributed according to the proposed classification presented in Table 2. Only the parameters with the role of covariates, gain, and thresholds were considered for the model fitting. Among gains and thresholds, the maximal abdominal pressure parameter (Pabdmax,n) was not considered for the subsequent procedure of parameter selection. It should not be modified for the simulation of healthy adult subjects. 3.1.2. Standardization of Simulation Conditions The parameters used for the standardization of simulation conditions corresponded to FiO2, FiCO2, Patm, basal respiratory tidal volume (VTn), anaerobic threshold (AT), total blood volume (Vtot) and unstressed blood volumes. FiO2, FiCO2, Patm correspond to the recorded environmental conditions and were assigned by direct equivalence with the reported information. VTn, AT, Vtot, and the unstressed blood volumes are related to the subjects' specific characteristics and were estimated using equations applied to the experimental data. The results are reported in the model-building work . According to the above, only 216 parameters were selected for the subsequent parameter selection procedures, reducing the number of parameters considered for the fitting procedures by 31.6%. 3.1.3. Parameters Selected for the Base Fitting Approach Figure 2a shows the first ten parameters for subset selection, and Figure 2b shows the total sensitivity analysis ranking, in descending order from left to right. The parameters selected for the base fitting approach are highlighted in each ranking. Eight base fitting parameters were selected from the rankings, three from the subset selection technique under consideration of the tolerance range of 1x10-12 (Table 1 and Equation (4)), and five from the total sensitivity analysis corresponding to those whose sensitivity was greater than 46% of the maximum sensitivity found (Section 2.1.1). Regarding the subset-selection results, it is highlighted that there is a single significant difference between the parameter in the first position and the others presented, evidencing the difficulty of identifying a single optimal solution for more than one parameter using gradient-based techniques . Regarding the total sensitivity analysis, all the selected parameters directly affect the model's controllers, which are the ones that have the most significant influence on the model's base behavior, as expected. This approach evidences the impact of the modifications on selection methods, mainly those related to the error and stimulus-level evaluation. In this sense, the distribution of the parameters regarding the systems and controllers (5 parameters of the respiratory controller, 2 of the cardiovascular system and controller, and 1 of the gas exchange system) is associated with the error contribution of the related variables . After applying the selection criteria, the number of parameters considered for this fitting procedure was reduced by 97.4%. The selected parameters, the corresponding model equations and mechanisms, and the possible variation range information are presented below. KRlv is a parameter that describes the dependence of the left ventricle resistance (Rlv) on the isometric pressure (Pmax,lv) in the cardiovascular system . Its nominal value results from scaling data extracted from animal experiments to reflect changes in ventricle volume in human beings. It has been used in different works without presenting variations , even in studies focusing on personalized cardiovascular models . Considering the simulation results under nominal conditions of Rlv and Pmax,lv, and applying the rescaling approach of vascular resistance implemented in concerning the mean total blood volume from experimental data, variations close to 6% of the nominal value could be expected. MRBCO2 denotes the metabolic production rate for CO2 in the brain tissue and allows us to relate PaCO2 with PvbCO2, the CO2 brain venous blood pressure. Its reported nominal value is 0.0009 L/s STPD and has not been fitted in the different validation works in which the associated model has been used . Works related to other validated models report values for parameters with the same physiological sense ranging from 0.0007 to 0.00104 L/s STPD . Therefore, fitted values between -22.2% and 15.6% of the nominal value could be expected. T0 is a cardiovascular controller parameter representing the heart period (HP) in the absence of cardiac innervation . It is the offset term in the equation that relates to the changes in HP induced by sympathetic and parasympathetic stimulation (DTs and DTv, respectively). Its reported nominal value results from a fitting process to mimic animal experimental data . It has been used without any modification in different publications related to cardiovascular control models . Considering this value as a proportion of the reported HP at rest (0.833 s), variations close to -7% of the nominal value could be expected whether the median experimental value of HP at rest (0.775 s) is considered a reference. Pmax is a parameter of the respiratory controller that denotes the maximum inspiratory pressure . It relates to the inspiratory muscles' capacity to minimize the work of breathing. In , a nominal value of 150 cmH2O is proposed, and variations of around +-66% of this value are evaluated. Subsequent work has used a value of 50 cmH2O on fitting and validating such a model with healthy subjects . Following the above, although the optimization procedure can identify a value near the nominal value, variations higher than 100% could be expected. Ers is a parameter that denotes the overall elastance of the ventilatory system. It is used in the model's respiratory controller and lung mechanics to represent the motion equation of the respiratory system. Its nominal value is 21.9 cmH2O/l and agrees with that reported in for healthy adult subjects. However, other authors report lower values of 10, 8.55, and 8.52 cmH2O/l. According to the above, variations of around -66% of the nominal value could be expected . KpO2, KcCO2, and Kbg are the parameters of the respiratory controller associated with the control of ventilation. KpO2 and KcCO2 correspond to constant weighting factors related to the peripheral chemoreceptors for O2 and the central chemoreceptors for CO2 contributions, respectively. Kbg is an offset term that relates to the blood gas dissociation constant for the controller . These parameters correspond to fitted values to mimic the change in alveolar ventilation from rest. They have not been modified in studies in which experimental data on healthy adult subjects are used . 3.1.4. Parameters Selected for the Specific Fitting Approach Figure 3 shows each variable's relative sensitivity ranking results after removing the parameters selected for the base fitting approach. They are presented in descending order from left to right. The parameters selected for the specific fitting approach are highlighted in the ranking of each variable. The results highlighted that not all the parameters selected for each variable corresponded to the first ranking positions, which shows the significant influence of the regulation results between the model's different systems and controllers. This fact was presented mainly for variables not directly related to the controllers (PM, PD, and PACO2), evidencing that the parameters of the main regulatory mechanisms have the most significant influence on the model. The parameter selected for PACO2, corresponding to VLCO2, is not even among the positions presented in the respective ranking, showing the high sensitivity of the variable to the results of other systems and controllers. The number of parameters considered for this fitting procedure was reduced by 97.2%. The selected parameters, the related model equations and mechanisms, and the information reported regarding their possible variation ranges are presented below. GT,v corresponds to the weighting factor that relates parasympathetic activity with heart rate regulation in the cardiovascular controller . This parameter was initially adjusted to mimic the humans' cardiac period's response in . Its nominal value is not related to direct physiological measurement and has not been modified in subsequent applications of the model . Rsa is a parameter of the cardiovascular system that represents systemic arterial hydraulic resistance and relates Psa to systemic arterial blood flow (Qsa). Its nominal value was initially computed according to experimental cardiac output and cardiovascular pressure measurements . It has been modified in different cardiovascular system versions due to the inclusion of new vascular beds . The latest reported nominal value corresponds to that defined for the case study model . Although it has not been modified in other validation works , a rescaling approach was proposed in for personalized fitting based on experimental data on total blood volume. Following the above, using the average experimental value of total blood volume reported in as a reference, a variation close to 5.42% of the nominal value could be expected. KE,lv describes the left ventricle's function at the end of the diastole based on the pressure-volume relationship . Its nominal value was initially identified to fit the exponential relationship proposed in to healthy humans' experimental measurements. According to the experimental measurements reported in , variations of less than -35.7% and greater than 7.1% of the nominal value could be associated with symptoms of cardiac pathologies. Phmax is a cardiovascular controller parameter associated with the vasodilation of the peripheral resistance of the active muscles (Ramp) during exercise . It corresponds to the upper saturation bound of a sigmoid function used to describe the vasodilator effect independent of tissue hypoxia during exercise . The parameter's nominal value is not related to a direct physiological measure but results from optimization procedures to imitate experimental data. l1 is a parameter related to the breathing pattern optimizer and corresponds to a weighting factor that relates the mechanical work of the inspiratory phase (W I) with the average square magnitude of volume acceleration . Its value was fitted in to the experimental data of healthy subjects. Considering their results implies possible variations in the nominal value of around -43%. V0dead is a parameter of the respiratory controller related to the regulation of V E . This corresponds to the offset term of the empirical equation used in to calculate the dead space volume as a function of alveolar ventilation. It has not been modified in subsequent validation studies on healthy subjects . n is a parameter related to the breathing pattern optimizer, used as a power index of efficiency factors that relate W I with Pmusc(t) . Following the values fitted in the validation work by , a variation ranging from -9.17% to 81.7% of the nominal value could be expected. C1 is a parameter related to the dissociation of oxygen in the blood and denotes the maximum concentration of hemoglobin-bound oxygen . Its nominal value was taken from and calculated from predefined pressure, temperature, and the amount of hemoglobin conditions. Although this value has not been modified in subsequent studies of the same blood gas dissociation model, other values are reported for this physiological measure , allowing a variation of approximately -3.6% of the nominal value. VLCO2 is a parameter that relates PACO2 with the blood concentrations of CO2 and Qpp . It denotes the lungs' storage volume for CO2, and can be understood as a fraction of the functional alveolar volume of the lung . Therefore, using the alveolar volume values reported in , a study based on subjects under exercise as a reference, variations around 50% of the nominal value could be expected. 3.1.5. Stimulus-Related Fitting Parameters For this approach, the selected parameters relate to each of the eight mechanisms reported for the case study model . Only one parameter for each mechanism's regulatory activity, which was not selected in the previous fitting approaches, was selected. The mechanisms evaluated were: the central command action (I-EP) and the central respiratory neuromuscular drive (NT) on regulation control activities; the central vasodilatory action on active muscles due to central command (I-Ramp); the independent description of venous vascular beds from active muscles (V-Ramv); the muscle (MP) and the respiratory (RP) pumps; the neural driving ventilation related to metabolism (MRV); and the respiratory control action based on mechanical work of breathing minimizing (minWOB). I-EP, I-Ramp, V-Ramv, MP and RP are mechanisms that relate I (exercise intensity) to the regulatory activities of the cardiovascular controller and system. Their parameters were defined and optimized from human and animal experimental data . No parameter was selected concerning blood flow signals in the gas exchange system because it is not considered a mechanism that explicitly relates to the exercise stimulus. The selected parameters, their corresponding mechanisms, and regulatory activity are presented in Table 3. The number of parameters considered for this fitting procedure was reduced by 95.3% with respect to the total after applying the selection criteria. The related mechanisms and the information reported on the possible variation range of each selected parameter are presented below. gsh,max, gsp,max, gsv,max and gv,max are the upper saturation values of sigmoid functions that relate I to sympathetic and vagal efferent activity. In I-Ramp, gM is a static gain that relates I to the effect of tissue hypoxia concerning the regulation of the active skeletal muscle's peripheral resistance (Ramp). In V-Ramv, kr,am is a constant parameter that characterizes the inversely proportional behavior of the active muscles' venous vascular beds (Ramv) concerning the total volume of blood it contains (VTamv) during exercise. In MP, Aim is a parameter that denotes the peak value of Pim, which affects the vascular venous pressure during exercise (Pamv). Finally, in RP, gabd and gthor are constant gain factors that relate changes in the tidal volume with the maximum and minimum values of Pabd and Pthor, respectively. Wt,sh, Wt,sp, Wt,sv and Wt,v are weighting factors that relate Nt to sympathetic and parasympathetic efferent activity. Their values were optimized in to ensure that the dynamic behavior of the model under various conditions remains realistic, and they have been used in later works without any modification . KcMRV is a parameter of the respiratory controller associated with ventilation. It corresponds to a constant gain that relates MRV to V A. It was initially defined as equal to 1 in under the consideration of a direct action of MRV. However, in the case study model, it was defined as a constant parameter to consider a weighting factor for the related mechanism. l2 is a factor that weighs the expiratory mechanical work (W E) in the total mechanical work of breathing (W T). According to , a variation ranging between -28.4% and 170% of its nominal value could be considered. 3.2. Model Fitting A general evaluation range of +-30% regarding the nominal value was defined for those selected parameters whose variation could not be established or constrained to reported values in the literature. For that, the following considerations were taken into account: (a) it is suitable for the constrictions of each associated mechanism of the model, and (b) it agrees with the expected closeness of the results for the nominal values. It was also considered that these parameter values are related to subjects with physiological characteristics similar to the subject's experimental data (healthy adult males). The evaluation ranges for the other parameters are presented in Table 4, following what was previously described in the selection parameter results. It should be noted that most of the selected parameters were adapted to the defined general evaluation range; the remaining ones were mainly related to the increase of either lower or upper bounds. Only KE,lv required a decrease in the range due to its relationship with cardiovascular diseases. Table 5 compares the nominal parameter values against the best optimization results for each fitting stage. Most optimizations were between +-15% of the nominal value, confirming the expected closeness, considering that the nominal values and the experimental data are related to subjects with similar physiological characteristics. The most significant changes that occurred in the second and third fitting stages related to the specific and stimulus-related fitting approaches. The following main modifications were obtained regarding the specific fitting approach: (a) a decreased effect of volume on left ventricular pressure due to the decrease in KE,lv; (b) an increase in VD, and therefore an increase in V E not related to V A, due to the increase in V0dead; (c) a decrease in the PACO2 due to the decrease in VLCO2. For the Stimulus-related fitting approach, the following results were obtained: (a) a decrease of the sympathetic activity related to the regulation of peripheral resistances and heart elastances and an increase for the sympathetic activity for venous volumes due to the modifications in gsh,max, gsp,max and gsv,max; (b) a decrease in the tissues' hypoxic effect on the vasodilation action of Ramp due to the decrease in gM; (c) an increase in the muscular and respiratory pump activity on venous return due to increased Aim and gabd; (d) a decreased weighting of W E regarding W T due to decreased l2. The results obtained from NT are mainly related to increased sympathetic activity regarding heart elastances, but the I-EP results overshadowed this effect. 3.3. Validation 3.3.1. Steady-State Response Figure 4 presents the steady-state model predictions under nominal conditions and at each fitting stage. Eight equidistant step inputs of V CO2, from 0.3 L/min to 1.0 L/min were used. The steady-state results confirm the overall improvement of the model predictions after the fitting stages. The base fitting stage improves respiratory variables and gas exchange predictions during rest and exercise. Similar behaviors as nominal results are observed, but with an offset change, wherein the model results are closer to the experimental data's mean trend. The predictions of cardiovascular variables showed only an improvement in PS. The model's specific fitting improves most respiratory and cardiovascular predictions, evidencing behavior modifications under the stimulus's increase concerning the base fitting results.V E, VT, BF, PS, PM, and PD showed improvements mainly regarding rest and moderate stimulus levels, while HR improved his behavior for high levels of exercise. The stimulus fitting does not significantly improve the model accuracy but primarily benefits the systematic blood pressure predictions. Figure 5 shows the PE values obtained from the model predictions under nominal conditions and at each fitting stage. The mean, median, interquartile range, overall values, and statistically significant differences among the predictions are presented. The PE results confirm the steady-state predictions' observations. The highest errors are obtained under nominal conditions, and the last fitting stage reduces the overall PE by 21.9%. The most significant PE value changes are presented for the predictions of respiratory variables and systemic blood pressure measurements, with statistically significant differences for V E, VT, PS, PM, and PD. Although the results for PACO2 and PAO2 do not show significant differences between consecutive fitting stages, a lower dispersion for PACO2 and an improvement of 0.07% and 39.30% was obtained for PACO2 and PAO2 predictions, respectively. The most significant decrease in the overall PE was obtained for the specific fitting approach, which also had the most negligible negative effect on the previous prediction results, followed, in order, by the base fitting approach and the stimulus-related fitting approach. Table 6 presents the PE mean and standard deviation values for the model predictions under nominal conditions and at each fitting stage for the related subsystems. In general, a significant decrease in PE was found at each fitting stage. Slight adverse effects were evidenced at the base and stimulus-related fitting approaches. Improvements associated with cardiovascular variables were mainly obtained in the last fitting stage. They were related to the effects of exercise mechanisms on systemic arterial pressures. The most significant results for gas exchange predictions were obtained after the model's base fitting. The other stages do not present significant variations in PE, as Figure 4 and Figure 5 show. The results related to respiratory mechanics present the most significant variations between stages. This subsystem has the highest contribution to PE under nominal conditions and was reduced by around 30% after the specific fitting approach. 3.3.2. Transient Response Figure 6 presents the model transient results under nominal conditions and at each fitting stage for a single-step load simulation. Experimental and model-predicted data are depicted as proportional changes to the variable's initial values. Comparisons for every variable are presented, even though the experimental record length was shorter than the model simulation time. The simulation results do not present significant variations for the different fitting stages, consistent with the proposed fitting strategies focused on predictions in the steady state. As part of the validation strategy, it is shown that the predictions had consistent behaviors regarding the dynamic response of the experimental data, mainly highlighting the similarity for HR and V E. The rest of the predictions do not entirely mimic the dynamics of the experimental data. Table 7 shows the model predictions' settling times for a single load step simulation under nominal conditions and at each fitting stage. The settlement time results showed changes among the fitting stages. The obtained time values show adverse effects on the respiratory variables' predictions and significant improvements concerning the variables of the gas exchange system. No significant effect was obtained for HR. 4. Discussion 4.1. Parameter Classification This work presents a methodology focused on selecting reduced sets of model parameters that can be reliably fitted in steady-state conditions following several classification approaches. The methodology is based on applying complementary and sequential techniques of parameter classification that evaluate criteria, such as the role in the model, identifiability, and sensitivity to its variation. It involves modifications to reported techniques that evaluate different stimulus levels, imply variations in the parameter values, and consider the experimental data by evaluating the error contribution. The parameters' role classification initially constrained those parameters that should be considered for subsequent selection and fitting procedures. Five role classification groups of the parameters most commonly found in mathematical models of physiological systems were proposed. They were based on time constants, conversion parameters, covariates, initial values, and gain and thresholds that facilitated the case study model's parameter selection. The parameter identifiability classification was based on Jacobian matrix analysis, which focused on determining which parameters can be reliably fit from available experimental data. Different stimulus levels were evaluated, considering their effects on the model's prediction behavior. The first three parameters, classified as most identifiable for the case study, were selected . Each one belongs to one of the main subsystems of the evaluated model (cardiovascular, respiratory, and gas exchange), and their well-conditionality for reliable estimation could be related to the order of magnitude of their nominal values (Table 5). A single significant difference between the parameters in the first position concerning the others presented shows the difficulty of finding a unique identification solution considering more than one parameter . This fact is related to the model's limitation to better mimic the experimental data regarding the results under nominal conditions, which could already be considered sufficiently close. The above can be related to the small decreases in overall PE at each fitting stage and was involved in the value selection of termination tolerance in the function evaluation for the optimization algorithm (Table 1). Parameter sensitivity analysis is based on finite difference measurements. It evaluates model variable predictions in steady-state conditions under parameter variations and different stimulus levels. In particular, steady-state conditions allowed considering variable magnitude changes instead of changes to temporary lags among simulated variables, mainly observable in variables with oscillating dynamic behaviors such as Psa, BF, PAO2 and PACO2. Normalization measures were applied to the obtained relative sensitivities for each stimulus level and variable to obtain unbiased results (Equations (15) and (19)). Finally, given that the sensitivity analysis does not consider the closeness between the predicted and experimental data, PE for each case (variable and stimulus level) was used as a weighting factor to highlight cases where the error was exceptionally high. This consideration results in classifications that are more consistent with the selecting and fitting procedures (Equations (15)-(22)). These modifications are related to obtaining the most respiratory control and mechanics parameters in the first positions of the total sensitivity ranking , considering that their predictions provide the most significant error under nominal conditions at different stimulus levels . For the specific rankings by variable, obtaining parameters related to the own systems and controllers in the first positions is related to the equitable evaluation of the sensitivities, except for PAO2 and PACO2 due to their high sensitivity concerning variables from other systems . 4.2. Parameter Selection Parameter selection based on the parameter's classification according to their role in the model allowed a significant reduction of the complexity associated with subsequent selection and fitting procedures, mainly evidenced by the computational cost involved in the simulations. Its correct application depends on the model mechanisms' knowledge, its parameters, and the conditions to be simulated because some parameter variations may not be adequate or relevant for the stimulus, environmental conditions, and population features to be represented. Only parameters related to the response in magnitude were selected in this work, which is consistent with the model predictions in steady state and allowed to reduce the PEs in the fitting stages . In applications focused on fitting the temporal response of model predictions, it is necessary to consider parameters related to time-dependent characteristics. The procedure results based on the base fitting approach were mainly related to the respiratory system parameters and controller parameters, which is coherent considering that the model predictions under nominal conditions provide the highest PE values . The model selected parameters agree with the most influential ones, both for its systems and controllers, and their influence on the regulations with the most significant impact on all subsystems in closed-loop: KpO2, KcCO2 and Kbg of the ventilatory controller, related to V E; Ers and Pmax related to BF, VT, and TI; T0 related to HR; KRlv related to systemic arterial pressures and blood flows; and MRBCO2 related to MRV. Parameter selection based on the specific fitting approach was proposed to obtain optimal results focused on decreasing the PE values for each variable without negatively affecting the rest of the predictions, as usually happens under the traditional fitting approach. For the case study model predictions, a single parameter per variable was chosen based on its relative sensitivities . Most of the selected parameters agreed with the first positions in the rankings. They belonged to the controllers and were related to the essential regulations of the model in a closed loop. In contrast, the parameters selected for PM, PD, and PACO2 were not the most relevant for their rankings because of the high influence of the system controllers in such variables (they can be simultaneously affected by a considerable number of parameters of different subsystems and controllers). Following the above and adding that several variables can belong to the same system or controller, some of the selected parameters were found in relevant positions of other rankings, which could be related to the adverse effects obtained for PM, TI, and PACO2 in the second fitting stage . Parameter optimization under the stimulus-related fitting approach aims to improve the behavior of predictions. This procedure is justified for the case study, considering that although the model was previously evaluated , the mechanisms related to the exercise stimulus have not been fitted considering the experimental data. Due to the above, parameters directly related to the effect of the mechanisms on regulatory activities were selected. The fitting of these parameters mainly affected the systemic blood pressure variables (PS, PM, and PD), which agrees with what was expected because most of the mechanisms are related to regulating blood flows and cardiovascular resistances . 4.3. Model Fitting The fitting procedure was proposed as a sequential application of three stages based on different approaches that improved the model's prediction capacity. The order of the stages was selected considering, firstly, reducing the overall PE, bringing the general trends of simulation results and experimental data closer; secondly, decreasing specific PEs with the least possible adverse effect between predictions; and finally, improving the behavior of the predictions regarding the stimulus. The stages' results are related to the modification of the values of the selected parameters for each one, considering the constriction of the evaluation ranges for optimization according to the function in the model and the physiological sense (results Section 3.1 Classification and Selection of Parameters and Section 3.2 Model Fitting). The stage based on the base fitting approach presented an improvement in steady-state respiratory and gas exchange variables. The predictions' displacements characterized the results without significant changes in the behaviors regarding the stimulus . The best respiratory variable results are mainly related to most of the respiratory controller parameters selected for this stage. The decrease in Pmax promotes the respiratory controller to decrease TI and increase BF , which, considering its linear behavior regarding the stimulus , favors a constant increase in V E at each level (equations of the ventilation controller in the Supplementary Material). The increase in V E involves more appropriate gas exchange, evidenced by decreases in PACO2 and increases in PAO2. Feedback from the gas exchange allows regulating V A in the respiratory controller, according to the changes in KcCO2, KpO2, Kbg and MRBCO2 (affecting MRV) (equations of the ventilation controller in the Supplementary Material). Concerning the cardiovascular variables, the overall decrease in systemic blood pressure measurements (PS, PM, and PD) and the non-significant change in HR are mainly due to the decrease in KRlv (heart's equations in the Supplementary Material) and the slight increase in T0 (effector's equations for reflex control in the Supplementary Material), respectively, in an attempt by the model to maintain adequate blood flow values for gas exchange. The stage based on the specific fitting approach presented improvements in most predictions concerning what was previously obtained . This is related to the model's capacity for adapting mechanisms related to each variable by parameter modifications with minimal interference in the other predictions. The adverse effects presented can be attributed to the optimization difficulty concerning two main aspects: similarities in the sensitivity rankings of parameters for different variables and the effect of other predictions on regulation processes. Regarding TI, the parameters selected for V E and BF have important positions concerning their sensitivity ranking. They are variables regulated by the same controller , which, in turn, are involved in the regulation of themselves (equations of the respiratory controller in the Supplementary Material). The PACO2 ranking of sensitivities showed that due to the similarity concerning the rankings of the respiratory variables and the low importance of the parameters related to its regulation , its prediction is mainly affected by other predictions. The improvements in blood pressure predictions are mainly related to the increase in cardiac pressure and the decrease in arterial and peripheral resistance. The increase in KE,lv increases Pmax,lv and compensates for the previous change in KRlv (heart's equations in the Supplementary Material), while the increase in Phmax and the decrease in Rsa are related to lower input resistance to the peripheral and arterial beds (equations of blood flow local control and systemic arteries in the Supplementary Material), obtaining a Psa signal with an increase in the base level at all stimulus levels . A more significant improvement was obtained regarding HR because the increase in GT,v allows a decrease depending on the parasympathetic activity at each stimulus level (effector's equations for reflex control in the Supplementary Material). The correct increase in V E is related to increases in V0dead and BF (equations of the ventilation controller in the Supplementary Material), which, in turn, is related to decreases in TI due to changes in n and l1 (equations of the breathing pattern optimizer in the Supplementary Material). Changes in the behavior of the cardiovascular and respiratory variables regarding exercise were evidenced in this fitting stage and are mainly related to (1) modifying the vasodilation mechanism during exercise due to Phmax and (2) changing the respiratory controller due to n and l1. This promotes similar changes in the gas exchange system, consistent with decreases in PACO2 and increases in PAO2, also related to increased C1 and decreased VLCO2, respectively (equations of the gas exchange and mixing in the Supplementary Material). The parameter optimization of mechanisms directly related to the stimulus presented improvements mainly for systemic blood pressure measurements because most of them are related to regulations of vascular resistances and blood flows . Adverse effects of the fitting were evidenced in V E, VT and HR, and are mainly related to the optimization priority of cardiovascular parameters. The optimizations related to the cardiovascular controller were mainly characterized by a more significant role of NT and a minor role of I in sympathetic and parasympathetic activities regarding the previous fitting stage (Table 5 and the equations of the efferent pathways in the Supplementary Material). Besides the decrease in the effect of I-Ramp (Table 5 and equations of the blood flow local control in the Supplementary Material), these results generated smaller increases relative to stimuli for HR (effector's equations for reflex control in the Supplementary Material), peripheral vascular resistances, unstressed venous volumes, and ventricular elastances. The cardiovascular controller regulations and the increased effect of V-Ramv, MP and RP (Table 5 and the equations of the systemic peripheral and venous circulation, respiratory pump, and muscle pump in the Supplementary Material) generated a Psa signal with higher amplitude and base level at low exercise, and smaller increases as a function of the stimulus. Cardiovascular modifications change the behavior of gas exchange system variables, evidenced by slight improvements in PACO2 and PAO2, but feedback to the respiratory controller implies a variation in the V E slope, moving away from the experimental data at low stimulus levels. V E is compensated at high levels of stimulus by the decrease in KcMRV and the increase in BF (Table 5 and the equations of the ventilation controller in the Supplementary Material), and the latter is due to the decrease in TE, which is an expected result during exercise , and is achieved by the decrease in l2 (equations of breathing pattern optimizer in the Supplementary Material). Some results reached the bounds of the proposed evaluation range, evidencing greater differences than expected between the characteristics represented by the nominal values and the experimental data (Table 5). These results were presented for parameters whose value cannot be compared with physiological measurements, and the reported data are mainly related to optimizations focused on mimicking experimental responses. According to the above, they can be considered candidates from a wider evaluation range in future fitting works for the same model. 4.4. Validation 4.4.1. Steady-State Response A decrease in PE for the entire model for each variable and subsystem was obtained throughout the fitting stages , showing that the model's parameter optimization allows the experimental data to be more adequately predicted in comparison with nominal values. This result was evidenced mainly by changes in the base trend and the behavior of the predictions concerning the stimulus, presented differently depending on the variables and the stimulus level . Although the predictions have behaviors and values that still differ from the experimental mean trend, all the results reasonably approximate a directionally appropriate trend regarding the stimulus change. The respiratory variables were adequately predicted at rest, but the PEs increased with the exercise level . The simulation results showed linear behaviors regarding the stimulus. V E and VT results were similar to expected, although with higher slopes, and BF and TI disagreed. This fact can be related to the limitations of the fitting procedure and the model mechanisms used to represent the experimental behavior, considering that the main parameters related to the stimulus and the respiratory controller's feedback had been optimized. Most cardiovascular variables' predictions presented a behavior opposite respiratory predictions, characterized mainly by lower PE at high stimulus levels. The simulation results in steady state exhibit non-linear behaviors, with similarities regarding the experimental variables related to the number of different regulatory mechanisms. The differences concerning the mean experimental data showed a priority for adjusting PS at all stimulus levels and a proper prediction for HR, PM, and PD only at medium and high exercise levels . This is due to the proper optimization of parameters mainly related to stimulus and PS. Even so, the possible fitting of the mechanisms related to the predictions at rest stands out. The minor decreases in PE were obtained for the gas exchange system and are related to the PACO2 and PAO2 predictions under nominal conditions already presented the best fit compared to the other variables . Considering that the regulated variables in this system correspond to the most crucial feedback of both controllers of the model, slight variations in behavior and values are significant and related to the improvement of the entire model's prediction results. Thus, obtaining higher PAO2 and lower PACO2 values agreed with the expected response of healthy subjects under the simulated stimulus levels and allowed better predictions for the other variables ; but, the increase in the PE of these variables regarding the increase in exercise could be related to the presented fitting limitations, mainly regarding the respiratory variables . 4.4.2. Transient Response The simulation results in the transient regime did not present significant variations in magnitude change or behavior between the model under nominal conditions and in the fitting stages , probably because the strategy procedures were only focused on steady-state fitting. The most significant variations regarding the model results under nominal conditions were related to the settling time, highlighting an increase in the respiratory variables, no significant changes in HR, and a significant decrease in the gas exchange variables (Table 7). These results are mainly related to changes in the magnitude of the predictions. Although parameters related to the model's temporal behavior were not optimized, the equations that describe the different dynamic behaviors are affected by the transition's speeds and initial integration values. Even so, the transient predictions exhibited behaviors that, although they did not fully mimic the complex dynamics of the experimental data, reasonably approximated the general trends and are directionally appropriate considering the change in stimulus. 4.5. Strategy Application In this work, a fitting and validation strategy for physiological models with a large number of parameters and with the consideration of different populations and stimuli was proposed. This strategy was implemented in a case study of a cardiorespiratory model to fit and validate it regarding experimental data from healthy adult subjects on incremental aerobic exercise. According to the results, it can be considered that the fitted model agrees with the validation criteria of physiological models and predicts with reasonable accuracy and precision the experimental data in both transient and steady-state regimes. This result demonstrates the usefulness of the proposed strategy and the procedures that comprise it. The purpose of the presented strategy was to provide a systematic methodology for fitting and validation that could be implemented generically in physiological system models, considering predictions under different stimuli, subjects, and experimental conditions. This strategy comprises different procedures and modified techniques that improve the prediction capacity for steady-state predictions. A fitting approach based on the transitory regime's model predictions could be included as future complementary work. In this case, the procedures for classifying, selecting, and optimizing parameters that characterize temporal dynamic behavior should be considered. It is important to note that the proposed strategy aims to reduce the optimization problem's complexity, constraining parameter optimization results to values with physiological justification, and reducing the possibility of obtaining multiple fitting solutions. The benefits of its application will depend on (a) the relationship between the quantity and variety of experimental measures available regarding the number of parameters of the model to be fitted; (b) the model's capacity to mimic the behaviors of the experimental data; and (c) proper knowledge of the physiological system and the mechanisms of the model. The lack of any of these aspects will constitute a limitation in the application of the strategy, and its consequences will be evident in the poor results of applying the procedures and techniques that compose the approach. A constrained number of experimental variables or a low relationship between them and the model parameters would affect the parameter classification techniques, obtaining low and similar sensitivity values and the different optimization stages, and encouraging multiple identification solutions. The inappropriate choice of a physiological model to represent the experimental data will impact the optimization stages, leading to a lack of precision and accuracy of the results in the validation. Finally, the lack of knowledge about physiological systems and the different mechanisms associated with the model will affect the proper classification, selection, and constraint of parameter values. Due to the improvement of the prediction capacity and the adequate validation results of the cardiorespiratory model of the case study, both the model and the proposed fitting and validation strategy could be implemented in future works related to diagnostic applications, including athlete evaluation studies, detection of cardiorespiratory diseases, and simulation of the cardiorespiratory response under therapeutic treatments. Furthermore, the application of this strategy regarding experimental data from longitudinal records over time could be considered the basis for developing a dynamic fitting strategy. In this sense, the information obtained from the role, sensitivity, evaluation ranges, and parameter optimization at each instant in time could be used to analyze the temporal evolution of physiological system parameters and predict their future value. The implementation of the proposed strategy mainly involves the development and execution of software based on data storage and processing. The storage corresponds to the digital recording of the data of physiological variables in databases. At the same time, the processing includes the execution of code and algorithms related to the mathematical model of the physiological system under study and the techniques, stages, and procedures defined by the strategy. The recording of physiological measurements and signals will involve the use of applications that concentrate data from different possible sources, such as personal health devices, laboratory equipment, or medical equipment from clinical environments. The execution of the processing software should be semi-supervised, considering the importance of knowledge of the physiological system and its mathematical model, although in future works, training based on artificial intelligence could be evaluated to fully automate the process. New findings, such as model improvements, new parameter classification techniques, optimization, or validation criteria, can be incorporated into the strategy as long as the order described in each main procedure is considered. The results obtained must be interpreted by medical staff and can support clinical decisions regarding diagnosis and health monitoring. 5. Conclusions This paper presents a strategy for fitting and validating physiological models with a large number of parameters under the consideration of different populations and stimuli. The strategy consists of different procedures and techniques that improve the model's prediction capacity, considering the complexity reduction of the optimization problem, the results of parameter values with physiological justification, and minimization of the possibility of multiple fitting solutions. The validation results demonstrate that the case study model is adequate for predicting the cardiorespiratory response of healthy adult subjects under rest and aerobic exercise conditions with reasonable precision and accuracy. This model can constitute an analysis and diagnostic tool related to studies and evaluations of the cardiorespiratory system. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Schematic diagram of the model under study; Table S1: Symbols' description of the model's schematic block diagram; Experimental data description; Model equations and parameters. Click here for additional data file. Author Contributions Conceptualization, C.A.S., L.Y.S., A.M.H. and M.A.M.; methodology, C.A.S., L.Y.S., A.M.H. and M.A.M.; software, C.A.S. and L.Y.S.; validation, C.A.S., L.Y.S., A.M.H. and M.A.M.; formal analysis, C.A.S. and L.Y.S.; investigation, C.A.S., L.Y.S., A.M.H. and M.A.M.; data curation, C.A.S.; writing--original draft preparation, C.A.S., L.Y.S. and A.M.H.; writing--review and editing, C.A.S., L.Y.S., A.M.H. and M.A.M.; visualization, C.A.S. and L.Y.S.; supervision, C.A.S. and A.M.H.; project administration, A.M.H.; funding acquisition, A.M.H. and M.A.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study related to the experimental data used in this work was conducted in accordance with the Declaration of Helsinki and approved by the Human Research Ethical Committee of the Department of University Research (SIU) of the University of Antioquia (approval certificate 17-59-711). Informed Consent Statement Informed consent was obtained from all subjects involved in the study related to the experimental data used in this work. Data Availability Statement The experimental data used in this work correspond to those recorded to build and evaluate the cardiorespiratory model, and the complete description of the procedures and characteristics is reported in a previous paper . The information required to replicate the cardiorespiratory model can be found in the paper of the model building and evaluation . The equations and parameter values to implement and replicate the proposed strategy are described throughout this work and in the reported Supplementary Material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Schematic diagram of the fitting and validation strategy. The dotted lines divide the diagram into the main procedures and their respective stages: the first procedure is at the top and corresponds to the classification and selection of parameters; the second is in the middle and corresponds to model fitting, and the third one is at the bottom and corresponds to model validation. Figure 2 Top ten positions in the rankings of classification techniques: (a) correspond to the results for subset selection and (b) to the results for sensitivity analysis techniques. The light gray bars correspond to the selected base setting parameters, and the dark gray bars correspond to the parameters that will remain fixed at the nominal values. Figure 3 Relative sensitivity rankings after removing the parameters selected for the base fitting approach. The light gray bars correspond to the selected parameters for the specific fitting approach, and the dark gray bars correspond to the parameters that remain fixed at nominal values. The subfigures from (a) to (i) correspond to the result for each of the variables evaluated. Figure 4 Steady-state model predictions for each cardiorespiratory variable evaluated. Results are shown as a function of V CO2 values. Gray dots denote the experimental data limited at each subject's AT; the black dot-line the experimental data average; the square marker the model predictions under nominal conditions (Nominal); the cross marker the predictions of the model at the first fitting stage (Base); the plus sign marker the model predictions at the second fitting stage (Specific); and the diamond marker the model predictions at the third fitting stage (Stimulus). The subfigures from (a) to (j) correspond to the result for each of the variables evaluated. Figure 5 PE results for steady-state predictions under nominal conditions and at each fitting stage. The bar graph represents the errors' median values, and the whiskers represent the interquartile distance. The gray bars represent the PE under nominal conditions (Nominal), the line pattern bars the results at the first fitting stage (Base), the dots pattern bars the results at the second fitting stage (Specific), and the white bars represent the results at the third fitting stage (Stimulus). Symbols (*) and (**) highlight the statistically significant differences found between the obtained PE values (r < 0.05 and r < 0.01, respectively). Figure 6 Transient results for a single load step. Model inputs correspond to variations of V O2 and V CO2 from 0.64 to 0.82 L/min and 0.58 to 0.76 L/min, respectively. They were obtained from the experimental mean values at the beginning and end of the first exercise load step. The dotted lines are the simulation results under nominal conditions (Nominal); the dashed lines are the simulation results at the first fitting stage (Base); the dash-dot lines are the simulation results at the second fitting stage (Specific); and the dotted lines with cross marker are the simulation results at the third fitting stage (Stimulus). The simulation results are compared with the corresponding experimental data. The solid gray and black lines represent the subject-by-subject experimental data restricted at AT, and their total mean value. The subfigures from (a) to (i) correspond to the result for each of the variables evaluated. diagnostics-13-00908-t001_Table 1 Table 1 Parameter values used for the CMA-ES algorithm. Name Definition Value Fitness limit Value to reach Infinite TolFun Termination tolerance in the function evaluation 10-12 TolX Termination tolerance on x 10-3 MaxIter Maximal number of iterations 100x N2 * MaxFunEval Maximal number of function evaluations 500 MaxRestart Number of restarts 10 PopSize Population size 4+3ln(N)2 s Initial coordinate-wise standard deviation(s) 0.2(UB-LB) ** * N is defined by the number of the objective variables. ** UB and LB are the upper and lower bounds of objective variables (related to the model parameters' evaluation ranges). diagnostics-13-00908-t002_Table 2 Table 2 Distribution of the model parameters according to their role. Role Number of Parameters Covariates 12 Conversion parameters 1 Gain and thresholds 239 Initial values 24 Time constants 40 diagnostics-13-00908-t003_Table 3 Table 3 Selected parameters for stimulus-related fitting. Mechanism Parameter Regulatory Activity I-EP gsh,max Sympathetic activity to heart gsp,max Sympathetic activity to peripheral resistances gsv,max Sympathetic activity to veins volumes gv,max Vagal activity NT Wt,sh Sympathetic activity to heart Wt,sp Sympathetic activity to peripheral resistances Wt,sv Sympathetic activity to veins volumes Wt,v Vagal activity I-Ramp gM Effect of hypoxia on vascular vasodilation of active muscles during exercise V-Ramv kr,am Changes in venous resistance of active muscles during exercise MP Aim Venous return of active muscles RP gabd Abdominal pressure signal gthor Thoracic pressure signal MRV KcMRV Change in alveolar flow from its resting value minWOB l2 Total work of breathing diagnostics-13-00908-t004_Table 4 Table 4 Evaluation ranges of parameters according to the variations and constraints reported. Parameter Lower Bound (%) Upper Bound (%) Ers -70 30 KE,lv -30 5 l1 -50 30 l2 -30 200 n -30 90 Pmax -30 200 VLCO2 -30 50 The values are shown for upper and lower bounds correspond to the percentage of variation regarding the parameter's nominal value. diagnostics-13-00908-t005_Table 5 Table 5 Comparison of the parameter nominal values and optimization results for each fitting stage. Parameter Nominal Value Fitted Value Units Base fitting approach KpO2 4.7200 x 10-9 4.3473 x 10-9 mm Hg-4.9 KRlv 3.7500 x 10-4 3.9120 x 10-4 s/mm Hg MRBCO2 9.0000 x 10-4 9.3366 x 10-4 L/s STPD Kbg 17.4000 16.6734 Dimensionless KcCO2 0.2332 0.2395 mm Hg-1 T0 0.5800 0.5877 s Pmax 50.0000 42.4337 cm H2O Ers 21.9000 22.2940 cm H2O/L Specific fitting approach GT,v 0.0900 0.0951 Dimensionless Rsa 0.0600 0.0522 mm Hg*s/mL KE,lv 0.0140 0.0105 mL-1 Phmax 20.0000 22.0349 Dimensionless l1 0.8600 0.8901 Dimensionless V0dead 0.1587 0.2059 L n 1.1010 1.0157 Dimensionless C1 9.0000 9.5133 mmol/L VLCO2 3.0000 2.1479 L Stimulus-related fitting approach gsh,max 9.0 6.3 spikes/s gsp,max 5.50 3.85 spikes/s gsv,max 64.90 84.37 spikes/s gv,max 1.9000 2.0708 spikes/s Wt,sh 0.4000 0.5043 Dimensionless Wt,sp 0.4000 0.4016 Dimensionless Wt,sv 0.4000 0.4268 Dimensionless Wt,v 0.4000 0.4341 Dimensionless gM 40 28 Dimensionless kr,am 24.1700 27.7488 s/mL Aim 50.0000 59.6992 mm Hg gabd 3.3900 4.0826 mm Hg/L gthor 6.800 6.818 mm Hg/L KcMRV 1.000 0.895 Dimensionless l2 0.4890 0.3423 Dimensionless Where STPD is standard temperature and pressure, dry. diagnostics-13-00908-t006_Table 6 Table 6 Prediction error results (%) at each fitting stage for the model subsystems. Fitting Stage Cardiovascular Respiratory Mechanics Gas Exchange Nominal 8.33 +- 1.73 15.54 +- 3.87 4.03 +- 0.97 Base 8.71 +- 1.62 13.25 +- 2.02 3.27 +- 1.67 Specific 8.22 +- 1.46 10.83 +- 2.13 3.24 +- 1.78 Stimulus-related 7.41 +- 1.53 11.16 +- 1.35 3.28 +- 1.78 Table 6 shows the model PE under nominal conditions and at each fitting stage. The results are presented in function to the model subsystems: cardiovascular, respiratory mechanics, and gas exchange. diagnostics-13-00908-t007_Table 7 Table 7 Settling time (seconds) of the model predictions for each fitting stage. 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PMC10000474 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050913 foods-12-00913 Article Effect of Hyaluronic Acid and Kappa-Carrageenan on Milk Properties: Rheology, Protein Stability, Foaming, Water-Holding, and Emulsification Properties Sutariya Suresh G. * Salunke Prafulla Investigation Data curation Writing - review & editing Supervision Project administration Funding acquisition Chalova Vesela Academic Editor Liu Ru Academic Editor Liang Hongshan Academic Editor Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007, USA * Correspondence: [email protected] 21 2 2023 3 2023 12 5 91325 12 2022 17 1 2023 13 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Hyaluronic acid (HA) is now widely known for its ability to bind water and impart texture. The combined effects of HA and kappa-carrageenan (KC) have not yet been investigated, though. In this study, we looked at the synergistic effects of HA and KC (concentrations of 0.1 and 0.25%, and ratios of 85:15, 70:30, and 50:50 for each concentration) on the rheological properties, heat stability, protein phase separation, water-holding capacity, emulsification properties, and foaming properties of skim milk. When HA and KC were combined in various ratios with a skim milk sample, this resulted in lesser protein phase separation and a higher water-holding capacity than when HA and KC were utilized separately. Similarly, for the sample with a 0.1% concentration, the combination of HA + KC blends demonstrated a synergistic impact with greater emulsifying activity and stability. The samples with a concentration of 0.25% did not exhibit this synergistic effect, and the emulsifying activity and stability were mostly due to the HA's higher emulsifying activity and stability at 0.25% concentration. Similarly, for rheological (apparent viscosity, consistency coefficient K, and flow behavior index n) and foaming properties, the synergistic effect of the HA + KC blend was not readily apparent; rather, these values were mostly due to an increase in the amount of KC in the HA + KC blend ratios. When HC-control and KC-control samples were compared to various HA + KC mix ratios, there was no discernible difference in the heat stability. With the added benefits of protein stability (reduced phase separation), increased water-holding capacity, improved emulsification capabilities, and foaming abilities, the combination of HA + KC would be highly helpful in many texture-modifying applications. hyaluronic acid kappa-carrageenan rheology protein stability water holding oil emulsion foaming Dairy and Food Science Department, South Dakota State Universitythe HATCH projectSD00H749-22 This research was supported by the Dairy and Food Science Department, South Dakota State University and the HATCH project (Grant number SD00H749-22) development. pmc1. Introduction In Japan and South Korea, hyaluronic acid (HA) is recognized as a food additive and health food, respectively. HA is available as a dietary supplement in Belgium, Canada, Italy, and the United States . In 2021, China approved HA as a food and beverage additive. In the US a proposal to give HA the GRAS designation, allowing for its usage in foods and beverages, is currently being reviewed by the FDA . Given that HA is becoming more and more accepted in food applications, and its health advantages, learning more about its functional properties in dairy and food applications is very beneficial. In an aqueous environment, HA forms polymer spheres by occupying a high hydrodynamic volume because of the repulsive force between the negative charge of the carboxyl group and the intramolecular hydrogen bond . This negative charge is due to the carboxylic acid group which helps HA molecules bind large amounts of water molecules. Because of its large water-binding ability, HA forms a highly viscous gel when mixed with an aqueous solution . We are employing skim milk as a platform to investigate the functional advantages of HA in milk systems because of its capacity to build a viscoelastic network and increased water-binding capability in aqueous solutions. The knowledge from this milk system can also be applied to various dairy products in the future. Our latest research revealed that although HA made milk viscous, it had a negative impact on protein stability (phase separation) during storage . KC is well known to stabilize the milk protein through its interaction with casein micelle when used in low concentrations . Our hypothesis is that combining HA and KC may help address the issue of protein stability and enable the use of HA in dairy products to take advantage of its distinct rheological properties and health advantages. In addition to protein stability during shelf-life storage, protein stability during heat processing is crucial, and specific hydrocolloids are known to alter the heat stability of milk proteins during heat processing . We conducted this investigation to further understand the impact of the HA + KC blend on milk heat stability because it was found in our earlier work that HC negatively affected the heat stability of milk protein . Apart from rheological and textural benefits, hydrocolloids are also important in providing functional benefits such as foaming and emulsification properties. Our interest in thoroughly researching the synergistic role of the HA + KC blend in increasing the foaming and emulsification capabilities was sparked when preliminary experiments revealed that a combination of HA and KC created stable foams. The water-holding capacity and frequency sweep data were collected to understand the interaction of the HA + KC blend in the skim milk system and its effect on different functional properties. The study was designed with the objective to determine the effect of different concentrations and ratios of HA and KC blends on various physicochemical properties of milk such as (i) protein phase separation during storage and heat stability during processing, (ii) viscosity profile and hydrocolloid interactions in a milk environment, (iii) foaming properties, (iv) water-holding capacity, and (v) emulsification properties. 2. Materials and Methods 2.1. Design of Experiment The study used a blend of HA and KC at two different concentrations (0.1% and 0.25%), along with five different HA:KC ratios for each concentration level. The HA:KC ratios used were 100:0 (HA-control), 85:15, 70:30, 50:50, and 0:100. (KC-control). Investigations were conducted on milk's viscosity, protein stability during storage and processing, water-holding capacity, foaming potential, and emulsification qualities. Figure 1 graphically displays the experiment's design. 2.2. Milk Sample Preparation The sample of skim milk was bought from a nearby supermarket (Hy-Vee, Brookings, Washington, DC, USA). The preparation of samples and their analysis were performed as per the procedure described by Sutariya and Salunke . Using Milkoscan model TM FT3 (Foss analytical A/S, Hillerod, Denmark), the contents of the skim milk samples' fat, protein, lactose, and total solids were determined. The Kjeldahl standard method, as described by , was used to determine the total protein content, and the pH was measured using a pH meter (Hanna edgeblu, Smithfield, VA, USA). To preserve milk samples, a small quantity (0.02%) of sodium azide was added. The HA ~1500 kDa (Talsen Chemicals, New York, NY, USA) and KC powder (Cape crystal brands, Summit, NJ, USA) were dissolved in the milk to create samples with various concentrations and ratios of HA and KC as described in the experiment design . Pre-weighed amounts of HA and KC powder were mixed in cold milk (5 degC) at 25,000 rpm for 3 min using a high shear homogenizer POLYTRON(r)pt 2500 E (Kinematica AG, Malters, Switzerland). The samples were examined after mixing to ensure that the powders had been completely distributed and there were no discernible lumps. Following the mixing stage, the samples underwent a 20 s heat treatment at 80 degC before being quickly cooled in an ice-water bath (1 degC). After the heat treatment, these samples were hydrated in the refrigerator (5 degC) for 12 h. The final pH of these milk samples was adjusted to 6.7 using either 1 M HCl or 1 M NaOH while the milk was being stirred continuously. These samples were tested for gravimetric phase separation (protein stability), viscosity profile, frequency sweep, heat coagulation time (HCT), water-holding capacity, foaming capacity, foaming stability, emulsion activity, and emulsion stability analyses. 2.3. Frequency Sweep A slightly modified version of the frequency sweep test described by Sutariya and Salunke was used to better understand the time-dependent behavior and interactions of HA and KC polymers in the milk environment. The frequency sweep was carried out at a constant shear strain of 0.5% and over an angular frequency range of 16.7 to 89.5 rad/s. The sample temperature during the entire test was maintained at 5 degC. Values of the storage modulus (G', Pa) and the loss modulus (G'', Pa) were plotted against angular frequency range values. 2.4. Protein Phase Separation by Gravimetric Settling Method during Storage A slightly modified version of the method published by Sutariya and Salunke was used to assess the protein phase separation by gravimetric settling (protein stability). The samples were weighed (50 g), placed in graduated measuring cylinders, and left undisturbed for 48 h in a refrigerator maintained at 5 degC to allow gravimetric settling of proteins and phase separation due to the effect of HA + KC in the milk environment. Following 48 h, these samples were photographed to help see the protein phase separation. The 15 g sample was then carefully removed from the top layer and its total protein content was analyzed . The percentage of protein phase separation was calculated using the equation below. (1) % Protein phase separation ={(Protein in control sample - Protein in top 15 mL layer )Protein in control sample }x100 2.5. Heat Stability Measured by Heat Coagulation Time Test (HCT) The HCT of the skim milk samples was determined using a method described by Sutariya and Patel with slight modifications. The 5 g of sample was filled in 8 mL Wheaton glass tubes (D-17 mm x H-61 mm), airtight sealed, and clamped on the rocker stand. The rocker stand was submersed in an oil bath (Narang Scientific works PVT. LTD., New Delhi, India) maintained at 140 degC and put on rocker speed 3. The time needed to develop observable precipitation or coagulation at 140 degC was designated as the HCT. 2.6. Viscosity Profile Measurement The method outlined by Sutariya and Huppertz was slightly adjusted to measure the viscosity profile of these samples. For the viscosity profile measurement, a ramp liner shear rate profile range from 10 to 1000 s-1 and a testing temperature of 5 degC were used. The shear rate was increased by 20 s-1 over a liner time ramp duration from 2 to 10 s. The viscosity tests were performed using an MCR-92 rheometer (Anton Paar GmhH, Graz, Austria) and an analytical geometry of concentric cylinder (CC39, 38.690 mm) and cup (C-CC39, 42.010 mm), operated by Anton Paar RheoCompass 1.20 system. The viscosity profiles were assessed using a power law model as described by Sutariya and Salunke in order to compare the samples' viscous nature at a low shear rate and non-Newtonian viscosity behavior. 2.7. Water-Holding Capacity The milk samples were heated in a hot water bath to a temperature of 30 degC and maintained there for 15 min. The 10 mL of sample was filled in a graduated centrifuge tube. The samples were centrifuged at 30 degC for 15 min at 2000x g using sorvall ST plus series centrifuge (ThermoFisher Scientific, Karlsruhe, Germany). At the end of the centrifugation, the volume of sediment was recorded, and it was stated by the following Equation (2) . (2) Water holding capacity % =(Volume of sedimentInitial sample volume)x100 2.8. Oil Emulsifying Activity and Emulsion Stability The milk and sunflower oil (Hy-Vee, Brookings, USA) were first brought to a temperature of 30 degC in a hot water bath and kept for 15 min. Emulsion activity and emulsion stability were determined according to the method described by Mao and Hua with some modifications. The 35 g of milk sample was mixed with 15 g of sunflower oil so that the 30% (w/w) oil-in-water emulsion could be tested . To obtain the emulsion, the milk and oil samples were homogenized at a speed of 15,000 rpm for 2 min at 30 degC using a high shear homogenizer POLYTRON(r)pt 2500 E (Kinematica AG, Malters, Switzerland). The 10 mL of sample was filled in a graduated centrifuge tube. The samples were centrifuged at 30 degC for 15 min at 2000x g using sorvall ST plus series centrifuge (ThermoFisher Scientific, Karlsruhe, Germany). The volume of the emulsion was recorded, and it was stated by the following Equation (3). (3) Oil emulsion activity % =(Volume of emulsion layerInitial sample volume)x100 Once the emulsion activity test was completed, the emulsion stability was determined by gently missing the aqueous and emulsion later in the same test tubes and re-centrifugation followed by heating at 80 degC for 30 min. The volume of the remaining emulsion was recorded, and it was stated by the following Equation (4). (4) Oil emulsion stability % =(Volume of remaining emulsion layerInitial sample volume)x100 2.9. Foaming Capacity and Foaming Stability Foaming capacity and foaming stability were based on the method described by Mao and Hua with slight modifications. The milk sample was first brought to a temperature of 30 degC in a hot water bath and kept for 15 min. The 100 mL milk samples were filled in a 250 mL graduated plastic beaker. The foaming was generated by mixing the sample in the same container at a speed of 15,000 rpm for 2 min at 30 degC using a POLYTRON(r)pt 2500 E homogenizer (Kinematica AG, Malters, Switzerland). Foaming capacity was determined by measuring the volume of foam instantly after 1 min of mixing. Then, it was stated by the following Equation (5). To study the foaming stability, the same samples were stored in a water bath maintained at 30 degC. Foaming stability was determined by measuring the reduction of the foam volume at intervals of 0.5, 1, 1.5, 2, 4, 5, 6, 18, and 24 h. Then, it was stated by the following Equation (6). In addition to the foaming capacity and stability at 30 degC, the foaming capacity and stability at 65 degC for the 0.1% (HA + KC) was also determined to understand the foaming capacity and stability for the application of skim milk in coffee preparations. (5) Foaming capacity% ={(Sample volume after foaming - Initial sample volume)Initial sample volume}x100 (6) Foaming stability (retention)% ={1-[(Sample volume after 1minoffoaming - Sample volume after xminoffoaming)Sample volume after 1minoffoaming]}x 100 x = 0.5, 1, 1.5, 2, 4, 5, 6, 18, and 24 h. 2.10. Statistical Analysis Each experiment was repeated three times. All the outcomes were examined using Minitab(r) statistical software (version 0.3.1). One-way ANOVA with a two-sided confidence interval, 95% confidence level, and Tukey comparison technique was used to analyze the statistical differences between the samples with various dosages of HA treatments. Differences were deemed significant when p-values were less than 0.05 . 3. Results 3.1. Frequency Sweep The frequency sweep is a useful technique for understanding the interpolymer interactions of HA + KC blends (at different concentrations and ratios) in the milk system. Frequency sweep results for 0.1% concentration and different ratios of HA + KC are displayed in Figure 2A,B. For the samples with 0.1%, HA + KC concentration, the higher G" values over G' values of the HA-control, 85:15, and 70:30 ratio (HA:KC) indicated the dominating viscoelastic liquid behavior of these samples and hence the absence of gel network. The sample with a 50:50 ratio (HA:KC) showed a shift to viscoelastic solid behavior (G' > G") at a lower frequency range (<43.7 rad/s) and back to viscoelastic liquid behavior (G" > G') at higher frequency (>43.7 rad/s). This viscoelastic solid behavior at the lower frequency indicated the presence of a weak inter-polymer network, which was mainly attributed by KC considering that the KC-control sample had a viscoelastic solid behavior (G' > G") through the complete frequency range (indicating the formation of stable inter-polymer network). Frequency sweep results for 0.25% concentration and different ratios of HA + KC are displayed in Figure 3A,B. Similar to 0.1% HA + KC concentration, the viscoelastic liquid behavior (G" > G') for the HA-control and 85:15 samples were also observed for the 0.25% HA + KC concentration. The samples with 70:30 (HA:KC) and 50:50 (HA:KC) showed viscoelastic solid behavior (G' > G") through the entire frequency range, where again the viscoelastic solid behavior was mainly attributed to KC considering that the highest viscoelastic solid behavior was observed with KC-control sample. These results also indicated that the HA and KC polymers in blended samples did not show a synergistic effect in forming the stronger gel network as compared to the KC-control sample. 3.2. Protein Phase Separation The gravimetric phases separation method was employed to examine the impact of HA + KC concentrations (0.1% and 0.25%) and various ratios on protein stability in the milk system during storage. The results obtained from the protein phase separation study provided important information about the effect of these two hydrocolloids on the stability of the protein in milk during storage. For both concentrations (0.1% and 0.25%), HA-control samples showed the highest phase separation among all the samples followed by KC-control samples. The higher phase separation in the HA-control sample could have been due to the depletion flocculation phenomenon . In the case of the KC-control sample, this may be related to the reduced KC-protein interaction at higher KC concentrations (>0.018%) . For the samples with 0.1% concentration, the blend of HA + KC at all three ratios showed significantly (p < 0.05) lower phase separation as compared to both KC-control samples. Similarly, for the samples with 0.25% concentration, the blend of HA + KC at all 3 ratios also showed significantly (p < 0.05) lower phase separation as compared to both KC-control samples. Lower concentration of KC (<0.05%) is typically recommended to minimize the milk protein phase separation through weak gel network formation. The application of higher KC concentration can lead to phase separation . Similarly, HA when used in a concentration > 0.05% leads to an increase in milk protein phase separation . The increased milk protein phase separation at higher concentrations of HA-control and KC-control (0.1 and 0.25%) was in alignment with the finding of these studies. Interestingly, when HA and KC were used in combinations at higher concentrations (0.1 and 0.25%) it showed a significant (p < 0.05) reduction in the milk protein phase separations. The lowest phase separation at both concentrations in the samples with a 70:30 ratio indicated the best synergistic effect in reducing the phase separation as compared to HA and KC when used alone. Hence, combinations of HA and KC will allow its application at higher concentrations (>0.1%) to gain the functional benefits of these hydrocolloids without having a significant impact on milk protein phase separation. The frequency sweep results indicated that the significantly reduced phase separation of the blended HA + KC samples were independent of their viscoelastic liquid behavior (G" > G', at ratios of 85:15 and 70:30 with 0.1% concentration, 85:15 ratio with 0.25% concentration) and viscoelastic solid behavior (G' > G", 50:50 ratio with 0.1% concentration, 70:30 and 50:50 ratio with 0.25% concentration), which indicated the possibility of protein stabilization through intertwined polymer network of HA and KC in the blended sample with the proteins in stabilizing them in the milk environment. 3.3. Heat Coagulation Time Test (HCT) The heat stability test (HCT at 140 degC) was carried out to understand the effect of HA and KC concentrations and ratios on the protein stability when subjected to the ultra-high temperature. The HCT results are displayed in Figure 5. For the samples with 0.1% concentration, the KC-control sample showed the highest HCT among all the samples. The increase in HCT with 50:50 (HC:KC) ratio at 0.1% concentration was mainly due to the contribution of KC. At a lower concentration level of 0.1%, the KC is known to interact with casein and thereby potentially increase the z potential which can improve heat stability through increased electrostatic repulsion . In the case of samples with 0.25% (HA + KC) concentration, the results were somewhat opposite to the results we observed at 0.1% concentration. At a higher concentration level of 0.25%, the KC is known to have reduced interaction with casein micelle ; however, in this case, the negatively charged HA could possibly enhance the heat stability through increased electrostatic repulsion via the HA-casein complex . Although all the samples showed lower heat stability (121 to 156 s) as compared to milk samples (395 s) it was still above the commercial UHT processing requirements and hence should not be a concern for heat processing. The mechanism behind these decreases in HCT is not well understood. However, one of the potential factors could be the increase in calcium ions and protein and concentrations in the continuous serum phase as a result of increased water binding by HA and KC . 3.4. Flow Behavior Properties The change in the viscosity behavior of milk samples as a function of different HA and KC concentrations and ratios is depicted in Figure 6A,B (0.1% concentration and 0.25% concentration). For a better understanding and numerical comparison of the shear thinning behavior and apparent viscosity at lower shear rates, flow behavior index n and the consistency coefficient log K (Pa sn) values were derived using a power law model (Table 1). The findings showed that log K values of the milk samples were significantly higher (p < 0.05) and n values were significantly lower (p < 0.05) as a function of HA and KC blend concentration (0.1 v/s 0.25%) for each HA:KC ratio (HA:KC ratio: 100:0, 85:15, 70:30, 50:50, 0:100). Moreover, for different ratios of HA:KC at each concentration level (0.1 and 0.25%), the log K values increased, and n values decreased as a function of proportions of KC in the ratio. Moreover, the highest log K values and lowest n values of the KC-control samples at both concentrations (0.1% and 0.25%) indicated that the amount of KC in different ratios (HA:KC) contributed to the increase in log K values and reduction in n values. The n values were highest for the HA-control samples at both concentrations (0.1 and 0.25%) levels. The significant (p < 0.05) reduction in n values was observed as a function of the increase in KC amount in the samples with different ratios of HA:KC (85:15, 70:30, 50:50, and KC-control). The frequency sweep results showed the absence of a gel network formation (G" > G', viscoelastic liquid behavior) for HA-control samples and the presence of a gel network formation (G' > G'', viscoelastic solid behavior) for KC-control samples at both concentrations (0.1 and 0.25%), which can very well explain that for each HA:KC ratio (HA:KC ratio: 100:0, 85:15, 70:30, 50:50, 0:100) the increase in K values and reduction in n values was the function of KC's ability to form gel network as the amount of KC increased in the HA + KC blended sample. Although, a combination of HA + KC showed a synergistic effect in reducing the protein phase separation; however, no synergistic effect was observed in viscosity profile results . 3.5. Water-Holding Capacity The water-holding capacity of the skim milk sample was influenced by the effect of HA + KA concentration as well as the ratios. The water-holding capacity results are displayed in Table 2. The water-holding capacity significantly (p < 0.05) increased as a function of concentration (0.1 v/s 0.25) at each ratio (HA:KC--100:0, 85:15, 70:30, 50:50), except for the KC-control sample. When comparing the HA-control with KC-control samples, the KC-control samples showed a higher water-holding capacity at both concentrations (Table 2). This higher water-holding capability of KC-control samples can be due to their gel formation capabilities at both concentrations, which was absent in the case of HA-control samples. For the samples with 0.1% concentration, the increase in water-holding capacity at different ratios was mainly contributed by the amount of KC, since the KC-control showed the higher water-holding capacity. However, for the samples with 0.25% concentration, the synergistic effect was demonstrated by the combination of HA + KC at all ratios (85:15, 70:30, and 50:50), which was evident by the significantly higher water-holding capacity (88 +- 1.7% at 85:15, 80 +- 0.0% at 70:30, and 62 +- 1.7% at 50:50) as compared to both HA-control (18 +- 1.4%) and KC-control (48 +- 3.8%). One possible explanation for the synergistic effect of HA + KC in retaining higher water could be that, while KC holds water through the gelling mechanism, the HA might be providing a synergistic effect by increasing the water binding (through hydrogen bonding with water molecules) in the serum phase trapped between the gel network. 3.6. Emulsifying Activity and Stability The emulsifying activity and stability results are displayed in Table 3. Emulsion activity and stability were significantly increased as a function of concentration (0.1 v/s 0.25%) at each ratio (HA:KC--100:0, 85:15, 70:30, 50:50, and 0:100). For 0.1% concentration, the blend of HA + KC samples showed significantly higher emulsion activity and stability as compared to both HA-control and KC-control, which indicated the synergistic effect of these ratios over individual HA and KC samples. For the sample with 0.25% concentration, both the emulsifying activity and stability were significantly higher for the HA-control samples including all three blended ratios (85:15, 70:30, and 50:50) as compared to the KC-control sample, which indicated that the higher emulsifying activity and stability in the blended samples were mainly contributed by the HA amounts. When comparing the stand-alone effect of HA v/s KC, for the 0.1% concentration, the HA-control sample showed significantly lower emulsion activity and stability as compared to KC-control which was reversed at 0.25% concentration. Based on these results, it appears that for the product formulation requiring lower concentration (<=0.1%), the use of a combination of HA + KC would yield better emulsion activity and stability. However, in the case of higher concentration (0.25%), HA alone would be able to provide the emulsion activity and stability similar to the combination of HA + KC. Overall, HA would be a great alternative or additional option in the space of hydrocolloids providing the dual benefit of texture and emulsification. The biopolymer such as HA and KC can act as emulsifiers through different modes of action such as forming a complex with the proteins covering the oil droplet surface and thereby creating strong repulsive forces between oil droplets and their gel-forming capabilities slowing down the movement and separation ability of the oil droplets . At 0.1% concentration, the emulsifying action of the KC could be mainly attributed to its complex formation with milk protein (interaction between negatively changed KC and positively charges region of k-casein) located at the milk serum phase and oil interphase . Along with the action of KC and k-casein complex at the oil droplet surface, the viscosity increase in milk samples due to the action of KC would also contribute to KC's ability to improve milk emulsification properties . HA being a negatively charged biopolymer similar to KC, HA's emulsification properties could also be through a similar mechanism of HA and k-casein complex at oil droplet interphase and the viscosity increase in milk samples due to the action of HA. The lower emulsion activity and stability of the HA-control at 0.1% concentration compared to the KC-control sample could be due to the lower viscosity of the HA-control sample. The significantly higher emulsion activity and stability of the samples containing HA + KC blends with different ratios could be due to the combined synergistic effect of the increased viscosity of the serum phase (as a function of HA) trapped within a weak gel network formed by KC, which together will have a higher synergistic effect on slowing down the oil droplet movement and phase separation as compared to HA-control and KC-control samples. For the samples with 0.25% concentration, lower emulsification activity and stability of the KC-control sample as compared to the HA-control sample could be attributed to the reduced KC and k-casein interactions , and hence the emulsification properties of the KC-control sample could be mainly attributed to gel network formation and higher viscosity. The higher emulsification activity and stability of the HA-control and HA + KC blended sample could possibly be attributed to the interaction of HC and k-casein complex (interaction between negatively charged HC and positively charged region of k-casein) at the oil droplets--milk serum interphase in combination with higher viscosity. These synergistic benefits of higher emulsification of HA + KC blend would be of interest to the food manufacturers. 3.7. Foaming Capacity and Stability 3.7.1. Foaming Capacity and Stability of Skim Milk Sample at 65 degC The effect of the milk treated with 0.1% HA + KC concentration and different ratios on the foaming properties was investigated targeting its application in coffee preparation. The most desirable method for coffee preparation requires heating the milk to 65-70 degC to partially denature the proteins to enhance the foam stability and also this temperature is a requirement for dispensing hot beverages . For this purpose, the foaming capacity and stability of the skim milk samples (containing HA + KC) were studied at 65 degC. For this study, only 0.1% concentration was selected as the viscosity at 0.25% concentration was high for a coffee application. The foam capacity and foam stability data are displayed in Table 4. The foam capacity was lowest with the HC-control sample (98.3 +- 1.7%) and highest with the KC-control sample (170 +- 2.9%). For the sample containing different ratios of HA:KC, the foam capacity increased as a function of the increase in KC concentration in the ratio; however, they were still lower than the KC-control sample. This indicated the absence of a synergistic effect between HA and KC in a mixed blend to yield higher foaming compared to the KC-control sample. As for the retention of foam stability, the HA-control sample showed the lowest foam retention (79 +- 1.7% at 0.5 h mark and 59 +- 1.7% at 1 h mark) as compared to the KC-control sample (88 +- 2.9% at 0.5 h mark and 82 +- 2.9% at 1 h mark). The retention of foam (both at 0.5 h and 1 h mark) increased as a function of KC concentration in the blended samples. Overall, the foam retention of the 50:50 blend (HA:KC) was either equivalent (at 0.5 h mark) or better (at 1 h mark) as compared to the KC-control sample. We continued to monitor the foam retention for further time and all the foam subsided after 6 h for all the samples. Based on the results, HA does have a great potential for generating foam and better stability for application in coffee preparations. However, KC has a better performance which could be related to its ability to form a weak gel at a lower concentration. 3.7.2. Foaming Capacity and Stability of Skim Milk Sample at 30 degC The foaming capacity and stability of two different concentrations (0.1% and 0.25%) and different blend ratios of HA:KC (100:0, 85:15, 70:30, 50:50, 0:100) at 30 degC are displayed in Table 5 and Table 6. Overall, foaming capacity and stability were lower at 30 degC as compared to 65 degC, which could be a result of higher viscosity at a lower temperature. Moreover, the samples with 0.25% showed lower foaming capacity but higher foaming retention as compared to 0.1% concentration at 30 degC; again, this could be attributed to the higher viscosities of the sample with 0.25% concentration . The HA-control samples at both concentrations showed lower foaming capacity as compared to the KC-control samples. For the samples with 0.1% concentration, the foam retention was 100% for all the samples at the 0.5 h mark, which decreased with the storage time up to 24 h. At the mark of 24 h storage, the HA-control and blended sample with 85:15 ratio (HA:KC) showed significantly lower foam retention as compared to the KC-control and blended samples with 70:30 and 50:50 ratios. For the samples with 0.25% concentration, the foam retention was 100% for all the samples up to the 1.5 h mark, which declined with the storage time up to 24 h. At the mark of 24 h storage, the HA-control and blended sample with 85:15 ratio (HA:KC) showed significantly (p < 0.05) lower foam retention as compared to the KC-control and blended samples with 70:30 and 50:50 ratios. The KC-control and blended samples with a 50:50 ratio showed the most stable (100%) foam retention over the entire testing period of 24 h. Based on the results it can be concluded that although HA does have a good foaming capacity and stability; however, it was still lower compared to KC, and improved foaming capacity and stability of the HA + KC blended samples (compared to HA-control) were mainly contributed by the KC component in the blend. Considering the gradual increase in the negative image of carrageenan, HA does have the potential of providing an alternate ingredient for foaming applications. In a skim milk environment during high-speed mixing, the milk proteins could diffuse from the serum phase and adsorb on the air-water interface to facilitate the foam formation. Adding negatively charged hydrocolloid (HA and KC) could enhance the flexibility of diffusion and distribution of proteins at the gas-water interface and facilitates the formation of an adsorption layer, which promotes capturing and formation of bubbles . Hydrocolloids (HA and KC) being hydrophilic molecules does not directly participate in the foam formation; however, they could interact with milk protein molecules (interaction between the negatively charged region of hydrocolloid and positively charged region of milk protein) and thereby inducing the conformational changes to the protein molecule which are more favorable to support foam formation . These protein conformation changes caused by KC-protein interaction might be favoring more foam formation as compared to the protein conformation changes caused by HA-protein interaction, which is reflected in the higher foam capacity of the KC-control as compared to HA-control. The progressive increase in foam capacity of the blended sample (HA + KC) as a function of the increase in KC amount could be mainly related to the contribution of KC's protein conformation changes caused by KC-protein interaction favoring progressively increased foam formation. For foam stability, factors such as drainage, coalescence, and disproportionation play a role in thinning of the interfacial film, leading to the breakage and collapse of the foam . From frequency sweep results (G' > G", for KC-control at both 0.1 and 0.25% concentration) the KC's gel network forming ability would slow down the drainage of the serum phase around the foam and thereby contribute to the longer stability . Moreover, in the blended samples, the amount of KC in each blend will proportionally contribute to longer foam stability. Similarly, KC-induced gel in the serum phase could also possibly play a role in minimizing the coalescence and disproportionation and thereby contribute to longer foam stability. 4. Conclusions The combination of HA + KC blends at all three ratios showed a very good synergistic effect in significantly (p < 0.05) reducing the protein phase separation as well as increasing the water-holding capacity as compared to HA and KC when used alone. Similarly, the combination of HA + KC blends showed a synergistic effect in significantly (p < 0.05) higher emulsifying activity and stability for the sample with 0.1% concentration. For the samples with 0.25% concentration, the emulsifying activity and stability were mainly attributed to the higher emulsifying activity and stability of the HA. Heat stability had no noticeable impact when HC-control and KC-control samples were compared with different ratios of HA + KC blends. The rheological (viscosity, K values, and n values) and foaming properties were higher with the KC-control and lowest with the HA-control sample; the increase in these values was mainly related to an increase in the amount of KC in the HA + KC blend ratios. The combination of HA + KC would be very beneficial in different texture-modulating applications with the added benefit of protein stability (lower phase separation), higher water-holding capacity, better emulsification properties, and foaming abilities. It would be interesting to explore the synergistic effect of HA of different molecular weights in combination with other different types of hydrocolloids. Author Contributions S.G.S.: Conceptualization, methodology, formal analysis, writing--original draft. P.S.: Supervision, formal analysis, review and editing, funding acquisition. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy need. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Experimental design. Figure 2 Frequency sweep test. G'--storage modulus and G"--loss modulus as a function skim milk sample treated with 0.1% (HA + KC) concentration and different ratios of HA:KC. (A) HA-control (100:0) G' (^), G" (), HA:KC (85:15) G' () G" (), (B) HA:KC (70:30) G' () G" (*), HA:KC (50:50) G' (*) G" (*), and KC-control (0:100) G' (#) G" (#). To allow better visual clarity of the graph, the error bars (n = 3, for the standard error of the mean) are not shown. Figure 3 Frequency sweep test. Storage modulus (G') and loss modulus (G") as a function skim milk sample treated with 0.25% (HA + KC) concentration and different ratios of HA:KC. (A) HA-control (100:0) G' (^) G" (), HA:KC (85:15), G' (), G" (), (B) HA:KC (70:30) G' () G" (*), HA:KC (50:50) G' (*) G" (*), and KC-control (0:100) G' (#) G" (#). To allow better visual clarity of the graph, the error bars (n = 3, for the standard error of the mean) are not shown. Figure 4 Protein phase separation of skim milk samples treated with different concentrations and ratios of HA + KC blend during storage (5 degC for 48 h). All values in this table are the mean (n = 3) +- the standard error of the mean. a-d completely different superscript letters in a table show significant differences (p < 0.05). Figure 5 HCT at 140 degC of skim milk sample as a function of two different concentrations of 0.1% (#) and 0.25% (#), and different ratios of HA + KC: The error bars represent the standard deviation of the mean for each treatment's triple analysis. Significant differences between (p < 0.05) HCT values on the column bar are shown by completely different superscript letters a-c. Figure 6 Viscosity profile of skim milk samples treated with different concentrations and ratios of HA:KC. (A) 0.1% HA + KC: HA-control (100:0)--(*), HA:KC (85:15)--(), HA:KC (70:30)--(), HA:KC (50:50)--(^), and KC-control--(#). (B) 0.25% HA + KC: HA-control (100:0)--(*), HA:KC (85:15)--(*), HA:KC (70:30)--(), HA:KC (50:50)--(), and KC-control--(#). To allow better visual clarity of the graph, the error bars (n = 3, for the standard error of the mean) are not shown. foods-12-00913-t001_Table 1 Table 1 Power law-derived consistency coefficient (K) and flow behavior index (n) of skim milk samples treated with different concentrations and ratios of HA + KC blend. HA:KC (Ratio) log K(Pa sn) n (-) 0.1% (HA + KC) 0.25% (HA + KC) 0.1% (HA + KC) 0.25% (HA + KC) HA-control (100:0) 0.029 +- 0.00 a,A 0.69 +- 0.07 a,B 0.91 +- 0.00 a,C 0.55 +- 0.02 a,D HA:KC (85:15) 0.093 +- 0.00 a,A 1.81 +- 0.21 a,B 0.77 +- 0.00 b,C 0.46 +- 0.02 b,D HA:KC (70:30) 0.38 +- 0.01 a,A 3.37 +- 0.05 ab,B 0.60 +- 0.00 c,C 0.38 +- 0.00 c,D HA:KC (50:50) 1.13 +- 0.05 b,A 6.11 +- 0.03 b,B 0.48 +- 0.01 d,C 0.31 +- 0.00 d,D KC-control (0:100) 4.01 +- 0.23 c,A 22.0 +- 1.64 c,B 0.33 +- 0.01 e,C 0.18 +- 0.00 e,D HA = Hyaluronic acid; KC = kappa-carrageenan for all figures and tables. All values in this table are the mean of triplicate analyses +- the standard error of the mean. a-e Completely different superscript letters in the column show a significant difference (p < 0.05) between different ratios of HA and KC. Significant differences (p < 0.05) in log K values between 0.1% and 0.25% concentrations of HA and KC are shown by different superscript letters A,B in a row (for log K only). Significant differences (p < 0.05) in n values between 0.1% and 0.25% concentrations of HA and KC are shown by different superscript letters C,D in a row (for n only). foods-12-00913-t002_Table 2 Table 2 Water-holding capacity of skim milk samples treated with different concentrations and ratios of HA + KC blend. % Water-Holding Capacity Concentration (HA + KC) HA-Control (100:0) HA:KC (85:15) HA:KC (70:30) HA:KC (50:50) KC-Control (0:100) 0.1% 10 +- 0 a,A 25 +- 0 b,A 42 +- 1.7 c,A 52 +- 1.7 d,A 47 +- 1.7 cd,A 0.25% 18 +- 1.4 a,B 88 +- 1.7 b,B 80 +- 0 b,B 62 +- 1.7 c,B 48 +- 3.8 d,A All values in this table are the mean of triplicate analyses +- the standard error of the mean. Significant differences (p < 0.05) for the row values are shown by superscript letters a-d and for the column values are shown by superscript letters A,B. foods-12-00913-t003_Table 3 Table 3 Emulsifying properties (emulsifying activity and stability) of skim milk sample treated with different concentrations (0.1 and 0.25% HA + KC) and different ratios of HA + KC blend. % Emulsifying Properties Concentration (HA + KC) Emulsion Test Type HA-Control (100:0) HA:KC (85:15) HA:KC (70:30) HA:KC (50:50) KC-Control (0:100) 0.10% % Emulsion activity 55 +- 1.4 a,A 72.5 +- 1.4 b,c,A 79.2 +- 0.8 c,A 76.7 +- 1.7 c,A 66.7 +- 1.7 b,A % Emulsion stability 50 +- 2.9 a,A 65 +- 0 b,B 75 +- 0 c,B 79.2 +- 2.2 c,A 60 +- 2.9 b,A,B 0.25% % Emulsion activity 95 +- 0 a,B 96.7 +- 0 a,C 95 +- 0 a,C 90 +- 0 b,B 75 +- 0.8 c,B,C % Emulsion stability 87 +- 1.7 a,C 86.7 +- 1.7 a,D 90.8 +- 0.8 a,D 93.3 +- 1.7 a,B 76.7 +- 1.7 b,C All values in this table are the mean of triplicate analyses +- the standard error of the mean. Significant differences (p < 0.05) for the row values are shown by superscript letters a-c and for the column values are shown by superscript letters A-D. foods-12-00913-t004_Table 4 Table 4 Foaming capacity and stability of the skim milk sample at 65 degC treated with 0.1% HA + KC concentration and different ratios of HA + KC blend. % Foam Capacity % Foam Stability (Retention) HA:KC (Ratio) 0 h 0.5 h 1 h 6 h 12 h HA-control (100:0) 98.3 +- 1.7 A 79 +- 1.7 A,a 59 +- 1.7 A,b 54 +- 1.7 A 0 +- 0 A,c HA:KC (85:15) 98.3 +- 1.7 A 79 +- 1.7 A,a 79 +- 1.7 B,a 74 +- 1.7 B 0 +- 0 A,c HA:KC (70:30) 118.3 +- 1.7 B 83 +- 1.7 B,a 75 +- 1.7 C,b 66 +- 1.7 B 0 +- 0 A,c HA:KC (50:50) 146.7 +- 1.7 C 87 +- 1.7 C,a 87 +- 1.7 D,a 52 +- 1.7 B 0 +- 0 A,c KC-control (0:100) 170 +- 2.9 D 88 +- 2.9 D,a 82 +- 2.9 E,a 41 +- 2.9 B 0 +- 0 A,c All values in this table are the mean of triplicate analyses +- the standard error of the mean. Significant differences (p < 0.05) for the row values are shown by superscript letters a-c and for the column values are shown by superscript letters A-E. foods-12-00913-t005_Table 5 Table 5 Foaming capacity and stability of skim milk sample at 30 degC treated with 0.1% HA + KC concentration and different ratios of HA + KC blend. % Foam Capacity % Foaming Stability (Retention) HA:KC (Ratio) 0 h 0.5 h 1 h 1.5 h 2 h 4 h 5 h 6 h 18 h 24 h HA-control (100:0) 68 +- 1.7 a 100 +- 1.7 a 85 +- 1.7 a 85 +- 1.7 a 85 +- 1.7 a 85 +- 1.7 a 85 +- 1.7 a 85 +- 1.7 a 41 +- 1.7 a 36 +- 1.7 a HA:KC (85:15) 78 +- 1.7 b 100 +- 1.7 b 87 +- 1.7 b 87 +- 1.7 b 81 +- 1.7 ab 81 +- 1.7 ab 81 +- 1.7 ab 74 +- 1.7 a 49 +- 1.7 a 49 +- 1.7 a HA:KC (70:30) 80 +- 0 b 100 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b 87 +- 0 b HA:KC (50:50) 92 +- 1.7 c 100 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c KC-control (0:100) 92 +- 1.7 c 100 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c 89 +- 1.7 c All values in this table are the mean of triplicate analyses +- the standard error of the mean. Significant differences (p < 0.05) for the column values are shown by superscript letters a-c. foods-12-00913-t006_Table 6 Table 6 Foaming capacity and stability of skim milk sample at 30 degC treated with 0.25% HA + KC concentration and different ratios of HA + KC blend. % Foam Capacity % Foam Stability HA:KC (Ratio) 0 h 0.5 h 1 h 1.5 h 2 h 4 h 5 h 6 h 18 h 24 h HA-control (100:0) 60 +- 0 a 100 +- 0 a 100 +- 0 a 100 +- 0 a 100 +- 0 a 80 +- 3.3 a 75 +- 1.7 a 63 +- 6.0 a 33 +- 0 a 33 +- 0 a HA:KC (85:15) 60 +- 0 a 100 +- 0 a 100 +- 0 a 100 +- 0 a 100 +- 0 a 97 +- 1.7 b 92 +- 0 c 92 +- 0 b 72 +- 1.7 b 50 +- 0 b HA:KC (70:30) 57 +- 1.7 a 100 +- 1.7 a 100 +- 0 a 100 +- 0 a 95 +- 0 a 88 +- 0 ab 88 +- 0 b 88 +- 0 b 88 +- 0 c 88 +- 0 c HA:KC (50:50) 72 +- 1.7 b 100 +- 0 b 100 +- 0 b 100 +- 0 b 100 +- 0 b 100 +- 0 c 100 +- 0 d 100 +- 0 c 100 +- 0 d 100 +- 0 d KC-control (0:100) 82 +- 1.7 c 100 +- 0 c 100 +- 0 c 100 +- 0 c 100 +- 0 c 100 +- 0 d 100 +- 0 e 100 +- 0 d 100 +- 0 e 100 +- 0 e All values in this table are the mean of triplicate analyses +- the standard error of the mean. 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PMC10000475 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051068 foods-12-01068 Article Whey Protein Isolate-Mesona chinensis Polysaccharide Conjugate: Characterization and Its Applications in O/W Emulsions Yao Meixiang Conceptualization Investigation Data curation Writing - review & editing 12 Qi Xin Conceptualization Methodology Formal analysis Writing - original draft 2* Zhang Jiahui Methodology Validation Investigation 2 Wang Chengyuan Visualization Project administration 12 Xie Jianhua Investigation Writing - original draft Writing - review & editing Supervision Project administration Funding acquisition 3* Kaur Lovedeep Academic Editor 1 Jiangzhong Dietary Therapy Technology Co., Ltd., Jiujiang 332020, China 2 State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China 3 International Institute of Food Innovation, Nanchang University, Nanchang 330200, China * Correspondence: [email protected] (X.Q.); [email protected] (J.X.) 02 3 2023 3 2023 12 5 106812 11 2022 18 1 2023 20 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Mesona chinensis polysaccharide (MCP), a common thickener, stabilizer and gelling agent in food and pharmaceuticals, also has antioxidant, immunomodulatory and hypoglycemic properties. Whey protein isolate (WPI)-MCP conjugate was prepared and used as a stabilizer for O/W emulsion in this study. FT-IR and surface hydrophobicity results showed there could exist interactions between - MCP and -NH3+ in WPI, and hydrogen bonding may be involved in the covalent binding process. The red-shifted peaks in the FT-IR spectra suggested the formation of WPI-MCP conjugate, and MCP may be bound to the hydrophobic area of WPI with decreasing surface hydrophobicity. According to chemical bond measurement, hydrophobic interaction, hydrogen bond and disulfide bond played the main role in the formation process of WPI-MCP conjugate. According to morphological analysis, the O/W emulsion formed by WPI-MCP had a larger size than the emulsion formed by WPI. The conjugation of MCP with WPI improved the apparent viscosity and gel structure of emulsions, which was concentration-dependent. The oxidative stability of the WPI-MCP emulsion was higher than that of the WPI emulsion. However, the protection effect of WPI-MCP emulsion on b-carotene still needs to be further improved. Mesona chinensis polysaccharide whey protein isolate conjugate emulsion This research received no funding. pmc1. Introduction Compared with conventional emulsion, Pickering emulsion has the advantages of enhanced encapsulation capability and resisting coalescence, phase separation, and Ostwald ripening . Therefore, in recent years, Pickering emulsion is often used as carriers for the delivery of bioactive substances, including lutein, curcumin, resveratrol and so on. Generally, Pickering emulsion is stabilized by organic solid particles like protein, phospholipid, polysaccharide, and inorganic solid particles like SiO2 and CaCO3. Food grade organic particles have won people's favor because of their safe, green, effective features . In addition, it is difficult to prepare superior emulsions with a single stabilizer and thus protein-polysaccharide, protein-phospholipid, and protein-protein composite nanoparticles have attracted widespread attention. Xu et al. prepared a WPI-chitosan complex stabilized emulsion for controlled and sustainable release of a-tocopherol. Liu et al. stabilized O/W Pickering emulsion with WPI glycated with glucose, lactose, and maltodextrin. They found that glycation changed the surface hydrophobicity of WPI, improved protein adsorption, and formed a more stable emulsion. Previous studies also showed that polysaccharide improved the performance of protein-based emulsion systems, such as increased encapsulation efficiency (EE), improved redispersibility after drying and bioaccessibility . Therefore, protein-polysaccharide composite nanoparticles are promising stabilizers in emulsions. MCP is an acid heteropolysaccharide extracted from Mesona chinensis Benth , a kind of medicinal and edible plant of the Labiatae family . It is composed of xylose and galacturonic acid . MCP has good rheological properties and gelling behavior, and a great influence on the textural, rheological, and digestibility properties of starch. Some studies suggested that it could be used to prepare starch-based food packaging materials, nanoparticles that deliver bioactive substances, and self-supporting hydrogels with the desired texture and gelling properties . In addition, MCP possesses various bioactivities, including antioxidant effect against DPPH radical and ABTS radical cation, hepatoprotective and immunoregulatory effects . However, study on MCP-based emulsions is scarce. b-carotene, a natural lipophilic compound, is widely found in many fruits and vegetables, such as pawpaw, carrot, sea buckthorn, and smoke stove. Owing to its excellent coloring effect and biocompatibility, b-carotene is allowed to be used as an additive in the food industry (e.g., fruit juice, candies, jam, flavored fermented milk, etc.) for coloring purposes . b-carotene contains eight isoprene structures on the main chain and two b-viologen ring structures at the end , which gives it favorable antioxidant activity. b-carotene is often used to prevent oils from oxidizing and prepare food packaging material as an excellent natural antioxidant . In addition to these in vitro applications, b-carotene can perform many important biological functions in the human body as a vitamin A precursor . b-carotene possesses antioxidation, anti-inflammatory and anti-cancer activities . Furthermore, it can improve intestinal dysfunctions, control defects in vision, modulate atherosclerotic cardiovascular disease, and reduce the symptoms of Alzheimer's disease . However, the unsaturated double bonds in the b-carotene molecule structure cause poor storage stability and thus limits its wide application in the food field . In this study, the MCP was covalently combined with WPI, a kind of protein with good gelation, emulsification, and polysaccharide binding properties, to prepare WPI-MCP conjugate. The WPI-MCP conjugate was characterized by FT-IR, chemical bonds, and surface hydrophobicity measurements. Then, WPI-MCP conjugate was used to prepare O/W emulsion, and its protective effect on b-carotene during storage was investigated. Knowledge obtained from our work will contribute to the development of polysaccharide-protein conjugate stabilized emulsions and provide information for better stability of b-carotene. 2. Materials and Methods 2.1. Materials MCP (35.62% total sugar, 37.14% of uronic acid, 14.33% protein, and the molecular weight was 325 kDa) was extracted according to Lin et al. . WPI was purchased from Hilmar Ingredients Corporation (Hilmar, CA, USA), and b-carotene was obtained from Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). Corn oil was obtained from the local market (Nanchang, China). 1-anilino-8-naphthalensulfonate (ANS) was purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). The water used in this work was ultrapure water. 2.2. Preparation and Characterization of WPI-MCP Conjugate 2.2.1. Preparation MCP and WPI were dissolved in phosphate buffer (PBS) (10 mM, pH 7.0) with magnetic stirring at 25 degC for 120 min respectively. The MCP and WPI stock solutions were placed at 4 degC overnight for hydration. After that, MCP stock solutions were mixed with WPI stock solutions and named WPI (2% WPI, w/v), WPI-MCP0.05 (2% WPI + 0.05% MCP, w/v), WPI-MCP0.1 (2% WPI + 0.1% MCP, w/v), WPI-MCP0.2 (2% WPI + 0.2% MCP, w/v), WPI-MCP0.3 (2% WPI + 0.3% MCP, w/v), respectively, and then heated at 95 degC for 30 min. The mixtures were placed in ice to cool immediately, followed by homogenization at 13,000 r/min for 5 min to prepare the composite particles (WPI-MCP conjugate). 2.2.2. FT-IR Samples were lyophilized using a FreeZone 2.5 freeze dryer (Labconco, Kansas City, MO, USA) and taken at approximately 1:100 with potassium bromide, and the infrared spectra were obtained on a Nicolet 5700 Fourier transform infrared spectrophotometer (Nicolet, Madison, WI, USA) using potassium bromide as a blank background control. The wavelength range was 4000-500 cm-1 with 64 scans and 4 cm-1 resolution. Each sample was measured three times. 2.2.3. Chemical Bonds Measurement The chemical bonds that existed in WPI-MCP conjugate containing 2% WPI and 0.2% MCP (w/v) were evaluated based on Deng's method with slight modification. 0.2% MCP concentration (w/v) was chosen because the WPI-MCP0.2 emulsion had the smallest particle size (not shown in this work). Four solvents were prepared: solvent 1 (S1) was 0.6 M sodium chloride, solvent 2 (S2) was 0.6 M sodium chloride + 1.5 M urea, solvent 3 (S3) was 0.6 M sodium chloride + 8 M urea, and solvent 4 (S4) was 0.6 M sodium chloride + 8 M urea +0.5 M b-mercaptoethanol. 500 mg lyophilized samples were added to 5 mL S1 and then mixed by vortexing for 120 s. The mixtures were placed at 25 degC for 20 min, followed by centrifugation at 10,000x g for 20 min. The precipitates were mixed with 5 mL S2/S3/S4 with the same procedures. The WPI solubility, expressed as the percentage of protein content (obtained by Bradford method) in the supernatant relative to the total protein, in S1, S2, S3, and S4 was used to evaluate the ionic bond, hydrogen bond, hydrophobic interaction, and disulfide bond, respectively. 2.2.4. Surface Hydrophobicity Surface hydrophobicity was determined using Dong's method . ANS working solution was obtained by dissolving ANS in PBS (10 mM, pH 7.0) buffer. The WPI and WPI-MCP systems were diluted with the same PBS to a protein concentration from 0.1 to 0.5 mg/mL at 0.1 mg/mL intervals. Surface hydrophobicity of MCP was obtained at 0.1, 0.2, 0.3, 0.4, and 0.5 mg/mL MCP concentration. The dilution was added to 8 mM ANS solution at a ratio of 200:1, mixed well and placed in the dark for 15 min before the measurement of fluorescence intensity on a microplate reader (Molecular Devices, Sunnyvale, CA, USA). The excitation, emission wavelengths, and slit width were 390, 470, and 10 nm respectively. The initial slope of the fluorescence intensity versus WPI concentration corresponded to the surface hydrophobicity. 2.3. Preparation and Characterization of WPI-MCP Emulsion 2.3.1. Preparation WPI-MCP solutions containing 2% (w/v) WPI and 0%, 0.05%, 0.1%, 0.2%, and 0.3% (w/v) MCP were mixed with corn oil at a ratio of 9:1 (v/v). The mixtures were homogenized with a high-speed shear emulsifier at 13,000 r/min for 5 min, and then the emulsion was obtained by a high-pressure microjet circulating three times at 120 MPa. 2.3.2. Microstructure Analysis The morphology of the Pickering emulsion was characterized by an Olympus CKX53 microscope (Olympus Co., Ltd., Tokyo, Japan). A 10-fold dilution of the emulsion was placed on the slide without a coverslip to avoid deformation of the droplets to observe the microstructure. In addition, a BX 53 fluorescence microscope (Olympus Co., Ltd., Tokyo, Japan) was employed for observing the emulsion interfacial structure. Nile Red (0.1%, w/v) and Nile Blue A dye (0.1%, w/v) were used for staining, which were excited by a 488 nm argon laser and a 633 nm helium-neon (He-Ne) laser, respectively. 2.3.3. Rheological Properties Rheological properties of emulsions were obtained on the DHR-2 rheometer (TA Instruments Inc., New Castle, DE, USA) using a 40 mm diameter parallel plate at a 0.5 mm gap at 25 degC after 12 h of resting. For steady rheological determination, the relationship between apparent viscosity and the shear rate was recorded at the shear rate ranging from 0.1 to 100 s-1. For dynamic viscoelasticity properties, the changes of storage modulus (G') and loss modulus (G'') were recorded at 0.1-10 rad/s frequency range. 2.4. Preparation and Characterization of b-Carotene-Loaded WPI-MCP Emulsion 2.4.1. Preparation b-carotene was dissolved in corn oil at 1 mg/mL under ultrasonic processing for 30 min. The emulsions were prepared according to Section 2.3.1. In the WPI-MCP b-carotene emulsion, the concentration of b-carotene was 0.1 mg/mL, and the WPI-MCP solution containing 0.2% (w/v) MCP was chosen to prepare b-carotene emulsion because the particle size of the emulsion stabilized by WPI-MCP0.2 was the smallest (not shown in this work). Emulsion without MCP as a control group. 2.4.2. Particle Size and Zeta Potential Determinations 100-fold dilution of the emulsion was measured for particle size and zeta potential using a Zetasizer Nano ZS90 particle size analyzer (Malvern Inc., Malvern, UK). The determinations were preformed in triplicate at 25 degC. 2.4.3. EE EE of b-carotene was evaluated according to Zhang's method with adaptations. The b-carotene entrapped within the emulsion was extracted by anhydrous ethanol-n-hexane (1:2, v/v) solution 3 times. The pooled n-hexane phase was measured on a microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 450 nm. The amount of b-carotene in the sample was calculated by the standard curve. EE was obtained by the following equation:(1) EE %=Entrapped b-caroteneTotal mass of input b-carotene 2.4.4. Oxidative Stability Assessment The peroxide value (POV) was analyzed by measuring the content of hydrogen peroxide in the primary lipid of the emulsion based on Yuan's method with slight modification. The emulsion was mixed with isopropanol-isooctane solution (1:2, v/v) at a ratio of 1:5. Then, 200 mL of supernatant were taken after centrifugation at 3500x g for 2 min and mixed with 20 mL 3.94 mol/L thiocyanate and 20 mL of Fe2+, and then fixed to 5 mL with butanol-methanol solution (1:2, v/v). The mixtures were kept away from light for 20 min, followed by a record on a microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 510 nm. The concentration of peroxides was calculated by a standard curve prepared with Fe3+. Thiobarbituric acid reactive substances (TBARS) were analyzed according to Chen's method . Emulsions were mixed with trichloroacetic acid (10%, w/v) and thiobarbituric acid solution (1%, w/v) at a ratio of 3:5:2, followed by heat treatment at 100 degC for 30 min. The emulsions were placed in ice for rapid cooling, followed by centrifugation at 4500 r/min for 20 min. The supernatant was collected and measured on a microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 532 nm. Different concentrations of 1,1,3,3-tetraethoxypropane (0, 1.25, 2.5, 5, 10, 20 mM) were used to calculate the TBARS value. The samples were placed at 45 degC and the POV and TBARS values were analyzed at 0, 7, 14, 21, and 28 days. 2.5. Chemical Stability Analysis The WPI b-carotene emulsion and WPI-MCP b-carotene emulsion were put in centrifuge tubes respectively and then stored at 4 degC and 25 degC away from light. The b-carotene retention, expressed as Ct/C0, where C0 and Ct were the b-carotene content at the 0 and t days storage, respectively, was measured at 0, 7, 14, 21, and 28 days by the same method with Section 2.4.3. 2.6. Statistical Analysis Data were analyzed by one-way analysis of variance (ANOVA) using SPSS 26.0 software (IBM, Chicago, IL, USA) and reported as mean +- SD. There was significant difference when the value of p < 0.05. 3. Results and Discussion 3.1. FT-IR Infrared spectroscopy can be used to study the structure and chemical bonding of compounds . Figure 2a showed the FT-IR spectra of WPI, MCP, and WPI-MCP conjugates at the 4000-500 cm-1 wavenumber range. For MCP, the peaks at 3349 cm-1 and 2936 cm-1 corresponded to the stretching vibrations of O-H and C-H, respectively . 1608 cm-1 could be caused by the carbonyl C = O vibrations in uronic acid. For WPI, the peak at 3292 cm-1 represented the stretching vibrations of O-H. Peaks at 1645 cm-1 (amide I) and 1537 cm-1 (amide II) are attributed to C = O stretching vibrations and C-N stretching vibrations in combination with N-H bending, respectively. After interaction with MCP, the peak of WPI at 3292 cm-1 shifted to 3294 cm-1 and became wider, indicating the binding of MCP with WPI and the intermolecular and/or intramolecular hydrogen bonds in WPI-MCP conjugate increased. Tirgarian et al. also reported that conjugation of soy protein isolate (SPI) and sodium caseinate with polysaccharides including Alyssum homolocarpum seed gum and kappa-carrageenan induced red shift of the peaks of these two proteins in 3200-3500 cm-1. Moreover, the peak in the amide I band at 1645 cm-1 shifted to 1647 cm-1 after conjugation, which may be caused by the interaction between - MCP and -NH3+ from WPI. The peaks at 1537, 1450, and 1394 cm-1 shifted to 1541, 1456, and 1398 cm-1, respectively. Chen et al. showed that conjugation resulted in a red shift, and the stronger the conjugate effect, the stronger the red shift. From the above results, it can be seen that these peaks in amide I, amide II, and 3200-3500 cm-1 underwent varying degrees of redshift, which supported the formation of WPI-MCP conjugate. Additionally, the spectra of WPI-MCP conjugates with different MCP concentrations were similar. 3.2. Surface Hydrophobicity Surface hydrophobicity has been used to predict and evaluate changes in the surface properties of the protein. The hydrophobic groups on the protein surface play a key role in maintaining stable protein conformation . ANS is an effective tool to measure surface hydrophobicity, because ANS can bind to hydrophobic amino acids on the protein surface . As shown in Table 1, the surface hydrophobicity values of WPI and MCP were 29.57 and 3.07, respectively, showing that MCP processed lower surface hydrophobicity, which may be due to the presence of a large number of hydroxy groups in the MCP. After cross-linking of WPI with MCP, WPI surface hydrophobicity significantly decreased with increasing concentration of MCP. The decrease of surface hydrophobicity started to slow down at 0.2% (w/v) MCP concentration. At this point, the value of surface hydrophobicity was reduced by 69.33%. The addition of polysaccharides introduced hydroxyl groups, which could decrease the surface hydrophobicity of the whole system. Another reason could be that MCP may be bound to the hydrophobic area of WPI and thus reduce the binding sites of ANS on WPI. Moreover, the formation of WPI-MCP conjugate with larger molecular weight may increase the steric hindrance preventing ANS adsorption. Hu et al. reported that the surface hydrophobicity of SPI-Pleurotus eryngii polysaccharide conjugates was lower than that of WPI. Huang et al. also found the surface hydrophobicity of WPI decreased after conjugation with genipin-crosslinked alkaline soluble polysaccharides. They thought one of the reasons could be that the larger molecular weight after crosslinking increased steric hindrance for adsorption by ANS. 3.3. Chemical Bonds Measurement The intermolecular force was investigated by breaking the different forces involved in protein-protein and protein-polysaccharide molecules with different solvents. The intermolecular forces that appeared in WPI and WPI-MCP solutions were evaluated in our study. Figure 2b indicated there were fewer ionic bonds in the WPI-MCP system. MCP as acidic polysaccharides had negative charges, and WPI was also negatively charged at pH 7 because its isoelectric point was pH 4.5 . Therefore, it is difficult for WPI and MCP to interact with each other through ionic bonds. In addition, the hydrophobic interaction, hydrogen bond, and disulfide bond increased significantly (p < 0.05) after conjugation with MCP, especially the hydrogen bond. The reason may be that MCP possessed abundant hydroxyl groups, which could promote the formation of hydrogen bonds between hydroxyl groups in MCP and amino and carboxyl groups in WPI. Moreover, heat treatment may cause the WPI conformation to unfold, exposing internal sulfhydryl and hydrophobic groups, which could enhance hydrophobic interaction, and disulfide bond. Therefore, hydrophobic interaction, hydrogen bond and disulfide bond played the main role in the formation process of WPI-MCP conjugate. 3.4. Morphology Figure 3 depicted the microscopic morphology of WPI and WPI-MCP emulsions. WPI was marked in red and the oil phase in green . The oil droplets were encapsulated, and O/W emulsions were formed. The results showed that the WPI-MCP conjugates were surface active and had a tendency to adsorb to the oil-water interface. According to Figure 3b, the diameter of emulsion droplets increased with increased MCP concentration, which may be caused by the thick coating formed by the binding of protein with polysaccharide. The WPI-MCP conjugate formed a dense filling layer on the surface of the spherical oil droplets. This interfacial structure created a physical barrier to flocculation, coalescence, and Ostwald maturation of Pickering emulsion. 3.5. Rheological Property As shown in Figure 4a, the apparent viscosity of WPI-MCP emulsions containing 0%, 0.05%, 0.1%, 0.2%, and 0.3% MCP (w/v) was investigated. The viscosity of the emulsion decreased significantly when the shear rate increased, which indicated the emulsions exhibited shear thinning properties . This phenomenon can be attributed to the gradual disruption of flocculated droplets and the alignment of droplets and polymers with the water flow . When the emulsion was subjected to shear, the originally entangled macromolecules separated, the resistance to flow was reduced, and then the viscosity decreased. Similar phenomena have been previously reported . When the concentration of MCP increased, apparent viscosity also increased. This was because the higher the polysaccharide concentration, the high molecular weight molecules in the emulsion were more likely to collide with each other, resulting in increased flow resistance and viscosity. Jiang et al. suggested that MCP was a thickening agent, and when MCP was cross-linked with WPI, independently moving molecules were restricted, resulting in enhanced apparent viscosity and pseudoplastic properties. The G'and G'' values at 0.1-10 rad/s oscillation frequencies were shown in Figure 4b. It was clear that G' was higher than G'' in the oscillation frequency range for all samples, indicating the elastic gel-like structure formed . Moreover, there was a tendency for G' and G'' to increase with increasing MCP concentration, and similar results were found by Lv et al. in their study of WPI-chitosan emulsion, suggesting the Pickering emulsion gel structure was enhanced. The value of G' increased gradually with increasing particle concentration, but to a lesser extent, indicating that they were essentially covalent "physical" crosslinks. Also, since MCP had higher viscosity at higher concentrations, increasing MCP concentration may also help to enhance the gel structure. 3.6. Size, Zeta Potential and EE of b-Carotene Emulsions As shown in Table 2, the average particle size of the WPI b-carotene emulsion and WPI-MCP b-carotene emulsion were 175.5 +- 2.79 nm and 235 +- 2.03 nm. The larger average size may be due to the ability of the covalently bound WPI-MCP to form a macromolecular stabilization layer around the WPI layer. PDI values (<0.3) implied that the emulsions had a narrow particle size distribution. The WPI b-carotene emulsion showed higher zeta potential than the WPI-MCP b-carotene emulsion. This may be due to the partial adsorption of the anion on the MCP molecule onto the surface of the WPI particles. Conjugation of whey proteins with inulin has also been reported to lose WPI positive charge . The absolute values of zeta potential for both emulsions were greater than 30 mV, indicating that the electrostatic repulsion present between droplets can maintain the emulsion stability and WPI-MCP b-carotene emulsion could be more stable . EE of WPI b-carotene emulsion and WPI-MCP b-carotene emulsion were 86.68 +- 2.45 and 87.18 +- 0.67 respectively, showing that there was no significant difference (p > 0.05). 3.7. Oxidative Stability In Figure 5, the WPI emulsion showed the highest POV and TBARS values during accelerated oxidation, suggesting it had the weakest oxidative stability. The reason may be that oil droplets were heavily accumulated and exposed to air, and the free radicals in the oil were oxidized by contacting with O2 in the air . However, the POV and TBARS values of WPI-MCP emulsion decreased significantly, which may be due to the antioxidant capacity of the hydroxyl structure of MCP. Another reason could be that the covalent binding of MCP with WPI increased the thickness of the interfacial layer and then prevented contact between O2 in the air and free radicals in the oil, thus inhibiting the lipid oxidation reaction. Additionally, it was known from Section 3.5 that the viscosity of the emulsion increased in the presence of MCP, which could inhibit the movement of oxidizing radicals and metal ions, leading to high oxidative stability . Notably, when b-carotene was added to the emulsion, the POV and TBARS values were significantly lower than that of the emulsion without b-carotene, indicating that b-carotene had strong antioxidant properties. There was no significant difference in POV and TBARS values between WPI-MCP b-carotene emulsion and WPI b-carotene emulsion for most of the time (p < 0.05), which could be caused by the strong antioxidant capacity of b-carotene. In the WPI b-carotene emulsion and WPI-MCP b-carotene emulsion systems, it was mainly the b-carotene that acted as an antioxidant. From the above results, it can be seen that small molecule antioxidants, and polysaccharides with antioxidant properties can improve the oxidative stability of emulsions and help to extend the shelf life of emulsions. 3.8. Chemical Stability of b-Carotene Due to the presence of a large number of unsaturated double bonds in b-carotene , it is susceptible to oxidation and trans-isomerization under the action of light, heat, and oxygen. Generally, the degradation of b-carotene leads to the formation of multiplex degradation compounds, including isomers (13-cis-b-carotene, 13,15-di-cis-b-carotene, etc.), epoxides (b-carotene 5,6-epoxide, b-carotene 5,8-epoxide, etc.), apocarotenones, apocarotenals and short-chain cleavage products (b-cyclocitral, b-ionone, ionene, 5,6-epoxi-b-ionone, dihydroactinidiolide, 4-oxo-ionone, etc.) . Therefore, the effects of different temperatures and stabilizer types on the chemical stability of b-carotene emulsions were investigated over a storage time of 28 days. As shown in Table 3, the retention of b-carotene in the samples tended to decrease during storage under all storage conditions. After one week of storage, no major degradation of b-carotene had yet occurred. During the 14 days of storage, there was no significant difference in b-carotene retention between WPI b-carotene emulsion and WPI-MCP b-carotene emulsion stored at 4 degC, while b-carotene retention in WPI-MCP b-carotene emulsion at 25 degC was higher than that in WPI b-carotene emulsion (p < 0.05), indicating WPI-MCP emulsion had better protection effect for b-carotene. After 28 days of storage, b-carotene in emulsion stabilized by WPI at 25 degC, WPI-MCP at 25 degC, WPI at 4 degC, and WPI-MCP at 4degC was 71.8 +- 4.42%, 73.57 +- 3.46%, 78.7 +- 14.03%, and 86.33 +- 6.44% of the initial levels, respectively. B-carotene in WPI-MCP emulsion at 4 degC was significantly higher than that at 25 degC, indicating b-carotene was sensitive to the temperature. Moreover, there was no significant difference in b-carotene retention between WPI b-carotene emulsion and WPI-MCP b-carotene emulsion when stored at the same temperature for 28 days, while WPI-MCP b-carotene emulsion had a larger average value. These results indicated that storage temperature was an important factor in determining the stability of b-carotene. Compared to WPI emulsion, WPI-MCP emulsion had more potential to improve b-carotene stability, but the protection effect still needed to be improved. 4. Conclusions In this work, the WPI-MCP conjugates with lower surface hydrophobicity than WPI were prepared, and there were hydrophobic interactions, hydrogen bonds, and disulfide bonds in the conjugation process. The WPI and WPI-MCP emulsions were O/W emulsions. The increased MCP concentration led to increased viscosity, enhanced gel structure, and increased size of droplets. The POV and TBARS values of the WPI-MCP emulsion were lower than those of the WPI emulsion, indicating improved oxidative stability. The ability of WPI-MCP emulsion to protect b-carotene from degradation still needs to be improved. This work provided references for the development of emulsion stabilized by protein-polysaccharide conjugate and the theoretical basis for the potential application of WPI-MCP conjugate on anti-lipid oxidant in the emulsion. Author Contributions Conceptualization, M.Y.; Data curation, M.Y.; Formal analysis, X.Q.; Funding acquisition, J.X.; Investigation, J.Z., M.Y., X.Q. and J.X.; Methodology, J.Z. and X.Q.; Project administration, C.W. and J.X.; Supervision, J.X.; Validation, J.Z.; Visualization, C.W.; Writing--original draft, X.Q. and J.X.; Writing--review & editing, M.Y. and J.X. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Data is contained within the article. Conflicts of Interest Author Meixiang Yao and Chengyuan Wang were employed by Jiangzhong Dietary Therapy Technology Co., Ltd.(Jiujiang, China). Author Meixiang Yao contributed to the paper as a researcher in the Jiangzhong Dietary Therapy Technology Co., Ltd. (Jiujiang, China) for conceptualization, data curation, investigation and writing--review & editing. Author Chengyuan Wang contributed to the paper as a researcher in Jiangzhong Dietary Therapy Technology Co., Ltd. (Jiujiang, China) for project administration and visualization. However, the Jiangzhong Dietary Therapy Technology Co., Ltd. (Jiujiang, China) did not contribute neither financially, nor in the optimization, analysis of the results, or writing of the paper. Therefore, there is no conflict of interest in relation with Jiangzhong Dietary Therapy Technology Co., Ltd. (Jiujiang, China). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Figure 1 The chemical structure of b-carotene (a) and appearance of Mesona chinensis Benth (b). (c) Overall experimental plan. Figure 2 (a) FTIR spectra of WPI, MCP and WPI-MCP conjugates. (b) Intermolecular forces, inluding ionic bond (S1), hydrogen bond (S2), hydrophobic interaction (S3), and disulfide bond (S4) in WPI and WPI-MCP systems containing 2% WPI and 0.2% MCP (w/v). Different superscripts represent statistically significantly different (p < 0.05). Figure 3 Typical CLSM (a) and light microscope images (b) of the emulsions stabilized by WPI (2%, w/v) with different concentration of MCP from 0 to 0.3% (w/v). For (a), from left to right were corn oil staining with Nile red, protein staining with Nile blue, and the combined images, respectively. The blue bars in (a) and black bars in (b) represent 25 mm and 20 mm in scale. The red arrows mark emulsion droplets. Figure 4 Apparent viscosity (a) and dynamic rheological properties (b) of WPI, WPI-MCP emulsions. Error bars are +- SD of the means. Figure 5 Changes of POV (a) and TBARS values (b) of different emulsions during 28 days storage. foods-12-01068-t001_Table 1 Table 1 The surface hydrophobicity of WPI, MCP and WPI-MCP conjugates. Sample Surface Hydrophobicity R2 WPI 29.57 +- 0.93 e 0.9925 MCP 3.07 +- 0.03 a 0.9879 WPI-MCP0.05 20.60 +- 0.11 d 0.9914 WPI-MCP0.1 11.68 +- 0.70 c 0.9867 WPI-MCP0.2 9.07 +- 1.05 b 0.9706 WPI-MCP0.3 8.53 +- 0.20 b 0.9890 Note: The data are presented as means +- SD. Different superscripts in same column (a-e) represent statistically significantly different (p < 0.05). foods-12-01068-t002_Table 2 Table 2 The size, PDI, zeta potential and EE of b-carotene emulsions. Emulsifiers Size (nm) PDI Zeta Potential (mV) EE (%) WPI 175.5 +- 2.79 a 0.29 +- 0.02 a -32.93 +- 1.05 b 86.68 +- 2.45 a WPI-MCP 235.0 +- 2.03 b 0.29 +- 0.04 a -37.87 +- 0.95 a 87.18 +- 0.67 a Note: The data are presented as means +- SD. Different superscripts (a-b) in same column represent statistically significantly different (p < 0.05). foods-12-01068-t003_Table 3 Table 3 b-carotene retention rate of emulsions during storage. Systems b-carotene Retention Rate at Different Storage Times (%) 0 Day 7 Day 14 Day 21 Day 28 Day WPI b-carotene emulsion stored at 4 degC 100 a 97.36 +- 0.3 a 90.73 +- 11.98 ab 89.13 +- 12.53 ab 78.7 +- 14.03 ab stored at 25 degC 100 a 98.53 +- 0.51 b 88.1 +- 1.75 a 80.93 +- 3.4 a 71.8 +- 4.42 a WPI-MCP b-carotene emulsion stored at 4 degC 100 a 97.1 +- 0.2 a 96.3 +- 3.96 b 98.03 +- 0.06 b 86.33 +- 6.44 b stored at 25 degC 100 a 98.07 +- 0.75 ab 99 +- 6.05 b 78.8 +- 1.8 a 73.57 +- 3.46 a Note: The data are presented as means +- SD. 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PMC10000476 | Cells Cells cells Cells 2073-4409 MDPI 36899881 10.3390/cells12050745 cells-12-00745 Article Cerebellar Transcriptomic Analysis in a Chronic plus Binge Mouse Model of Alcohol Use Disorder Demonstrates Ethanol-Induced Neuroinflammation and Altered Glial Gene Expression Holloway Kalee N. Formal analysis Investigation Writing - original draft Writing - review & editing Visualization 1 Pinson Marisa R. Formal analysis Investigation Writing - review & editing Visualization 2 Douglas James C. Formal analysis Investigation Writing - original draft Writing - review & editing Visualization 1 Rafferty Tonya M. Investigation Writing - review & editing Visualization 1 Kane Cynthia J. M. Conceptualization Writing - review & editing 1 Miranda Rajesh C. Conceptualization Writing - review & editing Supervision 2 Drew Paul D. Conceptualization Writing - original draft Writing - review & editing Supervision 13* Gruol Donna Academic Editor 1 Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; [email protected] (K.N.H.); [email protected] (J.C.D.); [email protected] (T.M.R.); [email protected] (C.J.M.K.) 2 Department of Neuroscience and Experimental Therapeutics, Texas A&M University School of Medicine, Bryan, TX 77807, USA; [email protected] (M.R.P.); [email protected] (R.C.M.) 3 Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA * Correspondence: [email protected] 25 2 2023 3 2023 12 5 74516 1 2023 21 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Alcohol use disorder (AUD) is one of the most common preventable mental health disorders and can result in pathology within the CNS, including the cerebellum. Cerebellar alcohol exposure during adulthood has been associated with disruptions in proper cerebellar function. However, the mechanisms regulating ethanol-induced cerebellar neuropathology are not well understood. High-throughput next generation sequencing was performed to compare control versus ethanol-treated adult C57BL/6J mice in a chronic plus binge model of AUD. Mice were euthanized, cerebella were microdissected, and RNA was isolated and submitted for RNA-sequencing. Down-stream transcriptomic analyses revealed significant changes in gene expression and global biological pathways in control versus ethanol-treated mice that included pathogen-influenced signaling pathways and cellular immune response pathways. Microglial-associated genes showed a decrease in homeostasis-associated transcripts and an increase in transcripts associated with chronic neurodegenerative diseases, while astrocyte-associated genes showed an increase in transcripts associated with acute injury. Oligodendrocyte lineage cell genes showed a decrease in transcripts associated with both immature progenitors as well as myelinating oligodendrocytes. These data provide new insight into the mechanisms by which ethanol induces cerebellar neuropathology and alterations to the immune response in AUD. AUD astrocyte microglia oligodendrocyte neuroinflammation transcriptomics National Institute on Alcohol Abuse and AlcoholismAA024695 AA026665 AA027111 AA027698 This work was supported by the National Institutes of Health: National Institute on Alcohol Abuse and Alcoholism [Grant/Award Numbers: R01 AA024695 (PDD), R01 AA026665 (PDD), R01 AA027111(PDD), F30 AA027698 (MRP)]. pmc1. Introduction Excessive alcohol consumption in adolescents and adults has significant societal impacts, with an estimated economic cost of $249 billion in the U.S. alone . Studies have shown that alcohol misuse can lead to low academic achievement, an increased risk of suicide, and a lifetime struggle with addiction . Furthermore, alcohol use disorder (AUD) is one of the most prevalent mental health disorders, with 15.7 million Americans aged 12 and older diagnosed , and is associated with many physical and psychiatric comorbidities . Despite the known consequences of excess alcohol consumption, 29.7% of men and 22.2% of women were diagnosed with an AUD in 2019 . AUD is associated with pathology to organ systems including the central nervous system (CNS). Animal models of AUD have been developed which simulate the behavioral abnormalities and neuropathologies associated with human AUD, thus allowing researchers to investigate the biological mechanisms associated with AUD . Within the CNS, the cerebellum is responsible for coordinating motor movements, cognitive processing, and sensory discrimination. In individuals with AUD, these cerebellar functions are often disrupted, which may persist following abstinence from alcohol . Alcohol can induce an immune response in the CNS termed neuroinflammation, which may result in neurodegeneration and an increased risk of developing an AUD . In adult rodents, the extent of alcohol-induced neuroinflammation can depend on the experimental paradigm of ethanol exposure utilized . In the current study, we evaluated the effects of ethanol on the transcriptomic profile of adult mouse cerebella, utilizing a chronic plus binge ethanol exposure paradigm adapted from an alcoholic liver disease model developed by the Gao laboratory, in which liver injury and systemic inflammation were reported . Using a top-down approach, we analyzed the effects of ethanol on global gene expression in the cerebellum. Our studies indicated that ethanol altered the expression of immune-related transcripts and pathways in the adult cerebellum, and may alter the function and phenotype of CNS glial cells. Thus, the current studies aid in advancing our understanding of the neuroinflammatory transcriptomic changes induced in AUD, unraveling potential targets for therapeutic strategies. 2. Materials and Methods 2.1. Animals All animal use protocols were reviewed and approved by the University of Arkansas for Medical Sciences (UAMS), Institutional Animal Care and Use Committee (IACUC). Adult C57BL/6J mice were purchased from The Jackson Laboratory (Bar Harbor, ME, USA; stock #000664) and were housed in the UAMS Division of Laboratory Animal Medicine, where a breeding colony was established to produce experimental animals. Adult male mice aged 10-14 weeks and weighing >=20 g were housed individually and were randomly separated into 2 experimental groups, ethanol (E) or vehicle control (C), (n = 5 mice per group). Solid food was removed from cages, while water was provided ad libitum for the duration of the study. On study days 1-5, both experimental groups of mice were allowed to acclimate to the Bio-Serv Rodent Liquid Diet, control formulation (Flemington, NJ, USA; #F1259SP) provided freely in a fresh tube each day just before the start of the dark cycle. Following acclimation, the ethanol group underwent ethanol ramping, in which mice received successive increases of the Bio-Serv ethanol formulation (#F1258SP) with either 1% (day 6), 2% (day 7), or 3% ethanol (day 8) diluted using 95% v/v ethanol (Acros, a part of Thermo Fisher Scientific, Waltham, MA, USA; #AC615110010). On study day 9, chronic ethanol administration began, in which the ethanol-treated mice received 4% ethanol for 10 days, followed by 5% ethanol for 7 days. Pair-feeding for the control group began on study day 10 (the second day of 4% ethanol administration), in which the control group was fed an equivalent volume of control diet to match the mean ethanol group consumption volume from the previous day. On the morning of study day 26, immediately following the start of the light cycle, the ethanol group underwent an acute binge administration of 5 g/kg of 31.5% ethanol (v/v) diluted from 95% v/v ethanol delivered in water via gavage. The control group received 45% (w/v) Maltose Dextrin (10 DE Food Grade #3585) diluted in water and delivered via gavage. At this time, the liquid diet was removed from all cages and standard food pellets were provided. 24 h following the ethanol binge administration, mice were euthanized and transcardially perfused with 1X PBS containing 5 U/mL heparin. Brains were removed and cerebella were micro-dissected into two halves along the midline and snap frozen in liquid nitrogen. Blood ethanol concentrations (BECs) from a separate set of animals were determined to be 230 (+-59.7) mg/dL following 4% administration, 311.7 (+-49.8) following 5% administration, and 718 (+-6.9) mg/dL following bolus administration, as reported previously when using this model . BECs were not measured at the time of tissue collection, though we suspect BECs were at or near 0 based upon preliminary studies using this model. 2.2. Isolation of RNA, RNA-Seq Library Preparation, and Sequencing One whole cerebellar hemisphere from each experimental animal was homogenized using a B2X24B Bullet Blender and 0.5 mm glass beads, as described by the manufacturer (Next Advance, Troy, NY, USA). RNA was isolated using the RNeasy Lipid Tissue Mini Kit with on-column Dnase digestion using the Rnase-free Dnase Set (Qiagen, Valencia, CA, USA, Cat #74804 and #79254), as described previously . RNA quantity was assessed using the Qubit 3.0 fluorometer with the Qubit Broad-Range RNA Assay Kit (Thermo Fisher Scientific), and an Agilent Fragment Analyzer with the Standard Sensitivity RNA Gel Kit (Agilent Technologies, Santa Clara, CA, USA) was used to ensure RNA quality. RNA-seq libraries were prepared using an Illumina TruSeq mRNA Library Prep Kit with TruSeq Unique Dual Indexed adapters (Illumina, San Diego, CA, USA), and were quantified with Qubit 1X dsDNA High-Sensitivity NGS Gel Kit (Thermo Fisher Scientific). KAPA Library Quantification (Roche, Basel, Switzerland) was used for further library characterization, and an Agilent Fragment Analyzer with the High-sensitivity NGS Gel Kit (Agilent) was used for determining fragment size. Library molarities were calculated followed by dilution and denaturation according to manufacturer's specification for clustering. The control and ethanol-exposed animals were clustered on a high-output NextSeq 500 flow cell and paired-end sequenced with 150-cycle SBS kit for 2X75 reads (Illumina). 2.3. Bioinformatic Analysis To identify significant differences in mRNA gene expression and global biological pathways associated with alterations of cerebellar genes between the control and ethanol treatment groups, raw RNA-sequence data (NCBI GEO accession GSE222445) were analyzed. RNA-seq reads were quality-checked, trimmed, and aligned to the GRCm39 reference genome (accession: GCA_000001635.9) using the Nextflow RNAseq pipeline, nf-core/rnaseq (version 3.4), available at DOI 10.5281/zenodo.1400710. The resulting gene counts were transformed to Log2 counts per million (CPM) . Lowly expressed genes were filtered out, and libraries were normalized by trimmed means of M-values . The Limma R package was used to calculate differential expression among genes . Log2 fold change values were calculated for ethanol compared to control, and genes with an adjusted (adj.) p <= 0.05 were considered statistically significant. Heat map and principal component analysis (PCA) plots were created from the processed differential gene expression data using R statistical software. The R-based EnhancedVolcano package was used to make the volcano plots . Pathway and network analysis were conducted using the QIAGEN Ingenuity Pathway Analysis (IPA) software (QIAGEN Inc., Valencia, CA, USA, accessed on 22 July 2022 ) using the "Core Expression Analysis". IPA analysis parameters were set with the "species" parameter as "mouse", and the "tissues and cell lines" parameter as "cerebellum", with gene cut offs of an adj. p <= 0.05 and Log2 fold change >=0.5 or <=-0.5. To obtain a better understanding of the specific cellular processes and cell types of the cerebellum that are most sensitive to ethanol exposure, we extracted cell type-specific gene lists from publicly available single-cell RNA-seq (scRNA-seq) resources, which have been used previously to deduce the cell composition of bulk RNA-seq tissue . Using this approach, we identified a total of 822 microglia-associated genes from scRNA-seq resources (Supplemental Table S1A). We compared this list of microglia-associated genes to the list of genes significantly differentially regulated by ethanol (adj. p <= 0.05) in our dataset, which identified 151 microglia-associated genes whose expression was altered by ethanol (Table 1). We were able to characterize 23 of the 151 genes as being either homeostatic or neurodegenerative (Table 2), as defined in previous studies (Supplemental Table S1B,C). To further evaluate the effects of ethanol on homeostatic versus neurodegenerative microglial phenotypes, we computed mean z-scores to compare control versus ethanol for the transcripts associated with these phenotypes. Since the goal was to determine relative gene expression changes in our dataset, i.e., to determine whether the genes are down-regulated due to ethanol, the average z-score was computed. We calculated the average z-score across individual genes in our extracted microglia homeostatic and neurodegenerative-associated gene lists, and then averaged these individual gene z-scores within each sample. The average z-score of each sample in the homeostatic and neurodegenerative group was then evaluated using a two-tailed Student's t test, with p <= 0.05 being considered statistically significant. R statistical software was used to conduct the Student's t-test as well as construct the average z-score graphs. Similar to microglia, we utilized scRNA-seq data to compose a list of 309 astrocyte-associated genes (Supplemental Table S2) . From this list we identified 56 astrocyte-associated genes that were differentially expressed in response to ethanol in our current study. We then characterized these transcripts as being associated with an astrocyte phenotype common to acute injury, chronic neurodegenerative diseases, or pan-injury (Table 3), the last of which includes genes associated with both acute injury and chronic neurodegenerative disease phenotypes . To test for statistical significance, the average z-scores of each gene in our extracted acute, chronic, and pan-injury astrocyte-associated gene lists were generated, and these individual gene z-scores were then averaged within each sample in a manner consistent with the microglia described above. The Student's t-test and average z-score graphs were constructed using R statistical software. Due to the small number of chronic neurodegenerative disease astrocyte-associated genes (n = 3), no z-score graph was generated for this group. For oligodendrocyte lineage-associated genes, we extracted gene lists for oligodendrocyte precursor cells (OPCs) (381 genes), committed oligodendrocyte precursor cells (COPs) (55 genes), newly formed oligodendrocytes (NFOL) (9 genes), myelin-forming oligodendrocytes (MFOL) (347 genes), and mature oligodendrocytes (MOL) (7 genes) from publicly available scRNA-seq studies (Supplemental Table S3), in a manner consistent with microglia and astrocytes described above, to determine which genes were significantly differentially regulated by ethanol. From these lists, we identified 71 differentially expressed genes associated with OPCs, 12 genes associated with COPs, 2 genes associated with NFOL, 2 genes associated with MOL, and 108 genes associated with MFOL within our significantly differentially regulated dataset (Table 4). We performed statistical analyses in a manner similar to the microglia and astrocytes above. Briefly, the average z-scores of each gene in our OPC, COP, and MFOL-associated gene lists were generated, and the individual gene z-scores were then averaged between each sample. The Student's t-test and average z-score graphs were constructed using R statistical software. Due to the small number of NFOL and MOL-associated genes differentially regulated by ethanol, z-score graphs were not generated for these groups. 3. Results 3.1. Alcohol-Induced Differential Gene Expression in the Cerebellum A principal component analysis (PCA) was performed to provide an overview of the transcriptomic changes that occurred in response to ethanol. PCA analysis demonstrated that gene transcripts correlating and anticorrelating to the first and second principal components could differentiate control animals from those exposed to ethanol. . Hierarchical clustering analysis of significant genes was conducted using Pearson's correlation, while controlling for false discovery rate adj. p <= 0.05 . RNA-seq analysis identified 732 genes that were significantly differentially regulated (adj. p <= 0.05 and log2FC 0.5). Of these 732 genes, 269 were upregulated genes (36.75%) and 463 were downregulated genes (63.25%), . 3.2. Pathway Analysis of the Alcohol-Induced Differentially Regulated Genes IPA analysis was performed to determine the specific pathways altered by ethanol in the cerebella of adult mice. The results of the top canonical pathways altered by ethanol exposure included those related to the generation of precursor metabolites and energy, pathogen-influenced signaling, cellular immune response, degradation/utilization/assimilation, cellular stress and injury, biosynthesis, disease-specific pathways, cardiovascular signaling, nuclear receptor signaling, and ingenuity toxicity list pathways . A description of the pathway names, p-values, and molecules associated with each significantly altered pathway category is shown in Table 5. The top disease and biological function categories altered by ethanol exposure included nervous system development and function, tissue/cell morphology, cell-to-cell signaling and interaction, cell death and survival, cellular compromise, immune cell trafficking, and inflammatory response [-log(p.val) range = 5.5-2.1] . The diseases and biological function annotations that correlate to the diseases and biological functions categories, as shown in Figure 2B, are myelination (p.val = 2.88 x 10-6 ) or demyelination (p.val = 0.0053) of the cerebellum; quantity (p.val = 0.000125) or coupling (p.val = 0.000556) of oligodendrocytes; thickness of myelin sheath (p.val = 0.000556); quantity of cells (p.val = 0.00783); activation of microglia (p.val = 0.00783); permeability of blood-brain barrier (p.val = 0.0236); and astrocytosis of cerebella (p.val = 0.0467), (Table 6). These results suggest that in the cerebellum, ethanol alters biological functions that pertain to alterations in the formation of myelin, along with possible microglia and astrocyte phenotypic changes. 3.3. Alcohol Suppresses Microglia Homeostatic Genes while Increasing the Expression of Microglia Neurodegenerative-Associated Genes Alcohol has been demonstrated to induce neuroinflammation in both humans and rodents which may include microglial activation, characterized by shortening and thickening of processes, along with the secretion of proinflammatory cytokines and chemokines that may contribute to neuropathology . We performed hierarchical clustering analysis on homeostatic and neurodegenerative disease microglia-associated genes that were differentially expressed (adj. p <= 0.05) in response to ethanol . A Student's t-test comparing the average z-scores across all relevant genes indicated that ethanol caused an overall significant downregulation of microglia homeostatic genes (p.val = 3.191 x 10-6) and an overall significant upregulation of microglia genes associated with neurodegenerative diseases (p.val = 7.786 x 10-5) . Collectively, these data suggest that ethanol may alter the microglial phenotype from a homeostatic and protective phenotype to a more activated phenotype observed in neurodegenerative diseases. 3.4. Astrocytes Undergo a Phenotypic Switch following Chronic plus Binge-like Alcohol Exposure Astrocytes are one of the most abundant cell types in the CNS and play a critical role in regulating CNS functions in health and disease by maintaining homeostasis, providing energy to neurons, regulating synapse development and plasticity, modulating blood-brain-barrier integrity, and controlling neurological function and behavior . Similarly to microglia, astrocytes play a role in CNS inflammation , and ethanol has been demonstrated to trigger an immune response in astrocytes . In the current study, we performed hierarchical clustering analysis on acute injury, chronic neurodegenerative, and pan-injury astrocyte-associated genes that were differentially expressed (adj. p <= 0.05) in response to ethanol . A Student's t-test comparing the average z-scores across all relevant genes indicated that ethanol caused an overall significant increase in astrocyte genes related to acute injury (p.val = 7.085 x 10-5) and an almost even number of down-regulated genes (12 up vs. 13 down) pertaining to pan-injury (p.val = 0.6266) . Ethanol only altered the expression of three genes associated with the chronic neurodegenerative disease category (Table 3), thus the effect of ethanol on this small number of genes was not statistically evaluated. These data suggest that alcohol-induced transcriptomic changes in astrocytes are consistent with an acute injury phenotype. 3.5. Oligodendrocyte Lineage Cells Are Depleted upon Chronic plus Binge-like Alcohol Exposure Ethanol has been demonstrated to alter myelination in adult humans and rodents . We performed hierarchical clustering analysis on genes associated with distinct oligodendrocyte lineages (immature and myelinating) whose expression was altered by ethanol . Evaluation of the effects of ethanol on immature oligodendrocyte lineages indicated that ethanol significantly decreased the expression of genes associated with COPs (p.val = 0.0006784) , and that ethanol skewed toward decreasing the expression of genes associated with OPCs (p.val = 0.1702) . For the myelinating oligodendrocyte lineage cells, ethanol significantly decreased the expression of genes associated with MFOLs (p.val = 2.905 x 10-05) . NFOL and MOL groups only contained two differentially expressed genes; therefore, statistical significance was not evaluated for these categories (Table 4). These results suggest that ethanol effects both immature and myelinating oligodendrocyte lineage cells, which could potentially lead to altered myelination. 4. Discussion Pathway analysis indicated that ethanol had significant effects on immune processes in the cerebella of adult mice. In addition, these analyses suggested that ethanol may alter the phenotype and function of glial cells including microglia, astrocytes, and oligodendrocyte lineage cells. We and others have previously demonstrated that ethanol induces neuroinflammation in adult rodents. However, the amount of neuroinflammation varies depending on the ethanol administration paradigm. For example, acute 4-day ethanol exposure did not alter the expression of pro-inflammatory molecules, although microglial activation was observed . Following 10-day ethanol exposure, increased expression of pro-inflammatory molecules was observed, although it was somewhat modest . Chronic ethanol exposure over a period of 3-5 months resulted in more robust neuroinflammation . Using a variation of the same model as the current study, in which gene expression in both male and female mice was evaluated in control, ethanol, and ethanol + pioglitazone experimental groups, we have previously demonstrated robust neuroinflammation following chronic plus binge exposure to ethanol in less than one month . This model is similar to an alcoholic liver disease model used previously by the Gao laboratory, in which they showed systemic inflammation and liver injury . At this point, it is unclear in our studies whether ethanol induces CNS inflammation directly or indirectly through ethanol induced inflammation outside of the CNS. In order to begin to understand the possible mechanisms by which ethanol induces neuroinflammation in this chronic plus binge model of AUD, we have treated a unique set of male mice for the purpose of RNAseq analysis in the current study. We acknowledge that the use of only male mice is a limitation of the current study. Furthermore, some of the pathways identified in the current study only contain 1 or 2 genes, and some genes are represented in multiple pathways. Thus, we have exercised caution to not overinterpret the results. We evaluated the transcriptomic data to identify immune-regulated genes whose expression was most strongly induced by ethanol, which included FOSB, CCL2, CCL7, C5AR1, SPP1, CD68, SOCS3, C3AR1, and KLF4. The most highly upregulated gene is FOSB, which encodes a transcription factor that dimerizes with Jun protein to form AP-1 and plays a critical role in alcohol and drug addiction . Alcohol increases the expression of FOSB in the mesocorticolimbic system, which is believed to contribute to alcohol use disorder . Furthermore, ethanol was demonstrated to alter synaptic plasticity and epigenetic alterations in the FOSB promoter, resulting in increased FOSB expression in the medial prefrontal cortex in wild-type but not TLR4 deficient mice. Since ethanol is believed to activate TLR4, resulting in downstream immune signaling , a role of ethanol-induced neuroinflammation is suggested in these processes. FOSB has also been demonstrated to contribute to excitotoxic microglial activation through regulation of complement C5a receptors in these cells . Interestingly ethanol strongly increased the expression of complement C5AR1 and C3AR1 in our RNA-Seq studies. C5AR1 expression is increased in the liver of patients with alcoholic hepatitis , and is believed to contribute to alcohol-induced inflammation and liver injury . Additionally, ethanol induces the expression of complement receptors including C3AR1 expression in microglia, resulting in altered phagocytosis . We previously demonstrated that ethanol induces the expression of the chemokine CCL2 or MCP-1 following acute ethanol exposure in adult rodents , as well as in animal models of fetal alcohol spectrum disorders (FASD) . It is interesting that in the current study, ethanol induced the expression of CCL2 as well the related chemokine CCL7 or MCP-3 in this chronic plus binge model. It should also be noted that transcriptomic changes were only evaluated at one timepoint, 24 h after the final ethanol exposure. Future studies may wish to evaluate transcriptomic changes at different times following the final ethanol exposure. It is also noteworthy that the other immune-related molecules we identified previously in this model were not indicated in the current study; this may be due to less sensitivity and smaller "n", both of which are limitations that come with RNAseq when compared to quantitative real-time PCR . Microglia are capable of responding to signals, resulting in activation and an altered phenotype. Our IPA analysis indicated that ethanol treatment resulted in microgliosis or microglial activation in the cerebellum. Upon activation, microglia have traditionally been hypothesized to undergo classical activation, resulting in a M1 pro-inflammatory phenotype, or alternative activation, resulting in an M2 anti-inflammatory or protective phenotype . However, more recently it has become clear that microglial phenotypes are complex, and cannot be defined or categorized effectively using this simple binary system . One recent nomenclature to distinguish microglial phenotype focuses on homeostatic versus neurodegenerative disease phenotypes. Under homeostatic conditions, microglia have a homeostatic phenotype, described by playing a role in synaptic plasticity and synaptogenesis, trophic support, chemotaxis and immune cell recruitment, and neurogenesis . During insult to the CNS, microglia commonly lose their homeostatic signature and assume a chronic inflammatory signature . Evaluation of the phenotype of microglia in a variety of neurodegenerative diseases have resulted in the identification of a common neurodegenerative disease-associated microglia phenotype . In the current study, ethanol induced a microglia phenotypic switch in the cerebellum. This phenotypic switch was similar to that observed in neurodegenerative diseases, with a downregulation of homeostatic signature genes and an upregulation of neurodegenerative signature genes. Astrocytes, like microglia, are capable of functioning in the innate immune response in the CNS. Once astrocytes are activated, commonly referred to as astrogliosis/astrocytosis, they produce cytokines and chemokines, nitric oxide, and other reactive oxygen species as part of an inflammatory response , Our IPA analysis indicated that ethanol treatment resulted in "astrocytosis". Astrocytes were classically defined to respond to various stimuli to become reactive A1 astrocytes (neurotoxic or reactive A2 astrocytes) which are protective and neurotrophic . However, as with microglia, this binary system of classifying reactive astrocytes appears inadequate to fully define and distinguish astrocyte phenotypes. More recently, Serrano-Pozo and colleagues performed a meta-analysis of mouse transcriptomic studies which resulted in a nomenclature that classified reactive astrocytes as being consistent with acute injury, chronic neurodegeneration, or pan-injury reactive astrocytes which exhibited characteristics of both acute injury and chronic neurodegenerative phenotypes . In the current study, we determined that ethanol induced changes consistent with an acute injury astrocyte phenotype. Interestingly, LPS was previously shown to trigger an acute injury astrocyte phenotype . ethanol has also been shown to activate TLR4 receptors, suggesting that ethanol-mediated neuroinflammation could occur in response to recruitment of TLR4 during alcohol use/abuse . Therefore, we speculate that in this model of AUD, in the cerebellum, ethanol induces an acute injury astrocytic phenotype through the activation of TLR4, subsequently inducing an immune response. Oligodendrocytes are responsible for forming a myelin sheath around axons of neurons in the CNS, facilitating the efficient propagation of action potentials . OPCs are produced during embryogenesis, and migrate to their functional location wherein they differentiate into mature myelinating oligodendrocytes. Most myelination occurs at later stages of CNS development but can occur throughout life . Ethanol has profound effects on the developing CNS and is believed to significantly contribute to the pathology associated with FASD, at least in part by altering myelination . Ethanol also alters myelination in adults with AUD . Ethanol is highly toxic to oligodendrocyte lineage cells, with OPCs being particularly susceptible . Alcohol exposure is known to disrupt OPC differentiation and survival by decreasing the expression of platelet-derived growth factor receptor a (PDGFRa), a molecule crucial for differentiation of OPCs into mature oligodendrocytes . In the current study, we found that adult chronic plus binge-like alcohol exposure depletes the expression of genes associated with both immature oligodendrocyte precursor cells as well as myelinating oligodendrocytes. Future studies are needed to determine the mechanism by which ethanol effects oligodendrocyte lineage cells and myelination in AUD. 5. Conclusions The current study demonstrates that ethanol alters the transcriptomic profile in the adult cerebellum in a chronic plus binge model of AUD. The pathways altered by ethanol included those involved in immune response. Ethanol caused a shift in the expression of microglial-associated genes, with a decrease in homeostatic and an increase in chronic neurodegenerative-associated transcripts. Ethanol also increased the expression of astrocyte-associated genes common to acute injury. Finally, ethanol decreased the expression of genes associated with immature oligodendrocyte progenitor cells, as well as myelinating oligodendrocytes. These results provide clues about the mechanisms by which ethanol induces neuroinflammation and altered glial function in AUD. Acknowledgments RNA sequencing was performed by the UAMS Genomics Core which is supported by the Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences. Supplementary Materials The following supporting information can be downloaded at: Table S1A. Microglia associated genes [identified in ], Table S1B. Microglia homeostatic genes [identified in and ], Table S1C. Common microglia genes affected during disease states [identified in ], Table S2. Categorized astrocyte associated genes [identified in ], Table S3. Categorized oligodendrocyte associated genes [identified in ]. Click here for additional data file. Author Contributions All authors had access to the data for the study, made substantial contributions to the manuscript, approved the submitted version of the manuscript, and take responsibility for the accuracy and integrity of the data. Conceptualization, P.D.D., C.J.M.K. and R.C.M.; Writing--Original Draft, P.D.D., K.N.H. and J.C.D., Writing--Review and Editing, K.N.H., M.R.P., J.C.D., T.M.R., C.J.M.K., R.C.M. and P.D.D.; Investigation, K.N.H., M.R.P., J.C.D. and T.M.R.; Formal Analysis, K.N.H., M.R.P. and J.C.D.; Visualization, K.N.H., M.R.P., J.C.D. and T.M.R.; Supervision, P.D.D. and R.C.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was conducted according to the guidelines set forth by the University of Arkansas for Medical Sciences (UAMS) Office of Laboratory Animal Welfare and was approved by the UAMS Institutional Animal Care and Use Committee (IACUC), on 19 July 2021 (IACUC Animal Use Protocol (AUP), File #4120). Informed Consent Statement Not applicable. Data Availability Statement The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE222445 accessed on 24 February 2023). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Ethanol-induced differential gene expression in the cerebellum. Principle component analysis (PCA) of genes contributing to variance between ethanol (E) and control (C) in the cerebellum were analyzed using R statistical software (A). A heatmap and hierarchical clustering dendrogram of relative gene expression across samples was constructed using R statistical software for significantly (adjusted p < 0.05) altered genes. Red indicates positive z-scores (upregulation) and blue indicates negative z-scores (downregulation) (B). The R EnhancedVolcano package was utilized to construct a volcano plot displaying fold change versus adjusted p-value of all detected genes in the cerebellum. 732 of 17,791 total identified transcripts displayed an adjusted p < 0.05 and Log2 fold change >=0.5 or <=-0.5, shown in red (C). n = 5 males per treatment group E or C. Figure 2 Top canonical pathways and top diseases and biological functions in the cerebellum altered by ethanol exposure. Qiagen Ingenuity Pathway Analysis (IPA) software was utilized to assess the top canonical pathways (A) and the top diseases and biological functions (B) altered by ethanol exposure using the "cerebellum" selected analysis settings. All analyses were restricted to genes with an adjusted p < 0.05 and Log2 fold change >= 0.5 or <=-0.5. n = 5 males per treatment group E or C. Figure 3 Microglia-associated genes altered by ethanol exposure in the cerebellum. R statistical software was utilized to construct a heatmap and hierarchical clustering dendrogram of relative gene expression across samples for significantly (adjusted p < 0.05) altered and categorized microglia-associated genes as detailed in Methods. Red indicates positive z-scores (upregulation) and blue indicates negative z-scores (downregulation) (A). Individual genes were z-scored across samples, followed by calculation of average z-score for each treatment group which was used for testing statistical significance in R with Student's t-test. Quantification by average z-score of homeostatic microglia-associated genes (B) and neurodegenerative microglia-associated genes (C). n = 5 males per treatment group E or C; *** p < 0.001. Figure 4 Astrocyte-associated genes altered by ethanol exposure in the cerebellum. R statistical software was utilized to construct a heatmap and hierarchical clustering dendrogram of relative gene expression across samples for significantly (adjusted p < 0.05) altered and categorized astrocyte-associated genes, as detailed in Methods. Red indicates positive z-scores (upregulation) and blue indicates negative z-scores (downregulation) (A). Individual genes were z-scored across samples, followed by calculation of the average z-score for each treatment group, which was used for testing statistical significance in R with Student's t-test. Quantification by average z-score of acute injury astrocyte-associated genes (B) and pan-injury astrocyte-associated genes (C). Due to the small number of chronic neurodegenerative injury astrocyte-associated genes, no z-score graph was generated for this group; however, this group is further characterized in Table 3. n = 5 males per treatment group E or C; *** p < 0.001. Figure 5 Alterations in oligodendrocyte lineage-associated genes by ethanol exposure in the cerebellum. R statistical software was utilized to construct a heatmap and hierarchical clustering dendrogram of relative gene expression across samples for significantly (adjusted p < 0.05) altered and categorized oligodendrocyte lineage-associated genes as detailed in Methods: immature oligodendrocyte lineage-associated genes (A) and myelinating oligodendrocyte lineage-associated genes (B) Red indicates positive z-scores (upregulation) and blue indicates negative z-scores (downregulation) (A,B). Individual genes were z-scored across samples, followed by calculation of average z-score for each treatment group, which was used for testing statistical significance in R with Student's t-test. Quantification by average z-score of COP-associated genes (C), OPC-associated genes (D), and MFOL-associated genes in the cerebellum (E). Due to the small number of NFOL and MOL-associated genes, no z-score graph was generated for this group; however, this group is further characterized in Table 4. Abbreviations: OPC, oligodendrocyte precursor cell; COP, committed oligodendrocyte precursor; MFOL, myelin-forming oligodendrocyte; NFOL, newly formed oligodendrocyte; MOL, mature oligodendrocyte. n = 5 males per treatment group E or C; *** p < 0.001. cells-12-00745-t001_Table 1 Table 1 Uncategorized microglia-associated genes dysregulated by ethanol exposure in the cerebellum. Genes were identified by cross-referencing our significantly (adjusted p < 0.05) differentially regulated gene list with the 822 microglia-associated genes extracted from previous studies [identified in ] (Supplemental Table S1A) using R statistical software, which identified 151 genes associated with microglia. Symbol LogFC Adj. p Symbol LogFC Adj. p Symbol LogFC Adj. p Symbol LogFC Adj. p Symbol LogFC Adj. p FOSB 2.81 0.0081 IFRD1 0.65 0.0001 SLC25A5 0.27 0.0010 CMTM6 -0.21 0.0438 PIK3CD -0.50 0.0057 GPX3 2.68 1.77 x 10-9 ZFP36 0.62 0.0027 CCNL1 0.27 0.0035 MKNK1 -0.22 0.0422 CTSS -0.51 0.0005 CCL2 2.44 0.0015 KLF4 0.60 0.0238 FTL1 0.26 0.0021 EDEM2 -0.23 0.0235 PLD4 -0.52 0.0208 CDKN1A 2.31 0.0007 ANXA3 0.58 0.0021 TMSB4X 0.26 0.0037 DOCK10 -0.23 0.0350 KCTD12 -0.53 1.79 x 10-5 FCNA 2.06 0.0028 ARHGDIB 0.54 0.0103 PTBP1 0.23 0.0289 RGS3 -0.23 0.0465 IFI203 -0.54 0.0313 MAFF 1.94 0.0002 IER3 0.50 0.0012 MYLIP 0.23 0.0321 TLN2 -0.24 0.0188 COL27A1 -0.54 0.0433 CCL7 1.81 0.0025 IER2 0.50 0.0318 BRD2 0.23 0.0038 SLC38A6 -0.24 0.0467 HPGDS -0.60 0.0100 C5AR1 1.53 0.0044 PROS1 0.48 0.0116 KLF6 0.23 0.0368 PLXDC2 -0.24 0.0134 UNC93B1 -0.60 0.0014 GM3002 1.40 0.0405 ICAM1 0.46 0.0449 MCL1 0.21 0.0160 RGL2 -0.25 0.0089 TREM2 -0.62 0.0170 MSR1 1.34 0.0221 CFH 0.45 0.0092 PCF11 0.21 0.0071 PPCDC -0.25 0.0401 ITGAM -0.65 0.0010 EVI2B 1.25 0.0051 LAIR1 0.45 0.0055 CLTC 0.21 0.0070 SLC29A3 -0.25 0.0314 CCR5 -0.67 0.0274 LYVE1 1.22 0.0164 DUSP6 0.44 0.0070 CYFIP1 0.20 0.0136 ZFP90 -0.25 0.0257 SELPLG -0.67 0.0003 UCP2 1.20 0.0088 REL 0.44 0.0343 ZCCHC2 0.20 0.0245 SLCO2B1 -0.28 0.0484 DSN1 -0.68 0.0116 CSRNP1 1.10 8.39 x 10-6 RGS2 0.43 0.0281 FMNL1 0.19 0.0425 CAMK1 -0.28 0.0040 IRF7 -0.70 0.0273 APOC1 1.05 0.0009 TSPO 0.42 0.0433 SERINC3 0.19 0.0467 GPR155 -0.28 0.0130 APOBEC1 -0.70 0.0296 SPP1 1.05 0.0315 ZFP36L2 0.41 0.0021 IL16 0.18 0.0149 TLR3 -0.30 0.0436 HK2 -0.77 0.0023 MERTK 1.00 0.0348 CD300A 0.41 0.0117 ARPC2 0.17 0.0203 AKR1B10 -0.30 0.0100 IFI27L2A -0.77 0.0403 F13A1 0.98 0.0109 SAT1 0.41 0.0007 PCNA 0.17 0.0350 UBC -0.31 0.0056 FGD2 -0.83 0.0048 SERPINB8 0.97 0.0282 1700017B05RIK 0.40 0.0163 UBE2J1 0.17 0.0384 AGO4 -0.32 0.0367 LY86 -0.84 0.0002 KLF10 0.95 0.0022 COTL1 0.39 0.0018 ELMO1 0.16 0.0220 APH1C -0.35 0.0282 FCRLS -0.85 0.0032 ATF3 0.94 0.0077 ATF4 0.39 0.0003 SEMA4D -0.16 0.0484 EPB41L2 -0.35 0.0016 HPGD -0.87 0.0004 HSPA1A 0.92 0.0054 SRGN 0.37 0.0237 ASAH1 -0.17 0.0333 LPCAT2 -0.35 0.0344 KLHL6 -0.95 0.0173 ARHGAP27 0.83 0.0001 ISYNA1 0.35 0.0247 B2M -0.17 0.0416 ARHGAP11A -0.37 0.0465 SIGLECH -0.98 0.0005 SOCS3 0.81 0.0258 H3F3B 0.33 0.0072 LY6E -0.19 0.0276 HEXB -0.38 0.0003 OAS2 -0.98 0.0095 GPNMB 0.79 0.0039 PPP1R15A 0.31 0.0263 TPP1 -0.19 0.0097 CSF1R -0.42 0.0020 P2RY12 -1.10 0.0001 PHYHD1 0.78 1.08 x 10-5 ARL4C 0.30 0.0029 SGPL1 -0.20 0.0388 MPEG1 -0.42 0.0088 CD74 -1.18 0.0001 CD68 0.73 0.0096 CCDC9 0.29 0.0047 IL6ST -0.20 0.0219 GPR34 -0.43 0.0433 H2-AA -1.55 0.0029 EGR1 0.72 0.0028 HERPUD1 0.28 0.0076 PMP22 -0.20 0.0479 CRYL1 -0.44 0.0130 SPARC 0.71 2.21 x 10-8 SKI 0.28 0.0104 RRBP1 -0.20 0.0274 SALL1 -0.45 0.0173 C3AR1 0.69 0.0154 SERPINF1 0.28 0.0375 AXL -0.21 0.0334 RENBP -0.46 0.0219 SH2B2 0.68 0.0052 PTPRJ 0.27 0.0060 COMMD8 -0.21 0.0440 P2RY13 -0.48 0.0356 cells-12-00745-t002_Table 2 Table 2 Categorized microglia-associated genes dysregulated by ethanol exposure in the cerebellum. The microglia-associated genes identified in our data set in Table 1 with an adjusted p < 0.05 and Log2 fold change >= 0.25 or <= -0.25 were further categorized as being homeostatic or neurodegenerative, as defined by previous studies [identified in ]. Homeostatic LogFC Adj. p Neurodegenerative LogFC Adj. p MERTK 1.00 0.0348 GPX3 2.68 1.77 x 10-9 EGR1 0.72 0.0028 CCL2 2.44 0.0015 SLCO2B1 -0.28 0.0484 MSR1 1.34 0.0221 HEXB -0.38 0.0003 SPP1 1.05 0.0315 CSF1R -0.42 0.0020 GPNMB 0.79 0.0039 GPR34 -0.43 0.0433 CD68 0.73 0.0096 SALL1 -0.45 0.0173 LAIR1 0.45 0.0055 P2RY13 -0.48 0.0356 TREM2 -0.62 0.0170 KCTD12 -0.53 1.79 x 10-5 Hpgds -0.60 0.0100 CCR5 -0.67 0.0274 FGD2 -0.83 0.0048 FCRLS -0.85 0.0032 Siglech -0.98 0.0005 P2RY12 -1.10 0.0001 cells-12-00745-t003_Table 3 Table 3 Categorized astrocyte-associated genes dysregulated by ethanol exposure in the cerebellum. Genes were identified by cross-referencing our significantly (adjusted p < 0.05) differentially regulated gene list with the list of 309 astrocyte-associated genes extracted from a previous study [identified in ] (Supplemental Table S2) using R statistical software. The astrocyte-associated genes identified in our dataset were then further categorized as being associated with acute injury, chronic neurodegenerative diseases, or pan-injury, as described in a previous study . Acute Injury LogFC Adj. p Pan Astrocytic LogFC Adj. p Chronic Neurodegenerative Diseases LogFC Adj. p RCAN2 0.40 0.0091 UCP2 1.20 0.0088 S1PR1 -0.33 0.0006 Lrrc58 0.31 0.0036 ATF3 0.94 0.0077 ARSK -0.33 0.0089 ARL4C 0.30 0.0029 GPNMB 0.79 0.0039 COBL -0.47 0.0172 PRELP 0.27 0.0368 LGALS3 0.67 0.0282 YWHAZ 0.26 0.0014 ARHGDIB 0.54 0.0103 DNTTIP2 0.24 0.0244 RHOJ 0.46 0.0117 CDC42SE1 0.23 0.0082 PARP3 0.45 0.0065 HINT1 0.22 0.0040 TIMP3 0.38 0.0216 CARS 0.22 0.0079 AHNAK 0.33 0.0173 IARS 0.21 0.0097 PPARGC1A 0.26 0.0276 ARNTL 0.19 0.0240 ELOVL2 0.25 0.0113 LRRC41 0.19 0.0461 MCL1 0.21 0.0160 SSBP3 0.19 0.0202 AHCYL1 0.16 0.0148 BRCC3 0.19 0.0288 B2M -0.17 0.0416 LRRC59 0.18 0.0391 DST -0.21 0.0280 UBE2F 0.18 0.0219 SQLE -0.27 0.0246 FARSB 0.16 0.0366 APLN -0.28 0.0433 CNBP 0.14 0.0482 PTPRD -0.33 0.0006 SGPL1 -0.20 0.0388 FLOT1 -0.33 0.0116 AXL -0.21 0.0334 NSDHL -0.35 0.0137 LAP3 -0.21 0.0321 HMGCS1 -0.43 0.0002 SGCB -0.21 0.0213 CTSS -0.51 0.0005 RNF141 -0.27 0.0039 VIM -0.51 1.91 x 10-5 SYNE1 -0.30 0.0102 IDI1 -0.55 0.0009 POLD4 -0.34 0.0375 IFIT3 -0.75 0.0360 PLIN2 -0.38 0.0084 IL33 -0.91 0.0001 IGSF1 -0.92 0.0057 cells-12-00745-t004_Table 4 Table 4 Categorized oligodendrocyte lineage-associated genes dysregulated by ethanol exposure in the cerebellum. Genes were identified by cross-referencing our significantly (adjusted p < 0.05) differentially regulated gene list with the list of OPC, COP, NFOL, MFOL and MOL-associated genes [identified in ] (Supplemental Table S3) using R statistical software. OPC LogFC Adj. p OPC LogFC Adj. p OPC LogFC Adj. p OPC LogFC Adj. p PTPRN 1.03 0.0011 GNG3 0.27 0.0053 PRKCB -0.17 0.0390 LNX1 -0.37 0.0017 SERPINA3N 0.98 0.0120 DSCAM 0.27 0.0173 DNM3 -0.18 0.0334 RSU1 -0.40 0.0007 SMOX 0.90 0.0001 NMNAT2 0.26 0.0130 DISP2 -0.18 0.0349 JAM2 -0.41 0.0006 GPNMB 0.79 0.0039 CXADR 0.25 0.0102 DDAH1 -0.20 0.0476 PHLDB1 -0.42 0.0004 SORCS1 0.60 0.0003 ABHD17B 0.25 0.0113 PCDH9 -0.22 0.0174 LBH -0.44 0.0002 MIDN 0.42 0.0088 SCG5 0.25 0.0033 PCDH10 -0.23 0.0301 RAMP1 -0.45 0.0003 TRIL 0.39 0.0116 CHPT1 0.24 0.0110 OMG -0.23 0.0191 EDNRB -0.47 0.0027 HIP1 0.35 0.0003 PHACTR3 0.24 0.0278 SLC35F1 -0.24 0.0275 COBL -0.47 0.0172 KANK1 0.33 0.0160 EHD3 0.23 0.0139 SLC22A15 -0.24 0.0188 GLTP -0.48 0.0006 ITGAV 0.33 0.0034 DLGAP1 0.20 0.0124 PCDH17 -0.25 0.0235 GJC3 -0.48 0.0001 CALY 0.32 0.0021 ADORA1 0.20 0.0151 ADCYAP1R1 -0.25 0.0029 PTN -0.52 0.0002 GPT2 0.31 0.0014 ZCCHC24 0.20 0.0245 SVIL -0.26 0.0391 PLXNB3 -0.52 0.0105 CASKIN2 0.31 0.0163 PTPRE 0.20 0.0168 KLHL5 -0.27 0.0075 MMP15 -0.56 0.0239 KCNK3 0.30 0.0130 RAB31 0.19 0.0231 GRIA4 -0.29 0.0018 RCN1 -0.65 0.0103 NCALD 0.30 0.0041 NELL2 0.19 0.0125 SERINC5 -0.30 0.0016 RLBP1 -0.78 0.0021 LRRFIP1 0.29 0.0024 GNPTG 0.18 0.0202 KLHL13 -0.31 0.0113 EMID1 -0.84 0.0013 CAV2 0.28 0.0473 GAD1 0.15 0.0246 CSPG5 -0.34 0.0086 PLLP -1.11 0.0001 SDC3 0.28 0.0411 NOVA1 -0.16 0.0402 GNB4 -0.35 0.0008 COP LogFC Adj. p NFOL LogFC Adj. p TIMP4 0.42 0.0001 H2-AB1 -1.38 0.0007 SEZ6L 0.40 0.0005 SEMA4D -0.16 0.0484 SIRT2 -0.16 0.0479 SLC44A1 -0.18 0.0460 EDIL3 -0.20 0.0247 S100B -0.24 0.0080 BCAS1 -0.28 0.0412 CNP -0.30 0.0066 GPR17 -0.33 0.0116 EPB41L2 -0.35 0.0016 LIMS2 -0.38 0.0468 ENPP6 -0.53 0.0036 MFOL LogFC Adj. p MFOL LogFC Adj. p MFOL LogFC Adj. p MFOL LogFC Adj. p MOL LogFC Adj. p APOD 1.66 0.0001 LAP3 -0.21 0.0321 SEPTIN4 -0.35 0.0005 UGT8A -1.16 0.0020 NINJ2 -1.88 0.0005 HSPA1A 0.92 0.0054 ATP8A1 -0.21 0.0091 ERMN -0.37 0.0346 SERPINB1A -1.28 3.22 x 10-5 KLK6 -1.04 0.0016 ADIPOR2 0.90 0.0018 SCCPDH -0.21 0.0377 MAG -0.39 0.0346 OPALIN -2.33 6.07 x 10-7 GLUL 0.79 0.0010 FGFR2 -0.21 0.0362 QDPR -0.41 0.0029 PIM3 0.64 0.0005 FNBP1 -0.21 0.0116 PHLDB1 -0.42 0.0004 KLF13 0.53 0.0001 CCP110 -0.22 0.0142 MAP6D1 -0.43 0.0002 HAPLN2 0.42 0.0267 DIP2A -0.22 0.0113 CRYAB -0.43 0.0445 TUBB4A 0.41 0.0036 PCDH9 -0.22 0.0174 ABCA8A -0.46 0.0122 FTH1 0.39 0.0054 TPST1 -0.23 0.0279 GNG11 -0.46 0.0049 KNDC1 0.39 0.0335 DOCK10 -0.23 0.0350 NIPA1 -0.47 0.0001 SLC38A2 0.34 0.0003 CNTN2 -0.23 0.0218 GLTP -0.48 0.0006 SLC20A2 0.30 0.0013 TULP4 -0.23 0.0022 GPR37 -0.48 0.0005 CFL2 0.28 0.0040 OMG -0.23 0.0191 GJC3 -0.48 0.0001 ZDHHC20 0.24 0.0249 EPS15 -0.24 0.0189 CAR2 -0.50 0.0010 NUDT4 0.24 0.0047 ARAP2 -0.24 0.0130 PRR5L -0.50 0.0043 LPGAT1 0.21 0.0097 AATK -0.25 0.0321 ANO4 -0.50 0.0010 PAK1 0.21 0.0071 SEMA6D -0.25 0.0062 ARSG -0.52 0.0029 TMOD2 0.20 0.0160 KCNA6 -0.27 0.0047 PLXNB3 -0.52 0.0105 GPX4 0.20 0.0175 GATM -0.27 0.0091 1700047M11RIK -0.53 0.0012 PSAT1 0.19 0.0409 BCAS1 -0.28 0.0412 LPAR1 -0.54 0.0012 PCNP 0.18 0.0231 S1PR5 -0.29 0.0214 TMEM88B -0.56 0.0002 CDC37L1 0.16 0.0424 GRM3 -0.29 0.0346 CMTM5 -0.59 0.0017 ATP6AP2 0.16 0.0309 EPHB1 -0.29 0.0059 FA2H -0.67 0.0004 DENND5A -0.16 0.0239 UNC5B -0.29 0.0226 ASPA -0.67 0.0001 ACOT7 -0.17 0.0496 TMEFF1 -0.30 0.0304 HHIP -0.73 0.0033 MYO6 -0.17 0.0271 SERINC5 -0.30 0.0016 TMEM125 -0.75 0.0102 SLC44A1 -0.18 0.0460 CNP -0.30 0.0066 SOX2OT -0.85 0.0052 SORT1 -0.18 0.0127 TTYH2 -0.31 0.0053 PPP1R14A -0.86 0.0011 DNM3 -0.18 0.0334 TPPP -0.32 0.0026 MOG -0.86 0.0010 ANK3 -0.19 0.0130 TRIM59 -0.33 0.0334 PDLIM2 -0.87 0.0014 YPEL2 -0.20 0.0410 REEP3 -0.33 0.0022 IL33 -0.91 0.0001 EDIL3 -0.20 0.0247 PTPRD -0.33 0.0006 PRR18 -0.91 0.0003 KCNJ10 -0.20 0.0348 PACS2 -0.34 0.0008 PLP1 -1.07 5.01 x 10-7 WNK1 -0.20 0.0039 DPY19L1 -0.34 0.0012 PLLP -1.11 0.0001 DST -0.21 0.0280 TSPAN2 -0.35 0.0008 GJC2 -1.11 0.0043 cells-12-00745-t005_Table 5 Table 5 Tabular descriptions of the top canonical pathway categories, including pathway names, p-values, and indicated molecules. Qiagen Ingenuity Pathway Analysis (IPA) software was utilized to assess the top canonical pathways altered by ethanol exposure using the "cerebellum" selected analysis settings. All analyses were restricted to genes with an adjusted p < 0.05 and Log2 fold change >=0.5 or <=-0.5. Pathway Category Pathway Name p-Value Molecules Generation of precursor metabolites and energy Glycerol-3-phosphate shuttle 0.0469 GPD1 Pathogen-influenced signaling LPS/IL-1 mediated inhibition of RXR function 0.0400 CHST7, GSTM5, IL33, RARA, SMOX, SREBF1 Cellular immune response Granulocyte adhesion and diapedesis 0.0303 C5AR1, IL33, SDC4, SELPLG Degradation/utilization/assimilation Tryptophan degradation X 0.0481 AKR1B10, SMOX Glycerol degradation I 0.0469 GPD1 Dopamine degradation 0.0368 SMOX, Sult1a1 Acetone degradation I (to Methylglyoxal) 0.0268 AKR1B10, CYP51A1 Spermine and spermidine degradation I 0.0237 SMOX Cellular stress and injury Intrinsic prothrombin activation pathway 0.0481 COL5A3, KLK6 GP6 signaling pathway 0.0388 COL16A1, COL27A1, COL5A1, COL5A3 Wound-healing signaling pathway 0.0288 COL16A1, COL27A1, COL5A1, COL5A3, IL33, VIM Coagulation system 0.0181 F3, VWF Osteoarthritis pathway 0.0163 ANXA2, FGFR3, GREM1, HES1, HTRA1, SDC4, SPP1 Apelin liver signaling pathway 0.0059 AGT, COL5A3, EDN1 Pulomary fibrosis idiopathic signaling pathway 0.0015 CCN2, COL16A1, COL27A1, COL5A1, COL5A3, EDN1, EGR1, FGFR3, HES1, LPAR1, VIM Biosynthesis Trans, trans-faresyl diphosphate biosynthesis 0.0469 IDI1 Cholesterol biosynthesis III (via desmosterol) 0.0316 CYP51A1, MSMO1 Glutamine biosynthesis I 0.0237 GLUL Superpathway of citrulline metabolism 0.0223 ASL, PRODH G-linolenate biosynthesis II 0.0181 FADS1, FADS2 Superpathway of geranylgeranyldiphosphate biosynthesis I (via mevalonate) 0.0143 ACAT2, IDI1 Mevalonate pathway I 0.0109 ACAT2, IDI1 Zymosterol biosynthesis 0.0054 CYP51A1, MSMO1 Superpathway of cholesterol biosynthesis 0.0011 ACAT2, CYP51A1, IDI1, MSMO1 Disease-specific pathway Osteoarthritis pathway 0.0163 ANXA2, FGFR3, GREM1, HES1, HTRA1, SDC4, SPP1 Pathogen-induced cytokine storm signaling pathway 0.0111 COL16A1, COL27A1, COL5A1, COL5A3, DHX58, IL33, SOCS3 Hepatic fibrosis/hepatic stellate cell activation 0.0040 AGT, CCN2, COL16A1, COL27A1, COL5A1, COL5A3, EDN1 Pulomary fibrosis idiopathic signaling pathway 0.0015 CCN2, COL16A1, COL27A1, COL5A1, COL5A3, EDN1, EGR1, FGFR3, HES1, LPAR1, VIM Atherosclerosis signaling 0.0005 APOD, COL5A3, F3, IL33, SELPLG, TNFRSF12A Cardiovascular signaling Intrinsic prothrombin activation pathway 0.0481 COL5A3, KLK6 Atherosclerosis signaling 0.0005 APOD, COL5A3, F3, IL33, SELPLG, TNFRSF12A Nuclear receptor signaling LPS/IL-1 mediated inhibition of RXR function 0.0400 CHST7, GSTM5, IL33, RARA, SMOX, SREBF1 LXR/RXR activation 0.0103 AGT, APOD, CYP51A1, IL33, SREBF1 FXR/RXR activation 0.0064 AGT, APOD, IL33, RARA, SREBF1 VDR/RXR activation 0.0002 CDKN1A, HES1, IGFBP1, KLF4, KLK6, SPP1 Ingenuity toxicity list pathways LPS/IL-1 mediated inhibition of RXR function 0.0400 CHST7, GSTM5, IL33, RARA, SMOX, SREBF1 LXR/RXR activation 0.0103 AGT, APOD, CYP51A1, IL33, SREBF1 FXR/RXR activation 0.0064 AGT, APOD, IL33, RARA, SREBF1 Hepatic fibrosis/hepatic stellate cell activation 0.0040 AGT, CCN2, COL16A1, COL27A1, COL5A1, COL5A3, EDN1 VDR/RXR activation 0.0002 CDKN1A, HES1, IGFBP1, KLF4, KLK6, SPP1 cells-12-00745-t006_Table 6 Table 6 Tabular descriptions of the disease and biological function categories, including annotation, p-value, and indicated molecules. Qiagen Ingenuity Pathway Analysis (IPA) software was utilized to assess the top diseases and biological functions altered by ethanol exposure using the "cerebellum" selected analysis settings. All analyses were restricted to genes with an adjusted p < 0.05 and Log2 fold change >= 0.5 or <=-0.5. Categories Disease or Function Annotation p-Value Molecules Nervous system development and function Myelination 2.88 x 10-6 ASPA, FGFR3, GJB6, GJC2, HPGDS Nervous system development and function, tissue Morphology Quantity of oligodendrocytes 0.000125 FGFR3, GJB6, GJC2 Cell-to-cell signaling and interaction Coupling of oligodendrocytes 0.000556 GJB6, GJC2 Cell morphology, cellular assembly and organization, nervous system development and function, tissue morphology Thickness of myelin sheath 0.000556 GJB6, GJC2 Cell-to-cell signaling and interaction Coupling of astrocytes 0.000556 GJB6, GJC2 Cellular assembly and organization Formation of vacuole 0.00164 GJB6, GJC2 Developmental disorder, nervous system development and function, neurological disease, organismal injury and abnormalities Demyelination of cerebellum 0.0053 ASPA, HPGDS Cell death and survival, cellular compromise, neurological disease, organismal injury and abnormalities, tissue morphology Neurodegeneration of axons 0.0053 ASPA, SPTSSB Tissue morphology Quantity of cells 0.00738 ARSG, ASPA, FGFR3, GJB6, GJC2, NRN1 Cell-to-cell signaling and interaction, hematological system development and function, immune cell trafficking, inflammatory response, nervous system development and function Activation of microglia 0.00783 GJB6, GJC2 Nervous system development and function Morphology of nervous system 0.011 ARSG, FA2H, GJB6, GJC2, MERTK, PLP1, RARA, TBATA, UGT8, ZIC4 Nervous system development and function, tissue morphology Morphology of nervous tissue 0.0126 ARSG, FA2H, GJB6, GJC2, PLP1, TBATA, UGT8 Cellular compromise, neurological disease, organismal injury and abnormalities Damage of axons 0.0236 SOCS3 Cell-to-cell signaling and interaction, nervous system development and function Synaptic transmission of Bergmann glia 0.0236 SLC1A6 Embryonic development, nervous system development and function, organ development, organismal development, tissue development Delay in myelination of cerebellum 0.0236 FGFR3 Cardiovascular system development and function, nervous system development and function, organ morphology, tissue morphology Permeability of blood-brain barrier 0.0236 MOG Nervous system development and function, neurological disease, organismal injury and abnormalities Abnormal morphology of nervous system 0.0314 ARSG, FA2H, MERTK, PLP1, RARA, TBATA, UGT8, ZIC4 Cellular assembly and organization, cellular function and maintenance, nervous system development and function, tissue morphology Quantity of dendrites 0.0467 NRN1 Neurological disease, organismal injury and abnormalities, psychological disorders Spongy degeneration of central nervous system of white matter 0.0467 ASPA Neurological disease, organismal injury and abnormalities Astrocytosis of cerebellum 0.0467 HPGDS Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000477 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050917 diagnostics-13-00917 Article E6/E7 mRNA Expression of the Most Prevalent High-Risk HPV Genotypes in Cervical Samples from Serbian Women Nikolic Natasa Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - original draft 1* Basica Branka Validation Formal analysis Investigation Writing - original draft 1 Mandic Aljosa Methodology Investigation Writing - review & editing Supervision 23 Surla Nela Methodology Validation Formal analysis Investigation Data curation 1 Gusman Vera Conceptualization Data curation 14 Medic Deana Data curation 14 Petrovic Tamas Methodology Writing - review & editing 5 Strbac Mirjana Formal analysis Data curation 1 Petrovic Vladimir Conceptualization Writing - original draft Writing - review & editing Supervision 16 Bottari Fabio Academic Editor Iacobone Anna Daniela Academic Editor 1 Institute of Public Health of Vojvodina, 21000 Novi Sad, Serbia 2 Clinic for Oncological Surgery, Oncology Institute of Vojvodina, 21208 Sremska Kamenica, Serbia 3 Department of Gynaecology and Obstetrics, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia 4 Department of Microbiology with Parasitology and Immunology, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia 5 Scientific Veterinary Institute Novi Sad, 21000 Novi Sad, Serbia 6 Department of Epidemiology, Faculty of Medicine, University of Novi Sad, 21000 Novi Sad, Serbia * Correspondence: [email protected] 28 2 2023 3 2023 13 5 91716 12 2022 21 2 2023 22 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Cervical cancer caused by persistent infection with HR HPV genotypes is the second leading cause of death in women aged 15 to 44 in Serbia. The expression of the E6 and E7 HPV oncogenes is considered as a promising biomarker in diagnosing high-grade squamous intraepithelial lesions (HSIL). This study aimed to evaluate HPV mRNA and DNA tests, compare the results according to the severity of the lesions, and assess the predictive potential for the diagnosis of HSIL. Cervical specimens were obtained at the Department of Gynecology, Community Health Centre Novi Sad, Serbia, and the Oncology Institute of Vojvodina, Serbia, during 2017-2021. The 365 samples were collected using the ThinPrep Pap test. The cytology slides were evaluated according to the Bethesda 2014 System. Using a real-time PCR test, HPV DNA was detected and genotyped, while the RT-PCR proved the presence of E6 and E7 mRNA. The most common genotypes in Serbian women are HPV 16, 31, 33, and 51. Oncogenic activity was demonstrated in 67% of HPV-positive women. A comparison of the HPV DNA and mRNA tests to assess the progression of cervical intraepithelial lesions indicated that higher specificity (89.1%) and positive predictive value (69.8-78.7%) were expressed by the E6/E7 mRNA test, while higher sensitivity was recorded when using the HPV DNA test (67.6-88%). The results determine the higher probability of detecting HPV infection by 7% provided by the mRNA test. The detected E6/E7 mRNA HR HPVs have a predictive potential in assessing the diagnosis of HSIL. The oncogenic activity of HPV 16 and age were the risk factors with the strongest predictive values for the development of HSIL. E6 E7 HPV cervical intraepithelial lesion biomarker Serbia This research received no external funding. pmc1. Introduction It is estimated that approximately every fourth malignancy can be linked to an infectious agent, that is, its contribution to various stages of cancer development (reviewed in ). About a third of this contribution is related to the human papillomavirus (HPV) (reviewed in ). Today, significant evidence confirms the association of high-risk (HR) HPV as a carcinogen or promoter in developing malignant diseases in different locations: the cervix, vulva, vagina, penis, anus, and certain head and neck regions. In first place are neoplasias of the lower genital tract, such as cervical cancer . According to estimates by the World Health Organization (WHO), that is, by the International Agency for Research on Cancer (IARC), 604,000 new cases and 342,000 deaths were registered around the world in 2020, which makes cervical cancer the fourth most frequently diagnosed cancer in women . In Serbia, organized cervical cancer screening has been conducted since 2012, using the PAP test, based on the cytomorphological examination of cervical samples. Screening is mandatory for women aged 25 to 69. However, despite organized screening, cervical cancer remains one of the most common cancers among women in Serbia . The incidence of cervical cancer in Serbia is still among the highest and is approximately twice the average in Europe (10.7 to 100,000) . It is necessary to emphasize that data on the HPV prevalence and genotype distribution among women with normal cervical cytology, precancerous cervical lesions, and cervical cancer are missing in the updated IARC Human Papillomavirus and Related Diseases Report for Serbia . HPV vaccination is a crucial prevention tool against HPV infection and HPV-related precancers and cancers . If vaccination against HPV is carried out before initial sexual activities, it is one of the most effective ways to prevent cervical cancer . Still, in Serbia, vaccination against HPV infection is not part of the mandatory national immunization program, but it is recommended for children aged 9 to 19 years . Strong evidence for HPV as a causative aetiology of cancers of various locations was provided by the IARC, which classified HPV according to its potential to cause malignant cell alteration as follows : Group 1 (carcinogenic to humans, HR) includes HPV genotypes: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, and 59; Group 2A (probably carcinogenic) includes HPV genotype 68; Group 2B (potentially carcinogenic) includes HPV genotypes: 26, 53, 66, 67, 70, 73, 82, 30, 34, 69, 85 and 97; Group 3 (low risk, LR) includes HPV genotypes 6 and 11. Persistent HPV infection is the most critical risk factor for the development of cervical cancer, which is confirmed by the presence of HR HPV in over 99% of cervical cancer samples. Concerning the oncogenic potential, infection with a particular HR HPV genotype carries a specific risk for cellular transformation and malignancy (reviewed in ). Namely, one of the most critical determinants of the degree of pathogenicity of different HPV genotypes is the functional differences between their oncoproteins, E6 and E7 . During viral genome integration into the host cell genome, E1 or E2 are usually disrupted . This gene disruption leads to uncontrolled transcription of E6 and E7 genes as the E2 repression on these oncogenes disappears . Their protein products lead to unregulated cell proliferation, differentiation, and loss of the reparative abilities of the host cell, wherefore they are considered the main actors of virus-induced oncogenesis of cervical cancer . Thanks to the use of cervical cancer screening tests, this cancer is classified as one of the most preventable malignancies. The most common test for this purpose is the cytological abnormality test, the Papanicolaou (PAP) test. However, considering the etiological role of HR HPV in developing cervical cancer, DNA tests have been incorporated into the primary screening of developed countries. Still, this test is characterized by high sensitivity and low specificity, which indicates the necessity of improving the test's characteristics concerning specificity . In this context, the results of numerous studies state that using the HR HPV mRNA test as a basic or additional test in primary screening would improve these characteristics . Given the above, this research aimed to determine the oncogenic activity of the most commonly diagnosed HR HPVs in cervical smear samples using the mRNA test and compare the results according to the severity of the cervical intraepithelial lesion. Furthermore, it aimed to examine the clinical characteristics and predictive potential in assessing the diagnosis of high-grade cervical intraepithelial lesions of HPV DNA and mRNA tests. 2. Materials and Methods 2.1. Study Population and Specimen Collection From 2017 to 2021, cervical smears were obtained from a sample of 365 female patients (age 20-74 years) with normal and abnormal results of cervical cytology who were undergoing gynecological exams at the Department of Gynecology, Community Health Centre Novi Sad, Serbia, and the Oncology Institute of Vojvodina, Serbia. All of the women in the study did not receive any prior treatment for cervical dysplasia or cancer, and all were unvaccinated against HPV infection. The samples were collected using the ThinPrep Pap test (Hologic Inc.) according to the manufacturer's instructions and sent for further analyses to the Center of Virology, Institute of Public Health of Vojvodina, Novi Sad, Republic of Serbia. The classification of cytological findings was performed according to the criteria of the Bethesda System 2014. It was categorized into negative for intraepithelial lesion or malignancy (NILM), atypical squamous cells of unknown significance (ASCUS), low-grade squamous intraepithelial lesions (LSIL), and high-grade squamous intraepithelial lesions (HSIL). All of the women enrolled in the study were informed about the research objective and signed an informed written consent form. The study protocol was reviewed and approved by the Medical Ethical Committee of the Institute of Public Health of Vojvodina, Novi Sad, Serbia (approval number: 01-252/3). 2.2. HR HPV Detection and Genotyping The ThinPrep cervical smear samples were stored at 4-8 degC for up to 3 days from the sampling day. The 2 mL of collected samples were transferred to nuclease-free tubes and centrifugated at 8000x g for 5 min. The formed pellet was dissolved in 200 mL of nuclease-free water and used for nucleic acid extraction. According to the manufacturer's instructions, DNA extraction was carried out using the SaMag STD DNA Extraction Kit (Sacace Biotechnologies, Como, Italy). The extracted DNA was eluted in 100 mL elution buffer. The detection and genotyping of 12 HR HPV genotypes (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, and 59), marked as the HPV DNA test, were performed using the High Risk Typing Real-TM Kit (Sacace Biotechnologies, Como, Italy) following manufacturer's instructions. The E7 gene of specific HPV genotypes was amplified using primers and TaqMan probes in the multiplex reaction performed in a total of 13 mL. The b globin gene is used as an internal control. Real-time PCR was performed on the SaCycler-96 (Sacace Biotechnologies, Como, Italy). After the initial activation of the DNA polymerase at 95 degC for 15 min, five cycles of amplification were performed under the following conditions: 95 degC/5 s, 60 degC/20 s, and 72 degC/15 s, and 40 amplifications were performed under the following conditions: 95 degC/5 s, 60 degC/30 s (fluorescence detection), and 72 degC/15 s. The kinetics of the detected fluorescence signals were monitored using the SaCycler-96 software package (Sacace Biotechnologies, Como, Italy). 2.3. E6/E7 mRNA HPV Detection E6/E7 mRNA of the most prevalent HPVs was tested in the cervical samples positive for the most prevalent HR HPVs DNA and HR HPV DNA negative samples. The HR-HPV-negative samples were included in E6/E7 mRNA testing because the study aimed to determine the mRNA test's clinical characteristics by evaluating and comparing it with the HPV DNA test. Total RNA was extracted from the prepared sample using the miRNeasy Mini Kit and QIAcube robotic workstation (Qiagen, Hilden, Germany) following the manufacturer's instructions. The total RNA was eluted in 50 mL ultrapure water free from nucleases. Following the manufacturer's recommendations, potentially present contaminants were removed using the TURBO DNA-free Kit (Invitrogen/ThermoFisher Scientific, Waltham, MA, USA). The routine procedure for removing contaminants using the kit above included the addition of 5 mL of 10x TURBO DNase Buffer and 1 mL of TURBO DNase enzyme into each sample of extracted total RNA, with incubation for 30 min at a temperature of 37 degC. After the action of the enzyme, 5 mL of inactivation reagent (Dnase Inactivation Reagent) was added, with incubation for 5 min, at room temperature and occasional vortexing. After that, centrifugation was performed (90 s, 10,000x g). The supernatant was carefully transferred to a nuclease-free tube. The real-time reverse transcription PCR (RT-PCR) analysis, marked as the HPV mRNA test, was performed using specific primers and TaqMan probes to detect the E6/E7 mRNA of individual HPV genotypes. The sequences for the primers and probes (Table 1) were adopted from Lindh et al. (2007) and purchased from Life Technologies (Carlsbad, CA, USA). The AgPath-ID One-Step RT-PCR Kit (Applied Biosystems, Waltham, MA, USA) was used for the real-time RT-PCR. A separate reaction mixture was prepared for each set of primers and TaqMan probes. The reaction was prepared to a final volume of 25 mL containing: 12.5 mL 2x RT-PCR Buffer, 1 mL of 25x RT-PCR Enzyme Mix, primers to a final concentration of 300 nM, the probe to a final concentration of 200 nM, 1 mL of RNase Inhibitor reagent (Applied Biosystems, Waltham, MA, USA), 5 mL of isolated total RNA, and DEPC-treated nuclease-free water (Invitrogen, Waltham, MA, USA). Real-time PCR was performed on the Applied Biosystems 7500 Real-Time PCR Systems (ThermoFisher Scientific, Waltham, MA, USA). After the reverse transcription reaction at 48 degC for 30 min, the inactivation of reverse transcriptase and the activation of Taq polymerase were performed at 95 degC for 10 min. After that, 45 cycles of PCR amplification were carried out with denaturation at 95 degC for 15 s and annealing and elongation at 58 degC for 1 min. The data were analyzed with the Applied Biosystems Software v2.0.6 (ThermoFisher Scientific, Waltham, MA, USA) and the GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). 2.4. Statistical Analysis All of the statistical analyses were performed using SPSS statistics software Version 21.0 (Chicago, IL, USA). Testing the difference in frequencies of attributive features was performed using the Chi-square (kh2) test of independence and quality of the match. The Student's t-test was used to compare values between the two age groups, a numerical characteristic. A one-way analysis of variance (ANOVA) and the Bonferroni post-hoc test were applied to compare values between three or more data groups. Frequencies were used to present the analysis of the oncogenic activity of multiple HR HPV infections. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and their 95% confidence intervals (CIs) of HR HPVs DNA and E6/E7 mRNA HPVs detection and cytology test were calculated. To quantify the diagnostic capabilities of the selected test and evaluate its significance, the receiver operating characteristics (ROC) curve was used, which enables testing the significance of differences in the discriminating potential of different variables for the same binary outcome. It is based on a graphical presentation of pairs of sensitivity and specificity that can be obtained by estimating the threshold value for all values of discontinuous variables of the sample. Univariate and multivariate logistic regression were used to analyze the connection between two or more features, generating adequate statistical models. Multivariate logistic regression analysis was applied to all of the analyzed factors to construct a predictive model and named the most relevant predictors for the development of HSIL. A p-value of less than 0.05 defined as statistically significance. 3. Results 3.1. Cervical Cytology A total of 365 specimens obtained from women in the north part of the Republic of Serbia (Vojvodina) were classified based on the Bethesda System 2014 into four categories by cytological criteria. 3.2. HR HPV DNA in Cervical Samples The cervical samples were analyzed for 12 HR HPVs, where 246 out of 365 (67.4%) had HPV-DNA-positive results, which indicates that the overall prevalence of HPV in the study population was 67.4%. All of the HPV genotypes covered by the HPV DNA test were identified (n = 274) in the study population (246 HR-HPV-positive cervical samples). The most prevalent HPV genotype is HPV 16 which makes up 38.3% (105/274) of the total HPV-detected genotypes in 42.7% (105/246) of -positive samples. HPV 31 takes second place with 17.2% (47/274) of total HPV-detected genotypes in 19.1% (47/246) of HPV-DNA-positive samples. Equally represented are HPV 33 and HPV 51, each with 8.8% (24/274) of total HPV-detected genotypes in 9.8% (24/246) of HPV-DNA-positive samples . The results show that those HR HPVs make up 73% (200/274) of the detected genotypes, including multiple infections, which determined those cervical samples (n = 172) for further examination of oncogenic activity, according to the study's aim. Multiple HPV infections were found in 15.7%. The most common co-infections were those with HPV 16 and 31, found in 7.6% (13/172) of cases with multiple infections (Table 2). Molecular data were compared with the cytological results and age categories of patients. The distribution of cytological groups was analyzed within the most prevalent HR-HPV-DNA-positive samples (172 cervical samples), including multiple infections. A minority of women, 16.9% (n = 29), had normal results, whereas 83.1% (n = 143) showed different abnormalities. A total of 26.7% (n = 46) of the examined women had ASCUS; in 25.6% (n = 44), LSILs were found, whereas HSILs were detected in 30.8% (n = 53). The mean age of the patients was 36.7 years. Among the specimens, the number of Serbian women who were <=30 years, 31-44 years, and >=45 years old accounted for 36.5% (n = 68), 36.0% (n = 62), and 24.4% (n = 42) of the samples, respectively (Table 3). The distribution of the most frequently detected HPVs concerning cytology is shown in Table 4. The prevalence rates of HR HPV 16 ranged from 44.8% in the group of NILM cytology to 75.5% in the HSIL group. Contrarily, the prevalence of HR HPV 31 is similar in the groups of NILM (37.9%), ASCUS (34.8%), and LSIL (31.8%), while it is lower in the group of HSIL (11.3%). HPV genotypes 33 and 51 are present in all of the cytological groups in less than 21%. The statistically significant difference in the prevalence between the number of positive findings of HPV 16 (kh2 test; p = 0.035) and HPV 31 (kh2 test; p = 0.017) was determined, depending on the degree of severity of the cytological findings, which was not determined for HPV 33 and 51 (kh2 test; p = 0.706, p = 0.790, respectively) (Table 4). A statistically significant difference was found in the number of female patients concerning the cytological findings and the age of the patients (kh2 test; kh2 = 29.500; p = 0.000) (Table 5). The statistically significant difference was determined regarding the cytological findings and the age of the patients, where the female patients diagnosed with HSIL were significantly older compared to the other groups (ANOVA; F = 9.321; p < 0.001). The Bonferroni post-hoc test determined that the female patients with HSIL are statistically significantly older than those with ASCUS (p < 0.001), NILM (p < 0.001), and LSIL (p = 0.012) . Female patients with confirmed HPV 31 are statistically significantly younger (33 years) than the other HR-HPV-DNA-positive patients (t = 2.317; p = 0.022). The average age of the female patients with confirmed HPV DNA 16 was 36.9 years; with HPV DNA 33, it was 34.1 years, while the average age of patients with HPV DNA 51 was 40.5 years. The statistical analyses show that the proportion of HPV 16 positivity maintained at the same level as age. Conversely, the proportion of HPV 31 positivity decreases with age. The detection of HR HPV 33 genotypes decreases with age, while HR HPV 51 increases (Table 5). 3.3. E6/E7 mRNA in Cervical Samples Figure 3 shows the study design with sample processing to analyze the expression of the E6/E7 mRNA of the most prevalent HR HPV in cervical samples from Serbian women. A total of 291 cervical samples, which include HPV 16-, 31-, 51-positive (n = 172) and HR-HPV-negative samples (n = 119), were tested by the HPV mRNA test. The E6/E7 mRNA HPV was detected exclusively in HR-HPV-DNA-positive samples (Table 6). E6 and E7 transcripts of the four most frequent HR HPVs were detected in 57.5% (115/200) of the HR HPV DNA confirmed genotypes. Accordingly, the distribution of E6/E7 mRNA HR HPV 16, 31, 33, and 51 are shown in Table 6. The E6/E7 mRNA HR HPV 16 was the most abundant, which accounted for 25.5% (51/200) of HR HPV genotypes. Next in frequency was the E6/E7 mRNA HR HPV 31 in 16.5% (33/200), while the E6/E7 mRNAs HR HPV 33 and 51 were equally represented in 8% (16/200) and 7.5% (15/200), respectively. Almost every second HPV 16 genotype is oncogenically expressed (48.6%; 51/105), and it was detected in 29.7% (51/172) HPV-DNA-positive samples. The oncogenic activity of HPV 31 was detected in approximately every fifth (19.2%; 33/172) HPV-DNA-positive sample. Regarding the oncogenic activity of the remaining tested genotypes, HPV 33 and HPV 51 were detected in roughly every tenth HPV-DNA-positive sample (Table 6). The results of expressing E6 and E7 HR HPV oncogenes were expressed through the dispersion of the obtained Ct values. The oncogenic activity of HPV 16 is detected by the lowest registered value (Ct = 16) . 3.4. Prevalence of HR HPV Based on E6/E7 mRNA HPV Expression in Different Cytological Groups The expression of the E6 and E7 genes as indicators of the oncogenic activity of HR HPV 16, 31, 33, and 51 was analyzed concerning cytological findings. The oncogenic activity of the tested genotypes increases with the severity of the cervical intraepithelial lesion. A statistically significant difference in E6/E7 mRNA HPV expression among the various cytological groups was observed (kh2 test; kh2 = 108.623; p < 0.001). E6/E7 mRNA HPVs are the most prevalent in patients with HSIL cytological findings (88.9%). In the group of patients with LSIL cytological findings, it was demonstrated in a lower percentage (60%). A two-fold lower prevalence is observed in patients with ASCUS (29.4%). Oncogene activity in women with normal cytological findings is present in 10.9% of samples (Table 7). Subsequently, the E6/E7 mRNA distribution of HR-HPV-DNA-positive samples according to genotype and cytological groups was analyzed. E6/E7 mRNA HR HPV 16 is the most represented in patients with HSIL cytological findings (64.2%), while in the other groups of cytological findings, it was demonstrated in a lower percentage (3.4-22.7%). A statistically significant difference was found in the number of positive findings of E6/E7 mRNA HR HPV 16 concerning the cytological status (kh2 test; kh2 = 46.881; p < 0.001). This result singled out the HR HPV 16 genotype for further analyses. The presence of E6/E7 mRNA HR HPV 31 was the least detected in HSIL (7.5%) compared to other cytological groups (22.7-26.1%). The distribution of the oncogenic activity of the remaining genotypes (HR HPV 33 and 51) is approximately the same across different cytological groups and remains at a low level (2.2-11.4%) (Table 7). The analyses of the oncogenic activity of multiple HR HPV infections are presented by frequencies. The overall oncogenic activity, including both single and multiple HR HPV infections detected using the E6/E7 mRNA HR HPV test, increases with the degree of cervical lesion severity (60-100%). The oncogenic activity detected in single-genotype infections (20.0-85.7%) is higher compared to the oncogenic activity of multiple genotypes (0-40%) (Table 8). 3.5. Prevalence of E6/E7 mRNA HR HPV Expression According to Age The results were categorized according to age categories (<=30, 31-44, >=45 years) to analyze the prevalence of E6/E7 mRNA HPV in the specific age groups. The lowest percent of E6/E7 mRNA HR HPV 16 was detected in the younger group and the highest percent was detected in patients over 44 years. A statistically significant difference was observed in patients with E6/E7 mRNA HR HPV 16 expression (kh2 test; kh2 = 7.331; p = 0.026), wherein individuals with positive E6/E7 mRNA HPV results were older than the others. The detection of E6/E7 mRNA HR HPV 31 and 33 decreases with the increasing age of the patient, while E6/E7 mRNA HR HPV 51 increases (Table 9). 3.6. Comparison of Tests for the Detection of HR HPV Genotypes and Their Oncogenic Activity The comparison of tests for the detection of the most prevalent HR HPV genotypes and their oncogenic activity revealed that the presence of the HR HPV genotypes is higher than the presence of the oncogenic activity of the genotypes in younger women (<=30 years), similar in middle-aged women (31-44 years), and lower in women 45 years and older. The prevalence of oncogenic activity of the HPV genotypes increases with the severity of the cervical intraepithelial lesion. Compared to the prevalence of the examined HR HPV genotypes, the same parameter is lower in women with normal and undefined cytological findings, approximately the same in low-grade lesions, and significantly higher in high-grade lesions . The calculated clinical characteristics of the DNA and E6/E7 mRNA HR HPV tests are shown in Table 10. The sensitivity and NPV of both tests were increased with the severity of the cervical intraepithelial lesion, with the HR HPV DNA test showing a statistically significantly higher level (67.6-98.2%). The specificity of the E6/E7 mRNA HR HPV test (89.1%) is statistically significantly higher than the HR HPV DNA test (75.6%). The PPV of the HR HPV DNA test is approximately the same for all types of cytological findings (60..6%), while for the mRNA HR HPV test, it increases with the degree of the cervical intraepithelial lesion (69..7%) and it is statistically significantly higher (Table 10). To quantify the diagnostic capabilities of the E6/E7 mRNA HPV test and evaluate its significance, an ROC curve was used to assess the assays for detecting HSIL. The area determined by the ROC curve (AUC) of E6/E7 mRNA HR HPV is 0.812 (CI (95%): 0.752-0.871), while the area under the ROC curve formed by the parameters of the HR HPV DNA test is 0.740 (CI (95%): 0.680-0.799) . The relationships between the oncogenic activity of all of the tested HPVs and previously singled out HPV 16 vs. the cytological results were analyzed using Spearman's (r) correlation . There is a statistically significant positive moderate correlation between the presence of HPV 16 oncogenic activity and cytological status (Spearman's correlation; r = 0.494; p < 0.001) . The oncogenic activity of the tested HPV genotypes is associated with a strong statistically significant positive correlation with the degree of cervical intraepithelial lesion severity (Spearman's correlation; r = 0.594; p < 0.001) . Univariate multinomial logistic regression examined the individual factors (the HR HPV DNA 16, the oncogenic activity of all of the tested HR HPVs, the oncogenic activity of the HR HPV 16 genotype, and the age category) that indicated an increased probability of developing HSIL (Supplementary Materials Tables S1-S4). For the influence of HR HPV 16 on the probability of HSIL, a statistically significant predictive value was determined in the NILM and LSIL cytological groups. Patients with the confirmed presence of the HPV 16 genotype through a DNA test have a higher probability of being diagnosed with HSIL than NILM (3.8-fold), while they will have a 2.6-fold higher probability of being diagnosed with HSIL compared to the probability of being diagnosed with LSIL (Supplementary Materials Table S1). The influence of the oncogenic activity of all tested of the HR HPV genotypes (E6/E7 mRNA HR HPVs) on diagnosing high-grade lesions of the cervical epithelium has a statistically significant prediction found in all cytological groups, NILM, ASCUS, and LSIL. If patients have confirmed indicators of oncogenic activity, they will have an almost seven-fold higher probability of being diagnosed with HSIL compared to the probability of being diagnosed with NILM. The same patients have a 19-fold higher probability of being diagnosed with HSIL compared to the probability of detecting ASCUS and a 5-fold higher probability of detecting HSIL compared to LSIL (Supplementary Materials Table S2). E6/E7 mRNA HR HPV 16 is an indicator for diagnosing HSIL, and a statistically significant predictive value was determined for all types of cytological findings, NILM, ASCUS, and LSIL. In a patient with confirmed HPV 16 oncogenic transcripts, the probability of diagnosing HSIL is 50-fold higher than the probability of diagnosing NILM. Patients with a positive result of E6/E7 mRNAs HR HPV 16 are 12-fold more likely to be diagnosed with HSIL compared to the detection of ASCUS, while in patients with the same result, the probability of detection of HSIL is 6-fold higher than the probability of detection of LSIL (Supplementary Materials Table S3). A statistically significant predictive value for the age category was determined in all cytological groups, NILM, ASCUS, and LSIL. The probability of detecting HSIL concerning normal results in HR-HPV-positive patients is 6.3-fold higher if they are >= 45 years of age than women under 30. A similar prediction for the detection of HSIL was shown concerning ASCUS (6.5-fold). Patients from the oldest age category have a 3.4-fold higher probability of detecting HSIL concerning LSIL than the youngest (Supplementary Materials Table S4). The predictive model contains four independent variables: HR HPV DNA 16, E6/E7 mRNA HR HPVs, E6/E7 mRNA HR HPV 16, and age category. The HSIL lesion, as a representative of a high degree of cervical atypia, represented a dependent variable concerning all of the analyzed relevant factors. Multivariate logistic regression analysis was applied to all of the analyzed factors to construct a predictive model and named the most relevant predictors for the development of HSIL (Table 12). Analyzing the mutual influence of the examined relevant factors for diagnosing HSIL compared to the probability of diagnosing a normal cytological finding, the strongest statistically significant predictor was determined to be the oncogenic activity of the HPV 16 genotype. If it is detected, the probability of diagnosing HSIL concerning the probability of diagnosing normal results increases 19-fold (OR = 19.10; CI (95%): 1.54-236.98; p = 0.022). A statistically significant but almost three-fold weaker predictor for the detection of HSIL compared to NILM is the patient belonging to the oldest age category (OR = 6.65; CI (95%): 1.66-26.60; p = 0.007), while female patients from the age category 31-44 years have a slightly lower statistically significant probability (OR = 5.38; CI (95%): 1.36-21.30; p = 0.016) for the detection of the same lesion. The age category was determined as the strongest statistically significant predictor by analyzing the mutual influence of relevant factors for diagnosing HSIL concerning the probability of detecting ASCUS. HR HPV DNA-positive patients belonging to the oldest age category (>=45 years) have an 8.7-fold higher probability of being diagnosed with HSIL compared to the probability of being diagnosed with ASCUS compared to patients belonging to the younger age category (OR = 8.74; CI (95%): 2.15-35.57; p = 0.002). Female patients with the proven oncogenic activity of HPV 16 have a probability of detecting HSIL 6.4-fold higher compared to the probability of being diagnosed with ASCUS (OR = 6.38; CI (95%): 1.22-33.54; p = 0.029). By analyzing the mutual influence of relevant factors for diagnosing HSIL concerning the probability of detection of LSIL, the strongest statistically significant predictor was determined to be the oncogenic activity of HPV 16 (OR = 5.10; CI (95%): 1.09-23.83; p = 0.038), while weaker statistically significant predictability is shown by the patient's belonging to a specific age category. Female patients belonging to the oldest age category (>=45 years) have a 3.7-fold greater probability of detecting an HSIL change compared to the detection of LSIL compared to the younger age category (<=30 years) (OR = 3.72; CI (95 %): 1.16-11.92; p = 0.027) (Table 12). 4. Discussion Persistent infection caused by HR HPV is the leading risk factor for developing cervical intraepithelial lesions and cervical cancer (reviewed in ). Many countries have introduced screening programs based on the cytomorphological examination of cervical samples using the PAP test during the last 60 years to reduce the morbidity and mortality caused by cervical cancer. However, this procedure has shown less than optimal sensitivity (50%) and high intra-individual variability . HPV DNA detection and genotyping provide an efficient screening method and enable risk stratification. However, just proving the presence of the HPV genome in a cervical epithelium does not provide insight into the type of infection. It does not answer whether there is a transient or persistent infection in which the virus is actively multiplying and in which there is a high risk of cancer developing (reviewed in ). It was established that cervical carcinogenesis is strongly associated with the HPV-caused infection in which the transcription of E6 and E7 HR HPV oncogenes occurs, with the consequent increase of their mRNA and protein levels. For this reason, the detection of E6 and E7 mRNA of HR HPVs can serve as a promising biomarker of their persistence and oncogenic activity (reviewed in ), which could enable a better assessment of the progression to high-grade cervical intraepithelial lesions and, in this regard, significantly influence the algorithm for monitoring patients (reviewed in ). In our study, 365 female patient samples from Serbia were tested for the twelve HR HPV genotypes. It should be emphasized that the study has limitations. Used HPV tests are non-validated according to European Guidelines for use in primary screening (Meijer HPV test criteria) or according to the VALidation of HPV GENoyping Tests (VALGENT) protocols . The commercial molecular HPV test was chosen for research according to Serbia's general requirements for molecular diagnostics and the limited research expenses. From the total number of tested samples, 246 (67.4%) samples were positive for at least one of the 12 tested HR genotypes. These results agree with previous studies in the same area and European countries, where a high prevalence of HPV was registered. Studies in Serbia have reported that the presence of HR HPV infections range from 50% to 79% of women . In the countries of our region, such as Croatia, a similar prevalence was shown (59%) and in Bulgaria (61%) , while a slightly lower prevalence was registered in Italy (53%) . Contrarily, a low prevalence of HPV infection was registered in Western and North European countries. Some of them are Great Britain (20.6%), Sweden (9.7%), and the Netherlands (3.8%) . HPV genotype 16 (38%) emerged as the most frequently detected genotype in the study group, in concordance with previous reports . The presence of HPV 16 is more often present (76%) in high-grade lesions compared to lower-grade lesions of the cervical epithelium. Studies on the HPV 16 genotype's prevalence concerning cytological findings confirm these results (reviewed in ). The following frequencies also represented the Alpha-9 genotype, HPV 31 (17%) and HPV 33 (9%). A meta-analysis study on five continents shows that HPV 31 is especially frequent in Europe . The results of this research indicate that the frequency of the HPV 31 genotype statistically significantly decreases with the progression of the intraepithelial lesion. The decreasing trend of the same genotype's presence according to the degree of severity of the cytological lesion, more precisely, a lower prevalence in cancers compared to precancerous lesions, is observed in research from other studies . Like HPV 31, a prevalence decrease of HPV 33 in HSIL compared to normal cytology was also registered in this research. Globally, HPV 33 ranks fourth in frequency and is responsible for 4.2% of all registered cervical cancers . The surprising fact is a markedly high prevalence (9%) of the Alpha-5 genotype HPV 51 in our research. In the context of the causative agents of cervical cancer, HPV 51 is not included in the top ten most frequent HPV genotypes registered worldwide . However, the detection of this genotype within this research, as well as previous studies from our region and certain European countries , places it among the first four most prevalent genotypes detected in precancerous lesions of the cervix. Since HPV vaccines do not protect against all oncogenic HPVs, such as HPV 51, a complete understanding of its oncogenic activity is particularly significant . The remaining tested genotypes (HR HPV 52, 56, 45, 18, 59, 58, 39, and 35) were present in a low percentage which is in concordance with previous reports . Although HPV 18 is considered to be responsible for 15% of invasive cervical cancers, it is essential to note that its prevalence is similar to some studies from neighboring countries ; we found that in our area, HPV 18 was present at a lower percentage. Its frequency (3.6%) was 10-fold lower than that of HPV 16 . The HPV vaccine was introduced in over half of the WHO member countries in 2020 . There is scientific data from numerous countries that have implemented HPV vaccines in their routine immunization programs on decreasing the burden of cervical HPV infections and precancers . According to our data, using the nine-valent vaccine could prevent more than 80% of the cervical precancerous lesions identified in this study. The presence of HR HPVs determined further examination of their oncogenic potential. In our study, the expression of E6/E7 mRNA HR HPV was identified in 67% of the HPV-positive samples (Table 6). The percentage of expression of the E6 and E7 HPV-examined HR HPVs is proportional to the degree of severity of the cervical lesion (Table 7). It can be observed that approximately every tenth HPV-infected woman (11%) with normal cytological findings is infected with an oncogenically expressed HPV. At the same time, in HSIL, this relationship is the opposite. Namely, the absence of indicators of HPV oncogenic activity is detected in approximately every tenth woman with HSIL status (11.1%). An undoubted trend in E6/E7 mRNA HR HPV positivity with increasing cytology severity has been observed in the data of studies conducted in different regions of the world . In agreement with the report of Argyri et al. (2013) and according to the mRNA test, E6/E7 expression was prevalent in 9.1% of women with normal cytology, similar to our study . However, other previously published data indicated the prevalence of those transcripts in a lower proportion of women with normal cytology findings than our study (0%) . In our study, HPV 16 constituted 29.7%, followed by genotype 31 (19.2%), genotype 33 (9.3%), and genotype 51 (8.7%). The results showed that approximately every second HPV 16 genotype is oncogenically expressed (48.6%). Our data agree with the results reported in other studies. Rossi et al. (2017) observed a positivity rate for E6/E7 mRNA HR HPV, ranging from 58% to 77% in HPV-DNA-positive women . A study by Tuney et al. (2017) in Turkey registered 55.6% E6/E7 mRNA HR HPVs, where HPV genotype 16 constituted 57.8% ; similar to that, Bruno et al. (2018) found that the HPV 16 genotype was the most oncogenetically active . As confirmed in this research, it is also stated by several other authors that the transcription product HPV 16 is most often detected, which indicates that the tendency of expression of the essential oncogenes of this genotype is significantly higher compared to the other examined genotypes , which gives it the status of the HPV with the most carcinogenic potential . The oncogenic activity of HPV 31 was detected in approximately every fifth (19.2%) HPV-DNA-positive sample. Contrary to HPV 16, the opposite trend is observed with the degree of cervical lesion severity. It can be assumed that the negative transcriptional status of E6 and E7 oncogenes is more prevalent due to the presence of an episomal form of the virus or an established transcriptional control that enables the spontaneous elimination of infection. Within this research, the results of E6/E7 mRNA HPV 51 detection are approximately the same as those of HPV 33. The distribution of oncogenic activity of these two genotypes is approximately the same across cytological groups and remains at a low level (2.2-11.4%) (Table 7). Other studies have registered different percentage ranges of transcriptional detection of oncogenes of a particular genotype (HPV 33), from its absence to complete expression of 100% . The reason for those differences can be explained by the variations in their number in the total sample . Furthermore, the total oncogenic activity increases with the degree of cervical lesion severity (60-100%). The oncogenic activity of individual genotypes (20-86%) is higher than that of multiple genotypes (0-40%) in the same type of lesion and increases with the degree of its severity (Table 8). These data are supported by the literature. Each of the detected genotypes is considered to have an independent mechanism of action in oncogenesis , which supports the hypothesis that different cells being infected with different viral genotypes rather than their intracellular coexistence is possible . To analyze the oncogenic activity of the four most frequently diagnosed HR HPVs related to the age categories, a statistically significantly higher prevalence of positive E6/E7 mRNA HPV 16 findings was observed in the older age groups (Table 9). In agreement with this result, studies have shown that E6 and E7 mRNA HR HPV detection is significantly higher after 30 years . The same result is supported by population-based cohort studies, which state that the majority of young women have an asymptomatic HPV infection which, thanks to the immune response, acquires transitory status . The growing interest in molecular diagnostics methods has led various authors to compare the characteristics of the HPV DNA test with the mRNA test, evaluating the diagnostic accuracy in identifying high-grade cervical lesions. Our data showed that the specificity (89%) and PPV (70-79%) of the mRNA test are statistically significantly higher, while the same test has a statistically significantly lower sensitivity than the HPV DNA test. These results agree with the statements of different authors, who emphasized slightly lower values of the sensitivity of the mRNA test compared to the sensitivity of the HPV DNA test. At the same time, the specificity is expressed at a higher level (reviewed in ). In contrast, others suggest that the sensitivity is similar and that its application would significantly improve the assay's specificity characteristics . Studies evaluating the reliability of the mRNA assay showed heterogeneous findings (reviewed in ). The meta-analysis results indicated that the obtained sensitivity value ranged from 41% to 95%, while the registered specificity was 42-97% (reviewed in ). The observed difference is explained by the heterogeneous participation of cervical pathology and methodological quality in different studies, which highlights the limitations in the general interpretation of these test characteristics . Although the results are presented broadly, they maintain a unique trend and suggest that the mRNA test over the HPV DNA test improves specificity . By comparing the clinical characteristics of the test, it can be concluded that the detection of E6 and E7 mRNA HR HPV compared to HPV DNA represents a much better marker for more accurate screening of high-grade cellular atypia of the cervix (reviewed in ), which make it an appropriate tool for the secondary screening of cervical cancer . In our study, the results of the ROC curve analysis indicated that the probability of detecting HPV infection with the mRNA test (81%, AUC = 0.812) in patients with high-grade lesions is higher than the possibility of diagnosing them with the HPV DNA test (74%, AUC = 0.740). The obtained results are in line with the other studies emphasizing the potential usefulness of this test. Sun et al. (2021) also found higher AUC values for the mRNA assay compared to the DNA HPV (0.929 vs. 0.833) , while according to Yao et al. (2017), the clinically relevant portion of the AUC of mRNA was 0.721 . According to the previously established degree of influence on diagnosing HSIL, relevant factors were selected in our research. Factors that represent an increased risk for more severe cervical changes were gradually examined (the HPV 16 genotype, the total oncogenic activity of all of the tested HPV genotypes, the HPV 16 oncogenic activity, and the age category of the patient). Firstly, the HPV-DNA-16-positive results have a statistically significant predictive value for diagnosing HSIL (Table S1). In the same context, the study of Bruno et al. (2018) stated that the presence of the HPV 16 genotype was associated with a five-fold higher risk of developing a high-grade lesion compared to women with the presence of another HPV genotype . Similarly, the data from a recent study indicate that type-specific HPV persistence predicted high-grade lesions, with HPV 16 being the most common type . Secondly, the oncogenic activity of all of the tested HR HPVs has a statistically significant predictive value for diagnosing HSIL (Table S2). The obtained results support the statements related to the research on the importance of oncogenic activity, which show that the detection of E6 and E7 mRNA HR HPV could have a prognostic value in monitoring the development of carcinogenesis . The results of the study by Fontecha et al. (2016) showed that in the highest percentage of E6 and E7 mRNA HPV-positive women, the progression of the lesion is diagnosed over time (53%), followed by the persistence of abnormal cytological findings (42%), while regression was recorded in 10-fold lower cases (4%). Furthermore, in patients with positive results of indicators of the oncogenic activity of HPV 16, a statistically significantly higher probability of diagnosing a high-grade lesion was determined in all types of cytological groups (Table S3). According to the previous insights into the published statements, one of the few prospective follow-up studies that dealt with the predictive value of E6 and E7 mRNA HPV 16 indicated that through the detection of this biomarker, it is possible to identify 87.5% of the HPV infections that progressed. In this case, the risk of progression of negative cytology and low-grade cervical lesions was 10-fold higher than that detected in mRNA-negative women during a follow-up period of 35 months . This is supported by the results of Johansson et al. (2015), which indicated that the absence of E6/E7 mRNA HPV demonstrated a high negative predictive value for the future development of high-grade lesions of the cervix among HR-HPV-DNA-positive women with ASCUS and LSIL . Within the results of this research, a statistically significant final model with all of the predictors was constructed, which shows the strength of the potential of the examined factors, that is, biomarkers for diagnosing precancerous lesions in women with HR HPV infection. Looking at each cytological group individually, two independent variables made a statistically significant contribution to the model and were thus named as the strongest predictors. These are the oncogenic activities of HR HPV 16 and the age category (>=45 years). It is known that the presence of HPV infection is confirmed in all age categories. However, belonging to a particular age group is a determinant significantly associated with the risk of acquiring this infection, depicting the peak in prevalence, which generally takes place around 20-25 years of age. For lesions to progress to more severe forms of cervical disease, a period of 5-14 years is necessary, during which the infection persists and the process of oncogenesis takes place ; the results of this research confirm the stated findings. In the examined women, the age category (>=45 years) is a statistically significant prognostic factor for diagnosing HSIL in all of the cytological groups (Table 12 and Table S4). Loopik et al. (2020) indicated that the risk of progression of an existing high-grade lesion increases with age, i.e., in women over 50, the risk of developing cervical cancer increases by seven fold. In addition, the risk of developing cervical abnormalities and the need to use an mRNA test in the diagnostic protocol of HPV-DNA-positive postmenopausal women with normal cytology is emphasized by Asciutto et al. (2020) . 5. Conclusions In summary, this study describes the detection rates of the most common HR HPVs (16, 31, 33, and 51) and E6/E7 mRNA HR HPV expression in 365 Serbian women who showed normal and abnormal cytological findings. Those HR HPV genotypes are oncogenically active in more than half of the examined cases, and the detected oncogenic activity has predictive potential in diagnosing high-grade cervical intraepithelial lesions. According to the constructed predictive model, the oncogenic activity of HPV 16 and age are risk factors with the strongest predictive values for developing those lesions. Thus, our data indicate that mRNA testing may be more relevant than HPV DNA for assessing lesion grade and diagnosing and monitoring women at risk of progressive cervical disease. This way, the mRNA test as a tool for better risk stratification of HPV infection could overcome unnecessary examinations, increased costs, and patient anxiety. However, further follow-up studies are needed to determine the clinical utility of the mRNA HR HPV test. Acknowledgments The authors are grateful to the personnel of the Department of Gynecology, Community Health Centre Novi Sad, Serbia, and the Oncology Institute of Vojvodina, Serbia, for their contribution to this study. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Dispersion of Ct values of E6/E7 mRNA HR HPVs. Table S1: Analysis of HR HPV DNA 16's influence on the diagnosis of HSIL; Table S2: Analysis of total E6/E7 mRNA HR HPV's influence on the diagnosis of HSIL; Table S3: Analysis of E6/E7 mRNA HR HPV 16's influence on the diagnosis of HSIL; Table S4: Analysis of the influence of age on the diagnosis of HSIL. Click here for additional data file. Author Contributions Conceptualization, N.N., V.G., and V.P; methodology, N.N., N.S., A.M., and T.P.; validation, N.N., N.S., and B.B.; formal analysis, N.N., N.S., M.S., and B.B.; investigation, N.N., A.M., N.S., and B.B.; data curation, N.N., V.G., N.S., D.M., and M.S.; writing--original draft preparation, N.N., B.B., and V.P.; writing--review and editing, V.P., T.P., and A.M.; supervision, V.P. and A.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Committee for the Ethics of Clinical Trials on Humans of the Faculty of Medicine of the University of Novi Sad (number: 01-39/136/1, date 2 March 2017) and the Ethics Committee of the Institute of Public Health of Vojvodina (number: 01-252/3, date 13 February 2017). Informed Consent Statement All of the women provided written consent for the use of the biological specimens for research purposes. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Genotype-specific distribution of HR HPVs. Figure 2 Age-specific analyses of the most prevalent HR HPV DNA in different cytological groups. NILM--negative for an intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. Figure 3 Flowchart presenting the study design. HR--high risk; HPV--human papillomavirus. Figure 4 Prevalence of the most prevalent HR HPVs DNA and achieved oncogenic activity according to age (A) and cytology (B). NILM--negative for an intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. Figure 5 ROC curve of HR HPV and E6/E7 HR HPV tests in HSIL. Figure 6 Correlation between the oncogenic activity of the HPV 16 genotype and cytology (A) and overall HPVs' oncogenic activity and cytology (B). NILM (1), ASCUS (2), LSIL (3), HSIL (4), and Spearman's correlation coefficient (r). diagnostics-13-00917-t001_Table 1 Table 1 Primer and probe sequences used for the RT-PCR analysis. Gene Primer and Probe Sequences (5'-3') E6/E7 HPV 16 F: TTGCAGATCATCAAGAACACGTAGA R: CAGTAGAGATCAGTTGTCTCTGGTTGC P: FAM-AATCATGCATGGAGATACACCTACATTGCATGA-TAMRA E6/E7 HPV 31 F: ATTCCACAACATAGGAGGAAGGTG R: CACTTGGGTTTCAGTACGAGGTCT P: FAM-ACAGGACGTTGCATAGCATGTTGGA-TAMRA E6/E7 HPV 33 F: ATATTTCGGGTCGTTGGGCA R: ACGTCACAGTGCAGTTTCTCTACGT P: FAM-GGACCTCCAACACGCCGCACA-TAMRA * E6/E7 HPV 51 F: AAAGCAAAAATTGGTGGACGA R: TGCCAGCAATTAGCGCATT P: FAM-CATGAAATAGCGGGACGTTGGACG-TAMRA F--forward; R--reverse; P--TaqMan probe; *--antisense; FAM--6-carboxyfluorescein; TAMRA--6-carboxytetramethylrhodamine. diagnostics-13-00917-t002_Table 2 Table 2 Distribution of the most prevalent HR HPVs (HR HPV 16, 31, 33, and 51) in single and multiple infections. HPV Infection HR HPV DNA n (%) n (%) Single 16 83 (48.3) 145 (84.3) 31 28 (16.3) 33 18 (10.5) 51 16 (9.3) Multiple 16, 31 13 (7.6) 27 (15.7) 16, 51 6 (3.5) 31, 33 3 (1.7) 16, 33 2 (1.2) 31, 51 2 (1.2) 16, 31, 33 1 (0.6) Total: 172 (100) 172 (100) diagnostics-13-00917-t003_Table 3 Table 3 Cervical cytology and age of female patients diagnosed with the most prevalent HR HPVs. Most Prevalent HR-HPV-DNA-Positive Women n (%) Cytology NILM 29 (16.9) ASCUS 46 (26.7) LSIL 44 (25.6) HSIL 53 (30.8) Total: 172 (100) Age <=30 68 (36.5) 31-44 62 (36.0) >=45 42 (24.4) Mean age (years, SD)) 36.7 (12.6) SD--standard deviation; NILM--negative for an intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. diagnostics-13-00917-t004_Table 4 Table 4 Distribution of the most frequently detected HR HPVs according to cytology. HR HPV DNA Cytology kh2 p NILM ASCUS LSIL HSIL n (%) n (%) n (%) n (%) HPV 16 + 13 (44.8) 28 (60.9) 24 (54.5) 40 (75.5) 8.628 0.035 * - 16 (55.2) 18 (39.1) 20 (45.5) 13 (24.5) HPV 31 + 11 (37.9) 16 (34.8) 14 (31.8) 6 (11.3) 10.214 0.017 * - 18 (62.1) 30 (65.2) 30 (68.2) 47 (88.7) HPV 33 + 6 (20.7) 6 (13.0) 5 (11.4) 7 (13.2) 1.398 0.706 - 23 (79.3) 40 (87.0) 39 (88.6) 46 (86.8) HPV 51 + 4 (13.8) 5 (10,9) 8 (18.2) 7 (13.2) 1.045 0.790 - 25 (86.2) 41 (89.1) 36 (81.8) 46 (86.8) Total: 29 (100) 46 (100) 44 (100) 53 (100) * p < 0.05. NILM--negative for an intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. diagnostics-13-00917-t005_Table 5 Table 5 Age-specific distribution of female patients with different cytological groups and genotypes. HR HPV-Positive Women Age Group (Years) Total n (%) kh2 p Mean Age (years, (SD)) # p <=30 31-44 >=45 n (%) n (%) n (%) Cytology NILM 19 (27.9) 5 (8.1) 5 (11.9) 29 (16.9) 29.500 0.000 *** 30.9 (12.2) 9.321 0.000 *** ASCUS 21 (30.9) 21 (33.9) 4 (9.5) 46 (26.7) 33.4 (9.2) 0.000 *** LSIL 17 (25.0) 18 (29.0) 9 (21.5) 44 (25.6) 35.9 (11.5) 0.012 * HSIL 11 (16.2) 18 (29.0) 24 (51.1) 53 (30.8) 43.4 (6.8) - Total: 68 (39.5) 62 (36.1) 42 (24.4) 172 (100) Genotype SS HR HPV 16 41 (50.6) 39 (52.0) 25 (56.8) 105 (52.5) 0.147 0.929 36.9 (12.9) 0.289 0.773 HR HPV 31 24 (29.6) 15 (20.0) 8 (18.2) 47 (23.5) 3.930 0.140 33.1 (10.8) 2.317 0.022 * HR HPV 33 10 (12.3) 10 (13.3) 4 (9.1) 24 (12.0) 0.963 0.618 34.1 (11.2) 1.077 0.283 HR HPV 51 6 (7.4) 11 (14.7) 7 15.9 24 (12.0) 2.489 0.298 40.5 (12.7) 1.610 0.109 Total: 81 (40.5) 75 (37.5) 44 (22.0) 200 (100) SD--Standard Deviation; #--ANOVA; SS--t test; * p < 0.05; *** p < 0.001. diagnostics-13-00917-t006_Table 6 Table 6 Analyses of E6/E7 mRNA HPV 16, 31, 33, and 51 in cervical samples. E6/E7 mRNA HPV Genotypes Genotypes n (%) HR HPV 16, 31, 33, 51 Cervical Samples (n = 291) E6/E7 mRNA HR HPV/Most Prevalent HR-HPV-DNA-Positive Samples (%) E6/E7 mRNA HR HPV Positive/HR-HPV-DNA-Positive (%) Positive n (%) Negative n (%) HPV 16 + 51 (25.5) 51 (48.6) 0 (0.0) 29.7 (51/172) 48.5 (51/105) - 149 (74.5) 54 (51.4) 186 (63.9) Total: 200 (100) 105 (36.1) 186 (63.9) HPV 31 + 33 (16.5) 33 (70.2) 0 (0.0) 19.2 (33/172) 70.2 (33/47) - 167 (83.5) 14 (29.8) 244 (83.8) Total: 200 (100) 47 (16.2) 244 (83.8) HPV 33 + 16 (8.0) 16 (66.7) 0 (0.0) 9.3 (16/172) 66.7 (16/24) - 184 (92.0) 8 (33.3) 267 (91.8) Total: 200 (100) 24 (8.2) 267 (91.8) HPV 51 + 15 (7.5) 15 (62.5) 0 (0.0) 8.7 (15/172) 62.5 (15/24) - 185 (92.5) 9 (37.5) 267 (91.8) Total: 200 (100) 24 (8.2) 267 (91.8) Total E6/E7 mRNA genotypes + 115 (57.5) 0 (0.0) 66.9 (115/172) 57.5 (115/200) - 85 (42.5) 119 (100) diagnostics-13-00917-t007_Table 7 Table 7 Distribution of E6/E7 mRNA HR HPV according to cytology. E6/E7 mRNA HPV Genotypes Cytology Total n (%) kh2 p NILM n (%) ASCUS n (%) LSIL n (%) HSIL n (%) HPV 16 + 1 (3.4) 6 (13.0) 10 (22.7) 34 (64.2) 51 (29.7) 46.881 0.000 *** - 28 (96.6) 40 (87.0) 34 (77.3) 19 (35.8) 121 (70.3) Total: 29 (100) 46 (100) 44 (100) 53 (100) 172 (100) HPV 31 + 7 (24.1) 12 (26.1) 10 (22.7) 4 (7.5) 33 (19.2) 6.858 0.077 - 22 (75.9) 34 (73.9) 34 (77.3) 49 (92.5) 139 (80.8) Total: 29 (100) 46 (100) 44 (100) 53 (100) 172 (100) HPV 33 + 3 (10.3) 3 (6.5) 5 (11.4) 5 (9.4) 16 (9.3) 0.682 0.878 - 26 (89.7) 43 (93.5) 39 (88.6) 48 (90.6) 156 (90.7) Total: 29 (100) 46 (100) 44 (100) 53 (100) 172 (100) HPV 51 + 3 (10.3) 1 (2.2) 5 (11.4) 6 (11.3) 15 (8.7) - - - 26 (89.7) 45 (97.8) 39 (88.6) 47 (88.7) 157 (91.3) Total: 29 (100) 46 (100) 44 (100) 53 (100) 172 (100) Cervical samples E6/E7 mRNA HPVs + 13 (10.9) 20 (29.4) 30 (60.0) 48 (88.9) 111 (38.1) - 106 (89.1) 48 (70.6) 20 (40.0) 6 (11.1) 180 (61.9) 108.623 0.000 *** Total: 119 (100) 68 (100) 50 (100) 54 (100) 291 (100) *** p < 0.001. NILM--negative for intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. diagnostics-13-00917-t008_Table 8 Table 8 Analysis of the oncogenic activity of multiple infections of the most prevalent HR HPV. Cytology HR HPV DNA f1 Multiple E6/E7 mRNA HR HPV f2 Single E6/E7 mRNA HR HPV f3 Multiple E6/E7 mRNA HR HPV * (%) Single E6/E7 mRNA HR HPV ** (%) Total Oncogenic Activity NILM 16, 31 1 - 0 - 0 40.0 20.0 60.0 16, 51 1 - 0 51 1 31, 33 2 31, 33 1 - 0 31, 51 1 31, 51 1 - 0 Total: 5 Total: 2 Total: 1 ASCUS 16, 31 6 - 0 16 1 22.2 44.4 66.6 31 3 16, 51 1 - 0 - 0 31, 33 1 31, 33 1 - 0 31, 51 1 31, 51 1 - 0 Total: 9 Total: 2 Total: 4 LSIL 16, 31 3 - 0 16 1 0.0 83.3 83.3 31 2 16, 31, 33 1 - 0 33 1 16, 51 2 - 0 51 1 Total: 6 Total: 0 Total: 5 HSIL 16, 31 3 16, 31 1 16 1 14.3 85.7 100 31 1 16, 33 2 - 0 16 1 33 1 16, 51 2 - 0 16 1 51 1 Total: 7 Total: 1 Total: 6 * (f2/f1) x 100; ** (f3/f1) x 100; NILM--negative for an intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. diagnostics-13-00917-t009_Table 9 Table 9 Analyses of E6/E7 mRNA HPVs according to age. E6/E7 mRNA HR HPV Age (years) Total kh2 p <=30 31-44 >=45 n (%) n (%) n (%) n (%) HPV 16 + 13 (19.1) 20 (32.3) 18 (42.9) 51 (29.7) 7.331 0.026 * - 55 (80.9) 42 (67.7) 24 (57.1) 121 (70.3) Total: 68 (100) 62 (100) 42 (100) 172 (100) HPV 31 + 16 (23.5) 10 (16.1) 7 (16.7) 33 (19.2) 1.373 0.503 - 52 (76.5) 52 (83.9) 35 (83.3) 139 (80.8) Total: 68 (100) 62 (100) 42 (100) 172 (100) HPV 33 + 7 (10.3) 6 (9.7) 3 (7.1) 16 (9.3) 0.322 0.851 - 61 (89.7) 56 (90.3) 39 (92.9) 156 (90.7) Total: 68 (100) 62 (100) 42 (100) 172 (100) HPV 51 + 3 (4.4) 5 (8.1) 7 (16.7) 15 (8.7) 4.951 0.084 - 65 (95.6) 57 (91.9) 35 (83.3) 157 (91.3) Total: 68 (100) 62 (100) 42 (100) 172 (100) * p < 0.05. diagnostics-13-00917-t010_Table 10 Table 10 Clinical characteristics of HR HPV DNA and E6/E7 mRNA HPV tests. Test Cytology Sensitivity CI Specificity CI PPV CI NPV CI (%) (95%) (%) (95%) (%) (95%) (%) (95%) HPV DNA ASCUS 67.6 *** 55.2-78.5 75.6 66.9-83.0 61.3 49.4-72.4 80.4 * 71.8-87.3 LSIL 88.0 ** 75.7-95.5 75.6 66.9-83.0 60.3 48.1-71.6 93.8 * 86.9-97.7 HSIL 98.2 90.1-100 75.6 66.9-83.0 64.6 53.3-74.9 98.9 94.0-100 E6/E7 mRNA HPV ASCUS 29.4 19.0-41.7 89.1 ** 82.0-94.0 60.6 42.1-77.1 68.8 60.9-76.0 LSIL 60.0 45.2-73.6 89.1 ** 82.0-94.0 69.8 *** 53.9-82.8 84.1 76.6-90.0 HSIL 88.9 77.4-95.8 89.1 ** 82.0-94.0 78.7 *** 66.3-88.1 94.6 88.7-98.0 * p < 0.05; ** p < 0.005; *** p < 0.001. CI (95%)--95% confidence interval; PPV--positive predictive value; NPV--negative predictive value; NILM--negative for intraepithelial lesion or malignancy; ASCUS--atypical squamous cells of unknown significance; LSIL--low-grade squamous intraepithelial lesions; HSIL--high-grade squamous intraepithelial lesions. diagnostics-13-00917-t011_Table 11 Table 11 Performance of E6/E7 mRNA HR HPV and HR HPV DNA tests in HSIL. HSIL AUC +- SE p CI (95%) E6/E7 mRNA HR HPV 0.812 +- 0.031 0.000 *** 0.752-0.871 HR HPV DNA 0.740 +- 0.030 0.000 *** 0.680-0.799 AUC--area under the ROC curve; SE--standard error; *** p < 0.001; CI (95%)--95% confidence intervals. diagnostics-13-00917-t012_Table 12 Table 12 Analysis of the mutual influence of relevant factors for HSIL development. HSIL OR CI (95%) p NILM HR HPV DNA 16 + 1.627 0.351-7.531 0.534 - 1.00 a E6/E7 mRNA HR HPV + 3.989 0.843-18.882 0.081 - 1.00 a E6/E7 mRNA HR HPV 16 + 19.099 1.539-236.983 0.022 * - 1.00 a Age (years) <=30 1.00a 31-44 5.382 1.360-21.296 0.016 * >=45 6.654 1.665-26.598 0.007 ** ASCUS HR HPV DNA 16 + 0.957 0.230-3.988 0.952 - 1.00 a E6/E7 mRNA HR HPV + 3.910 0.906-16.871 0.068 - 1.00 a E6/E7 mRNA HR HPV 16 + 6.384 1.215-33.545 0.029 * - 1.00 a Age (years) <=30 1.00 a 31-44 1.401 0.469-4.182 0.546 >=45 8.738 2.147-35.568 0.002 ** LSIL HR HPV DNA 16 + 1.009 0.243-4.192 0.990 - 1.00 a E6/E7 mRNA HR HPV + 1.636 0.377-7.102 0.511 - 1.00 a E6/E7 mRNA HR HPV 16 + 5.099 1.091-23.832 0.038 * - 1.00 a Age (years) <=30 1.00 a 31-44 1.362 0.464-3.992 0.574 >=45 3.719 1.161-11.920 0.027 * OR--Odds ratio; a--reference; CI (95%)--95% confidence interval; * p < 0.05; ** p < 0.01; NILM-negative for intraepithelial lesion or malignancy; ASCUS-atypical squamous cells of unknown significance; LSIL-low-grade squamous intraepithelial lesions; HSIL-high-grade squamous intraepithelial lesions. 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PMC10000478 | Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with a poor prognosis. For PDAC, an increase in the survival time of patients and a reduction mortality have not yet successfully been achieved. In many research works, Kinesin family member 2C (KIF2C) is highly expressed in several tumors. Nevertheless, the role of KIF2C in pancreatic cancer is unknown. In this study, we found that KIF2C expression is significantly upregulated in human PDAC tissues and cell lines such as ASPC-1 and MIA-PaCa2. Moreover, KIF2C upregulation is associated with a poor prognosis when combining the expression of KIF2C with clinical information. Through cell functional assays and the construction of animal models, we showed that KIF2C promotes PDAC cell proliferation, migration, invasion, and metastasis, both in vitro and in vivo. Finally, the results of sequencing showed that the overexpression of KIF2C causes a decrease in some proinflammatory factors and chemokines. The cell cycle detection indicated that the pancreatic cancer cells in the overexpressed group had abnormal proliferation in the G2 and S phases. These results revealed the potential of KIF2C as a therapeutic target for the treatment of PDAC. KIF2C PDAC prognosis invasion migration proliferation cell cycle the Technology Research from the Department of Education of Liaoning ProvinceJCZR2020013 the 345 Talent Project of Shengjing Hospital of China Medical UniversityThe present study was supported by the Technology Research from the Department of Education of Liaoning Province (Grant No. JCZR2020013), and the 345 Talent Project of Shengjing Hospital of China Medical University (J.X., Z.W.). pmc1. Introduction Pancreatic cancer remains a highly malignant tumor, and the survival rate of diagnosed patients is less than 10% . Due to the difficulty in the early diagnosis of pancreatic cancer and the limited treatment options after diagnosis, PDAC is projected to become the second leading cause of cancer deaths by 2040 . In recent decades, even though a lot of research has been conducted on the pathogenesis of pancreatic cancer, the specific molecular mechanism is not completely clear, and the prognosis of patients is still grim. Surgical operation is the most thorough treatment for pancreatic cancer, but fewer than 20% of patients have the opportunity to undergo surgical resection, and 80% of these patients relapse after surgery . Although some research related to pancreatic cancer has shown that immune checkpoint blockades can improve the survival rate of patients to a certain extent, they do not have a profound impact on the overall survival time and reduce the postoperative recurrence rate . Therefore, there is still an urgent need to identify novel therapeutic targets and further explore the underlying mechanisms. Mitosis is a dynamic process of cell division, which is strictly regulated . In this process, the chromosomes of cells are replicated by the separation of spindles with a microtubule structure, composed of dynamic polymers of a and b tubulin . This structure is regulated by a series of kinases, motor proteins, and microtubule-associated proteins . The kinesin 13 family is one of these regulators, which plays a vital role in regulating spindle assembly, chromosome aggregation, and segregation . KIF2C (mitotic centromere-associated kinesin, MCAK) is a member of the kinesin family . It is an efficient depolymerase, has a significant affinity for the end of the microtubule, and can effectively realize the depolymerization and recombination of the end of the microtubule. KIF2C can improve the depolymerization effect and the specificity of the binding tubulin terminal by acting as a dimer . Additionally, the precise regulation of KIF2C not only ensures the normal physiological process of cell mitosis but also interferes with the function of KIF2C, which may defect mitosis and make the structure of the chromosome unstable, both signs of tumor progression . It is also involved in the remodeling of the cytoskeleton during metastasis and invasion, which is related to the abilities of tumor invasion and metastasis . KIF2C has been reported to be involved in the proliferation and migration of hepatocellular carcinoma and breast cancer ; however, no studies have shown that KIF2C is related to the occurrence and development of pancreatic cancer. It is worth noting that there is sufficient evidence to indicate that the expression of KIF2C is abnormal in PDAC and plays a role in tumor progression. In this study, we report that the expression of KIF2C in pancreatic cancer is increased, and it is closely connected to the tumor stage and prognosis of patients. Both in vitro and in vivo experiments show that the expression level of KIF2C affects the invasion, metastasis, and proliferation of pancreatic cancer. 2. Materials and Methods 2.1. Survival Curve and Correlation Analysis The gene expression profile Interactive Analysis browser (Accessed on 5 July 2021, ) is a web-based tool for analyzing the data provided by gene expression profiles and gene tissue expression. The disease-free and overall survival curves associated with KIF2C were obtained from a GEPIA online analysis. In addition, the expression of KIF2C in different tumors was learned through a GEPIA analysis, as well as the expression differences between pancreatic cancer and adjacent cancer, which laid a certain foundation for future work. The correlation between KIF2C and CDC20 was also analyzed by GEPIA. The OS, PFS, and GSEA enrichment analyses were analyzed by R studio from TCGA datasets. 2.2. Patients and Specimens The 14 pairs of cancer and paracancerous tissues used in the qPCR analysis were all from Shengjing Hospital, Shenyang, China. The paraffin-embedded pathological specimens used for the immunohistochemical analysis from 200 patients with PDAC were collected from the archives of the Department of Pathology, Shengjing Hospital, between January 2017 and August 2019. These cases were randomly selected surgical slides from different inpatient wards, and the pathological information was completed by telephone follow-up at the same time as the completion of the immunohistochemistry. Patient consent was waived due to no additional inspection or injury, and all specimens used in the study were approved by the Committees for Ethical Review of Research Involving Human Subjects in the China Medical University. 2.3. Immunohistochemical (IHC) Staining Briefly, all of the steps of the immunohistochemistry were performed according to the instructions of the Immunohistochemical Kit (UltraSensitiveTM SP IHC Kit, MXB, China). We set the depth of staining as 0-3 (0 = none, 1 = weak, 2 = medium, and 3 = strong). The staining range was divided into the five grades of 0-4 (0 = none, 1 = <25%, 2 = 25-50%, 3 = 50-75%, and 4 = >75%). KIF2C expression = staining depth * staining range. 2.4. Cell Culture ASPC-1 and MIA-PaCa2 were purchased from Procell (Wuhan, China). All cell lines were authenticated. ASPC-1 was cultured in 1640 (VivaCell, Shanghai, China) with 10% 30070 (Hyclone, Logan, UT, USA), and MIA-PaCa2 was cultured in high-glucose Dulbecco's modified Eagle's medium (DMEM; VivaCell, Shanghai, China) with 10% 30070 and 3% horse serum (Gibco, Grand Island, New York City, NY, USA). Both of the cell lines were cultured in a 37 degC humidified incubator (Thermo, Waltham, MA, USA) with a 5% CO2 environment. 2.5. Plasmid Construction and Transfection All the plasmids were purchased from GenePharma (Suzhou, China). The sequence of shRNA and siRNA was 5'-GCATAAGCTCCTGTGAATATA-3'. Cell transfection was performed using Lipofectamine 2000 Reagent (11668-019, Invitrogen, Carlsbad, CA, USA) following the manufacturer's instructions. All transfection efficiencies were verified by qPCR after 24 h. shRNA and overexpressed plasmid transfection were screened with g418 (Ig0010, Solarbio, Beijing, China). Since the plasmid contained g418 resistance, 600, 800, and 1000 mg/mL of g418 antibiotics were added to the transfected six-well plate once every three days for a week. Then, the dose of antibiotics was halved and maintained for a month. The transfection efficiency was detected by qPCR. The cells selected by the 800 mg/mL concentration of antibiotics had the highest transfection efficiency. The cells were subcultured in a T75 culture flask (Thermo, Waltham, MA, USA) and frozen. 2.6. Cell Proliferation, Migration, and Invasion Assays The cell proliferation experiment was completed by the MTT and soft agar colony formation assays. MTT: The cells were seeded in a six-well plate for transfection, and within 24-48 h of transfection, the cells were digested, resuspended, and counted. Then, 5000 cells were evenly plated in a 96-well plate, and 20 mL of MTS (5 mg/mL) were added every day to incubate for 2 h, and the absorbance was measured. There were three wells in each group, and the cell proliferation was measured continuously for four days. Soft agar colony formation assays: Firstly, 1.2% agarose was mixed with 20% 30070 + 2*1640 medium/high-glucose DMEM in a 1:1 ratio, and 1.5 mL of the mixture was added to each well of the six-well plate, gently mixed, and left to set at room temperature (no bubbles were generated). Secondly, 0.7% agarose was mixed with 20% 30070 + 2*1640/high-glucose DMEM in a 1:1 ratio, and cell suspension prepared in advance was added into the mixture, which was quickly mixed and added into the six-well plate (1 mL per well). After the upper layer solidified, it was placed in the incubator at 37 degC for 2-3 weeks. Add 10% 30070 + 1640/high-glucose DMEM every two days to prevent excessive drying. The Transwell migration and Matrigel (Corning, Corning, New York City, NY, USA) invasion assays were mainly performed as below. The main process can be briefly described as follows: First, the Matrigel was diluted with serum-free medium (1:9), the mixture was evenly dripped to the upper part of the chambers (50 mL per chamber), and then, the 24-well plate was placed in a 37 degC humidified incubator for 4 h. Cells (5*104) ASPC-1/MIA-PaCa2 (100 mL) and 600 mL of 1640 medium (ASPC-1 cell line) or high-glucose DMEM cell (MIA-PaCa2 cell line) suspension were added to the upper layer of the chamber, and 600 mL of the ASPC-1 cell line culture medium (1640 with 10% 30070) or MIA-PaCa2 cell line culture medium (high-glucose DMEM with 10% 30070 and 3% horse serum) were added to the lower layer. When the cells were placed in the chamber for approximately 12 h, they were fixed with methanol, stained with hematoxylin and eosin, dried, and photographed under a microscope to observe the migration ability. For the Matrigel invasion, the migrated cells were fixed with methanol and stained with hematoxylin and eosin after 36 h. The data were all obtained from three independent experiments. 2.7. RNA Isolation and Quantitative RT-PCR All the tissues and cell RNA were obtained via Trizol (9109, TaKaRa, Shiga, Japan) extraction. The extracted RNA was reverse-transcribed using a PrimeScript RT-PCR Kit (RR047A, Takara, Shiga, Japan) to obtain cDNA. A SYBR GreenPCR Kit (RR820A, TaKaRa, Shiga, Japan) was the only reagent used to conduct qRT-PCR. The primer sequences can be found in Supplementary File S2. 2.8. Western Blot Cell and tissue samples were cleaved in a cold RIPA cleavage buffer (Beyotime, Shanghai, China). Determination of the protein concentration was achieved using a BCA Analytical Kit (Beyotime, Shanghai, China). The proteins were layered by electrophoresis through 10% SDS-PAGE gel (Beyotime, Shanghai, China) and then transferred to 0.22 mm PVDF membranes. The protein-transferred PVDF membrane was blocked with 5% skimmed milk powder for 2 h and subsequently washed three times with TBST, each for 5 minutes, before being incubated with the primary antibody overnight at 4 degC. The primary antibody was recycled, the membrane was washed with TBST three times (each for 5-10 minutes), and then, the secondary antibody was applied for 1 h at room temperature. After three washes with TBST, the ECL (Beyotime, Shanghai, China) was used to visualize the PVDF membrane. For quantification, the optical density of individual bands was analyzed by ImageJ software (V1.8.0, NIH, USA), and the values were normalized to GAPDH (1:5000, Proteintech, Chicago, USA). Full Western blot images can be found in Supplementary File S1. 2.9. Antibodies The antibodies used in this study were as follows: KIF2C (1:1000, Sigma, Darmstadt, Germany), IL-1b (1:1000, Elabscience, Wuhan, China), IL-18 (1:1000, Elabscience, Wuhan, China), CDC20 (1:2000, Proteintech, Chicago, USA), and GAPDH: (1:5000, Proteintech, Chicago, USA). 2.10. Animals Model Five-week-old female BALB/c nude mice were used in this study. In the subcutaneous xenograft model, MIA-PaCa2 cells were digested, resuspended with PBS, and counted. All 2*106 MIA-PaCa2 cells were resuspended with 100 microliters of bovine serum albumin solution and injected into the axilla of each nude mouse in the tumorigenesis experiment. The tumor formed two weeks after the injection, and the diameter of the tumor was measured every three days. Two weeks later, the nude mice were sacrificed, and the tumors were harvested, weighed, fixed, and paraffin-embedded for further analysis. For the metastatic assay, 2*106 MIA-PaCa2, the mice were euthanized and the lungs were excised and embedded in paraffin for further analysis. 2.11. Embedding and Slicing After the lung tumorigenesis model of the nude mice was taken out, the lungs were immediately squeezed in formalin (Beyotime, Shanghai, China) to fill the lungs. After soaking for one day, they were embedded in OCT (Tissue-Tek(r) O.C.T. Compound, Sakura Finetek, Torrance, CA, USA) and preserved at -80 degC for frozen sections. The embedded tissue was sliced with a frozen slicer (CM1950, Leica, Weztlar, Germany) with a thickness of 8 microns. 2.12. Cell Cycle Detection All operations were carried out in accordance with the instructions (Cell Cycle and Apoptosis Analysis Kit, Beyotime, Shanghai, China). 2.13. H&E Staining For hematoxylin-eosin staining (Modified Hematoxylin-Eosin (HE) Stain Kit, G1121, Solarbio, Beijing, China), we circled all of the tissues on the slices with an immunohistochemical pen (YA0310, Solarbio, Beijing, China) and then inserted all of the slides into the slice rack before rinsing with tap water for 10 min. Then, we took out the slides, put them on the dye board, and covered the tissue with drops of hematoxylin solution for 15 min before rinsing with tap water for 10 s. Next, we covered the tissue with drops of differentiation solution for 5 s before rinsing with tap water for 30 s. Following this, we covered the tissue with drops of bluing solution for 1 minute before rinsing with tap water for 30 s. Lastly, we covered the tissue with drops of eosin solution for 30 s before rinsing with tap water for 5 s. The slices were then dehydrated in a concentration of 75%, 85%, 95%, or 100% ethanol for 3 s; anhydrous ethanol II for 1 minute; and xylene I and II and each transparent for 1 minute. Finally, the slices were sealed with xylene and neutral balsam (G8590, Solarbio, Beijing, China) (1:1). 2.14. Statistical Analysis One-way ANOVAs were used to compare the expression levels of KIF2C or other targets among three or more groups, while t-tests were used to compare the expression levels of KIF2C or other targets between two groups. In order to compare the OS of the patients between subgroups, we used the Kaplan-Meier method and bilateral logarithmic rank tests. IBM SPSS 26 software (SPSS V26.0, Chicago, IL, USA) and Prism 9 (GraphPad Software V9.0, CA, USA) were used to analyze the experimental data. All experiments were carried out at least three times; the data are expressed as the mean +- standard deviation. The difference was statistically significant at p < 0.05. 2.15. Data Availability Statement The original contribution proposed in this study is included in the article/supplementary materials. Further inquiries can be directed to the corresponding author. 2.16. Ethics This project was approved by the Institutional Review Committee of Shengjing Hospital of China Medical University (ethical approval codes: 2021PS424K and 2021PS747K). 3. Results 3.1. Upregulation of KIF2C in PDAC The results of the TCGA analysis indicated that the expression of KIF2C was different in various cancers . The expression level of KIF2C in pancreatic cancer was also higher than that in normal tissues . Based on the data of The Human Protein Atlas, we found that, in normal pancreatic tissue, KIF2C was lowly expressed in exocrine glandular cells, while KIF2C was not detected in endocrine cells . In other words, the expression of KIF2C in normal pancreatic tissue is low, but after normal tissue develops into cancer, its expression increases rapidly. This means that KIF2C may be an important protein in the occurrence and development of pancreatic cancer. The difference in the expression of KIF2C in pancreatic cancer makes us think about the relationship between KIF2C and survival. The Kaplan-Meier analysis of the TCGA database showed that the expression of KIF2C was closely related to the survival time of patients; in particular, the high expression of KIF2C had a deeper impact on disease-free survival . In order to better determine the impact of KIF2C on survival, we analyzed other datasets of TCGA and obtained the same results . KIF2C affects the progression-free, disease-free, and overall survival. Moreover, the GSEA enrichment analysis indicates that KIF2C is closely associated with the cell cycle, DNA replication, etc. . 3.2. Abnormal Expression of KIF2C in Clinical Specimens The results of the bioinformatics analysis aroused our interest. We noticed that there is no relevant literature to show whether the difference in KIF2C expression has an influence on pancreatic cancer. At first, we performed qPCR detection and a Western blot of the KIF2C expression in the cell lines, including ASPC-1, BXPC-3, HPOECT, Y5, SW1990, CAPAN-1, and MIA-PaCa2. It was found that the expression of KIF2C in the ASPC-1 cell line was obviously increased in comparison to the expression in the other cell lines . After validating the cell lines, we extracted the cancer and paired adjacent cancer RNAs from pancreatic cancer patients and detected the relative expression of KIF2C by qPCR after reverse transcription . After that, we also extracted proteins from cancer and adjacent tissues and detected the expression of KIF2C by Western blot . We intuitively found that the expression of KIF2C in cancer tissue was higher than that in adjacent tissue. Next, we carried out immunohistochemical staining on 70 randomly selected pancreatic cancer specimens. By analyzing the depth and range of staining, the expression level of KIF2C in pancreatic cancer was prominently higher than that in normal or highly differentiated tissues . At the same time, after selecting the pathological tissues to be stained, we collected the relevant clinical information of the patients through case files and follow-up. By combining the staining results with the clinical information of the specimens, we acquired a meaningful result (Table 1). Patients with advanced TNM pancreatic cancer had higher KIF2C expression levels compared to patients with early TNM. In addition, KIF2C was also connected to the degree of tumor differentiation, and the expression of KIF2C was significant in poorly differentiated tumors. Furthermore, a combined analysis of KIF2C expression and the postoperative survival time showed that patients with high KIF2C expression had a shorter survival time than those with low KIF2C expression . 3.3. Knockdown of KIF2C Inhibits PDAC Cell Proliferation, Migration, and Invasion In Vitro Subsequently, we investigated whether KIF2C affects the proliferation, migration, and invasion of PDAC cells. First, we altered the KIF2C expression in APSC-1 and MIA-PaCa2 cells by the transfection of overexpressed plasmid and siRNA . In order to obtain stably expressing cells, we performed g418 antibiotic screening for one month after the transfection of overexpression and shRNA plasmids. As for the MTT assay, we plated 5000 cells per well evenly in 96-well plates to detect proliferation in the different treatment groups. The absorbance of three wells in each group was measured by the microplate reader every day for four consecutive days, and a line graph was made after taking the average value . The line graph clearly shows that the proliferation rate of the interference group was significantly lower than that of the other groups. Normally, the proliferation rate of ASPC-1 was faster than that of MIA-PaCa2. It can be seen from the figure that the inhibition of ASPC-1 proliferation by knocking down KIF2C was stronger than that of MIA-PaCa2 at 24 and 48 h. As for the migration and invasion assays, 50,000 cells were placed in each chamber for Transwell migration and Matrigel invasion assays. After 12 h, the cells in the migration assays were fixed and stained; after 36 h, the cells in the invasion assays were fixed and stained. After gently wiping away the non-infiltrated cells from the chamber and allowing the chamber to dry, the effect of sh-KIF2C on cell migration and invasion was observed under a microscope . Under the microscope, it was observed that, for both the ASPC-1 and MIA-PaCa2 cell lines, the interference of KIF2C caused a distinct decrease in the ability of cancer cells to invade and migrate. However, the evidence of in vivo experiments is also imperative. Before this, we chose to simulate the in vivo experiment through a soft agar colony formation assay to explore the expected results. Since the proliferation rate of MIA-PaCa2 is slower than that of ASPC-1 and the cell size of MIA-PaCa2 is also smaller, there were 5000 cells per well in a six-well plate in the ASPC-1 group and 10,000 cells per well in the MIA-PaCa2 group. In two to three weeks, the laid single cells proliferated to form a cell mass . Under the microscope, in the interfered treatment group, the proliferation of cancer cells was significantly inhibited. These results suggest that KIF2C may be one of the key genes with a strong ability to proliferate and invade in pancreatic cancer. 3.4. Overexpression of KIF2C Promotes PDAC Cell Proliferation, Migration, and Invasion In Vitro Irrespective of the analysis of bioinformatics or the verification of clinical samples, KIF2C in pancreatic tumor cells is much higher than that in a normal pancreas. The overexpression of KIF2C is very crucial to explore whether it can promote tumor proliferation and enhance the abilities of invasion and migration. In the MTT assays, the effect of the overexpression of KIF2C on the proliferation of ASPC-1 was slightly weaker than that of MIA-PaCa2 . However, in both cell lines, the overexpression of KIF2C did significantly promote the proliferation of tumor cells. As for the migration and invasion assays, the penetration ability of overexpressed tumor cells was stronger than that of the control group . In the soft agar colony formation assay, it was shown that, in the group with the overexpression of KIF2C, both MIA-PaCa2 and APSC-1 formed more and larger cell colonies than those in the control group . This means that the overexpression of KIF2C in pancreatic cancer is not meaningless. Pancreatic cancer patients have a low survival rate, a high degree of malignancy, and a high metastasis rate. KIF2C may play a promoting role in these aspects. 3.5. KIF2C Promotes PDAC Cell Proliferation, Migration, and Invasion In Vivo With the strong support of the above in vitro experiments, we further explored whether KIF2C has the same effect in vivo. We established a model of ectopic pancreatic cancer by subcutaneous injection in female nude mice. Our team chose to use MIA-PaCa2 when building a subcutaneous pancreatic cancer tumor model, because in previous experiments, we observed that the animal model built by ASPC-1 causes the tumor to rupture and bleed due to vascular infiltration, among other reasons. Two weeks later, tumor formation was observed, and the tumor diameter was measured every three days. Two weeks later, the nude mice were sacrificed, and the tumor was measured to compare the differences between the different treatment groups . In the process of observing the growth of the tumor, we noticed that the initial time of subcutaneous tumor formation in the interference group was significantly later than that in the other groups, and the tumor growth rate was also slower in the later stage . Although the tumor volume of mice in the blank control group was slightly higher than that in the NC group, there was no significant difference between the NC group and the blank control group. In the picture, we can see that the volume of the blank control group seems to be much larger than that of the NC group, but the weight is only slightly larger than that of the NC group. This is because, although the blank control group looks larger, it is thinner. The reason why the weight of the overexpression group is much larger than that of the control group is that the tumor is thicker, which can be observed by the height of the protruding skin of the nude mice. The proliferation rate and the final tumor size of the overexpressed KIF2C group were undoubtedly larger than those of the other groups. After fixing each subcutaneous tumor with paraformaldehyde, the tumor was dried and weighed for statistical analysis . When the mice were sacrificed, the average diameter of the control group was approximately 1.1 cm, while the overexpressed group reached 1.4 cm. However, in terms of tumor volume, the most obvious contrast was between the interference group and the control group. The tumor in the interference group was flatter, and the weight of the tumor was much smaller than that in the control group. This is consistent with the in vitro results. Meanwhile, we built a lung metastasis model by tail vein injection . Eight weeks later, the samples of lung metastases were taken out, and it was observed with the naked eye that the lung surface of the sh-KIF2C group was smoother, and the number of tumor metastases was lower, while the lung surface of the KIF2C group was full of lesions . We also observed the same results under the microscope after H&E (hematoxylin-eosin) staining of the lung-embedded sections . 3.6. The Potential Mechanism of KIF2C in PDAC After completing the experiments in vivo and in vitro, we have to think about how KIF2C has such an effect on pancreatic cancer cells. Therefore, we sent the transfected cells to be sequenced by Trizol cleavage in order to understand which genes changed and which signal pathways were affected when KIF2C changed. We performed the GO (Gene Ontology) analysis, differential gene screening, and KEGG analysis after obtaining the sequencing results. In the GO analysis, we learned that KIF2C is related to many functions, such as the mitotic DNA integrity checkpoint, response to osmotic stress, and DNA replication . What interests us most out of these functions is the cell cycle, because KIF2C is a mitotic centromere-associated kinesin. Therefore, we detected the cell cycle of transfected pancreatic cancer by flow cytometry . The results of the cell cycle detection showed that, compared to the control group, the S phase of the sh-KIF2C and KIF2C groups increased, while the S phase of the KIF2C group was longer. Combined with the results of the proliferation assays, we believe that the increase in the S phase in the KIF2C group is due to the abnormal activity of DNA synthesis, while, in the sh-KIF2C group, the S phase is prolonged due to the block of DNA synthesis in this phase. This is because the G2 phase increased after S phase prolongation in the KIF2C group, while the G2 phase did not increase in the sh-KIF2C group. In the differential gene screening, we found some genes that are statistically significant . Similarly, we obtained several statistically significant signal pathways in the KEGG analysis . Finally, we decided to select some differential genes in the pathway for verification. For these genes, we first carried out a preliminary detection by qPCR . It is not difficult to see that the signal pathways with significant statistical differences are related to the cell cycle and immunity. After verifying the expression level of RNA, we selected three indicators from the two aspects of immunity and the cell cycle to verify the alteration of the protein level . The results of the WB showed that the overexpression of KIF2C caused the downregulation of IL-1b and IL-18, and the expression of KIF2C was positively correlated with CDC20, which is consistent with the results of the correlation analysis in the TCGA database . 4. Discussion In this study, we first identified the high expression of KIF2C in pancreatic cancer by TCGA and subsequently verified this finding at the DNA and protein levels. After combining the expression level of KIF2C with the clinical information of patients, it was not difficult to find that the high expression level of KIF2C was positively correlated with the degree of malignancy of PDAC. Therefore, we speculate that KIF2C may play a crucial role in the occurrence and development of pancreatic cancer. To test this hypothesis, we designed a series of in vivo and in vitro assays to verify the effect of KIF2C on the degree of malignancy of PDAC. Compared to the control group, the tumor volume of KIF2C-overexpressing mice was larger, and the tumorigenesis time was shorter. In stark contrast, it significantly inhibited the growth of tumors in the shRNA group. Not only that, but we observed that KIF2C overexpression promoted tumor metastasis in a mouse lung tumor formation assay by tail vein injection, resulting in large areas of metastasis and the diffusion of cancer cells in the lungs of the mice. In recent years, the close relationship between KIF2C and different tumors has been gradually revealed, which coincides with our results . Sacha et al. found that KIF2C is significantly overexpressed in colorectal and other epithelial cancers, and the proliferative activity of the tumor is correlated with KIF2C expression levels . In fact, we are not surprised about these research findings due to the "background" of KIF2C. KIF2C is a member of the kinesin 13 family, which regulates the processes of spindle assembly, chromosome aggregation, and separation . The main function of KIF2C is to regulate the dynamics of microtubules during mitosis. It is located in the centrosome, the centromere/centromere region, and the middle of the spindle . As KIF2C recruits these regions, it participates in spindle assembly, correction of centromere-microtubule connection errors, and chromosome aggregation and separation . Therefore, the inhibition or depletion of KIF2C disrupts normal spindle dynamics, resulting in abnormal chromosome aggregation and segregation and reducing the activity of KIF2C, especially in the centromeric region, causing damage to the movement of chromosomes . Not only does KIF2C regulate the movement of chromosomes, but Zhu et al. also found that KIF2C is involved in DNA damage . When we talk about DNA damage and the structural instability of chromosomes, we have to turn our attention to another focus--cancer . Genomic instability is undoubtedly one of the main causes of tumorigenesis . The evidence presented thus far supports the idea that KIF2C is closely related to the occurrence of cancer. Moreover, KIF2C may also play a crucial regulatory role in the immune microenvironment. Researchers in endometrial cancer have found that the knockout of KIF2C can inhibit the apoptosis of CD8+T cells and ki-67 expression . In fact, KIF2C is involved in different signal pathways. For example, in cervical cancer, the downregulation of KIF2C can promote the activation of the p53 signal pathway ; in hepatocellular carcinoma, KIF2C promotes the development of hepatocellular carcinoma through the Ras/MAPK and PI3K/Akt signal pathways . In this study, the results very clearly demonstrate that the higher the expression level of KIF2C, the higher the degree of malignancy of the tumor. Interference with KIF2C can effectively reduce the invasiveness of pancreatic cancer, which may become a promising target for the treatment of this cancer. In the last part of this paper, we verified the potential mechanism of KIF2C, showing that the interference and overexpression of KIF2C can affect the cell cycle of pancreatic cancer cells, which is also consistent with the bioinformatics enrichment analysis, while changes in KIF2C also cause some changes in the immune index and signal pathway . The results of the transcriptome suggest that KIF2C may be related to the phase transition of the cell cycle, which may be by way of a S phase change after KIF2C knockout or overexpression. In addition, we found that the expression of KIF2C was positively correlated with CDC20. As a key regulatory protein in the cell cycle, in recent years, CDC20 has been proven to promote the proliferation, migration, and invasion of pancreatic cancer . CDC20 may also be involved in the role of KIF2C in pancreatic cancer. However, we did not conduct an in-depth exploration of the signal pathway of KIF2C's function, revealing only the role of KIF2C in pancreatic cancer and the pathways and genes that may be related to it, which is also where this study needs to be improved. 5. Conclusions In this study, we initially found a special expression of the KIF2C gene through bioinformatics and specimen detection. In the follow-up experiments, we clearly observed the effect of KIF2C on the proliferation and invasion of PDAC; the results of the sh-KIF2C group in the in vivo experiment were especially exciting. The downregulation of KIF2C can greatly inhibit the formation of subcutaneous tumors and lung metastasis. In the exploration of the potential mechanism, various results showed that KIF2C plays a regulatory role in the cell cycle, but this may not be the only way for KIF2C to promote the malignant proliferation of PDAC. The effect of KIF2C on pancreatic cancer may not only be limited to the development of PDAC but may also pull the "trigger" and cause tumorigenesis. At present, the therapeutic effect of pancreatic cancer is limited; we hope that the target of KIF2C can provide new ideas for its treatment, so that patients who cannot receive timely surgical treatment can obtain a better prognosis. Acknowledgments The authors sincerely thank all of the members of the laboratory for their valuable suggestions and appreciate TCGA and GEPIA for their data sharing. Supplementary Materials The following supporting information can be downloaded at: File S1: Full Western blot images. File S2: The primer sequences. Click here for additional data file. Author Contributions X.H. wrote the manuscript. J.X., Z.W. (Zhe Wang), Q.W., Z.W. (Zitong Wang), Q.Z., H.R. and F.Z. edited the final version. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Institutional Review Committee of Shengjing Hospital of China Medical University (ethical approval codes: 2021PS424K and 2021PS747K). Informed Consent Statement The requirement for written informed consent was waived due to the retrospective nature of the study. Data Availability Statement Data are available upon request through the corresponding author. Conflicts of Interest The study was conducted without any business or financial relationship that could be interpreted as a potential conflict of interest. Abbreviations PDAC: pancreatic ductal adenocarcinoma; IHC: immunohistochemistry; KIF2C: kinesin family member 2C; shRNA: small hairpin RNA; siRNA: small interfering RNA; TCGA: The Cancer Genome Atlas; IL-1b: interleukin-1b; IL-18: interleukin-18; CDC20: cell division cycle 20; GEPIA: Gene Expression Profiling Interactive Analysis; OS: overall survival; DFS: disease-free survival; GO: Gene Oncology; KEGG: Kyoto Encyclopedia of Genes and Genomes; NC: negative control; PAAD: pancreatic cancer. Figure 1 The expression level of KIF2C in PAAD and its relationship with survival and prognosis. (A) Expression levels of KIF2C in different tumors in the TCGA database. (B) The expression of KIF2C in PAAD was significantly higher than that in normal tissues in the TCGA database (Num(T) = 179, Num(N) = 171, *p < 0.05). (C) The expression of KIF2C in the pancreas from The Human Protein Atlas. (D) Kaplan-Meier curves for the OS (HR(High) = 1.6) and DFS (HR(High) = 2.2) of patients in the high-and low-KIF2C groups. (E) Kaplan-Meier curves for the PFS and DFS of patients in the high-and low-KIF2C groups. (F) Cell cycle, steroid hormone biosynthesis, systemic lupus erythematosus, and DNA replication were related to KIF2C in the GSEA enrichment analysis. Figure 2 Immunohistochemical results of KIF2C in pancreatic carcinoma with different differentiation. (A) Real-time PCR detection of the KIF2C expression in different pancreatic cancer cell lines. (B) Real-time PCR detection results of the KIF2C expression in 13 pairs of fresh specimens (pancreatic cancer and paired adjacent cancers). (C) Kaplan-Meier curves for the postoperative survival of patients in the low-KIF2C groups. (D) Western blot of the KIF2C expression in different pancreatic cancer cell lines. (E) Western blot of the KIF2C expression in 7 pairs of fresh specimens (pancreatic cancer and paired adjacent cancers). (F) Immunohistochemical staining intensity of KIF2C in different tumor differentiation grades. Figure 3 A series of assays on the invasion, migration, and proliferation of the transfected cell lines (ASPC-1 and MIA-PaCa2). (A) Western blot of the blank control, NC, overexpression, and si-KIF2C groups (** p < 0.01, *** p < 0.001, **** p < 0.0001). (B) A line chart of the absorbance for the MTT assay on ASPC-1 (* p < 0.05). (C) A line chart of the absorbance for the MTT assay on MIA-PaCa2 (* p < 0.05). (D) Migration assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (**** p < 0.0001). (E) Invasion assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (**** p < 0.0001). (F) A soft agar colony formation assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (**** p < 0.0001). Figure 4 A series of assays on the invasion, migration, and proliferation of the transfected cell lines (ASPC-1 and MIA-PaCa2). (A) Migration assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (**** p < 0.0001). (B) Invasion assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (*** p < 0.001, **** p < 0.0001). (C) Soft agar colony formation assay on ASPC-1 and MIA-PaCa2 stable transfection. On the right is a statistical bar chart (*** p < 0.001, **** p < 0.0001). Figure 5 Subcutaneous and pulmonary tumorigenesis assay in vivo. (A) A model picture of subcutaneous tumorigenesis. (B) The size and weight of the subcutaneous tumor in the different groups (**** p < 0.0001). (C) Growth changes of subcutaneous tumorigenesis at 0-4 weeks in each group. (D) A model picture of lung metastases. (E) Lung tissue with tumor metastasis in the different groups. (F) H&E staining of lung metastasis under a microscope in the different groups. (G) Lung metastasis area was measured in each group (*** p < 0.001, **** p < 0.0001). Figure 6 Analysis after sequencing and the results of cell cycle detection, real-time PCR, and Western blot validation. (A) The results of the GO analysis, in which the functions related to the cell cycle and mitosis are the most noteworthy. (B) Cell cycle detection of the transfected cell lines in each group, during which the S phase of the sh-KIF2C and KIF2C groups increased (*** p < 0.001, **** p < 0.0001). (C) Heat map of the differential genes in the overexpression and NC groups. (D) The results of the KEGG analysis, where the Nod-like receptor and cell cycle signaling pathways are perhaps the main pathways in which KIF2C plays a role. (E) The results of the real-time PCR detection of some differential genes, showing that changes in KIF2C do affect the expression of other genes. (F) Correlation analysis between KIF2C and CDC20 in the TCGA database (Red box and gray box represent cancer tissue and paracancerous tissue respectively). (G) Western blot analysis of the IL-1b, IL-18, and CDC20 levels (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001). Figure 7 The impact of KIF2C alterations. cancers-15-01502-t001_Table 1 Table 1 The relationship between KIF2C expression and the clinicopathological features of 70 patients with PDAC. Clinicopathological Variables n KIF2C Expression p Value Low/Moderate High All cases 70 42 28 Age (years) <60 32 18 14 >=60 38 16 22 0.643 Gender Male 35 23 12 Female 35 16 20 0.111 TNM stage IA 27 17 10 IB 17 8 9 IIA 0 0 0 B 11 4 7 III 0 0 0 IV 14 4 10 0.028 (<0.05) Differentiated degree Low/moderate 46 17 29 High 24 17 7 0.022 (<0.05) Drinking history Yes 21 12 9 No 49 22 27 0.412 Obstructive jaundice Yes 39 17 22 No 31 17 14 0.420 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000479 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050683 healthcare-11-00683 Review Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment Strunga Martin * Urban Renata Surovkova Jana Thurzo Andrej * Giansanti Daniele Academic Editor Department of Orthodontics, Regenerative and Forensic Dentistry, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia * Correspondence: [email protected] (M.S.); [email protected] (A.T.) 25 2 2023 3 2023 11 5 68331 12 2022 17 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients' treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently. orthodontics AI ChatGPT AI Treatment Assessment Teledentistry Cephalometrics Slovak Grant Agency for Science KEGA Thurzo054UK-4/2023 This work was supported by the Slovak Grant Agency for Science KEGA Thurzo--grant No. 054UK-4/2023. pmc1. Introduction Assistive technologies and automated systems are high-tech elements that are every day reshaping workflows of modern healthcare. Assistive technologies, including virtual reality, are designed to improve or maintain a person's functioning so that they can participate in all aspects of life . Automated systems empowered with Artificial Intelligence (AI) can support healthcare decision-making, therapy, and rehabilitation and can also help prevent treatment errors. These technologies can be used individually or can be interconnected to create assisted living solutions or enable rehabilitation at home . Artificial intelligence is essential for advanced computer aided diagnostics' appropriate integration of social robots with the potential to bring benefits to aged care and also future hybrid exoskeleton systems . Various telemonitoring systems will benefit from the AI evaluation of sensor data from mobile phones or wearables, e.g., patient movements in the early diagnosis of Parkinson's disease . AI is not only the future of advanced robotics in healthcare , but it is also cornerstone of advanced digital radiology in dentistry, including the orthodontic specialty . The editorial of the International Journal of Environmental Research and Public Health from September 2022 by Giansanti summarized what is expected from an AI-based system in the public health domain. Today's rapidly growing desire by dental practices to increase the effectiveness of their treatments has led to the development of numerous tools to achieve this, such as Dental Monitoring software (DM) (Dental Monitoring Co., Paris, France), StrojCHECK by Sangre Azul (3Dent medical Ltd., Bratislava, Slovakia), White teeth, etc. DM is a combination of artificial intelligence and telemedicine that enables easy daily collaboration and communication between the dental practice and the patient via a smartphone software app. This facilitates the coordination and execution of each step and the monitoring of the achieved goals throughout the treatment. It is feasible for both parties to use the maximum potential of this tool. There is an increasing demand for health apps not only in orthodontic dentistry but also in other medical specialties . The possibilities of health apps are immense, ranging from promoting an active, healthy lifestyle, assisting with nutrition, preventing diabetes and high blood pressure, and treating depression to changing behavior to stop smoking and drinking alcohol, taking medications regularly, etc. They also enable monitoring and adjustment of calorie intake and output. For this purpose, additional devices such as wristbands and smartwatches are often used alongside smartphones. These sensor systems vary from accelerometers, barometers, geosensors, heart rate sensors, etc. . Additionally, current studies have shown that telemedicine also provides a way to improve primary care accessibility, as it can decrease the time to specialty consultation, reduce the number of patients on the waitlist, and it allows the more urgent cases to reach a specialist sooner . The high technological level of sensors in smartphones have led not only to dental monitoring but also to utilizations of optical scanning for 3D face morphology registration . This application of telemedicine, specifically teledentistry, has proven to be increasingly popular and acceptable amongst not only adolescent and child patients but also in adults . For some clinical applications of advanced 3D-printed appliances in children with craniofacial syndrome, regular home telemonitoring would be extremely valuable and would minimize the potential risks of appliance damage and treatment failure in complicated cases, such as Pierre Robin Sequence patients with 3D-printed palatal plates or common orthodontic patients with 3D-printed distalizers . This also brings an economic and efficiency aspect to the usage of various types of telehealth software. Current data from after the COVID-19 pandemic show that treatments monitored with a DM app required 33.1% less appointments than patients without monitoring. In addition, the duration of the first phase of treatment was reduced by 1.7 months on average for the DM group and, finally, although without clinically significant relevance (less than 0.5 mm or less than 2deg), there was an increased accuracy of movements expressed on maxillary and mandibular anterior teeth when compared to predicted positions . Studies have shown that their use is perceived as feasible for several reasons: the first, and particularly important, reason is the behavioral impact on the patient during usage of these tools. It has been proven that a patient's engagement in the treatment is considerably improved as a direct effect of working with the app. As a result, better compliance is expected; hence, the outlined outcome should be improved accordingly. Compliance is, apart from the quality of treatment planning and difficulty of the teeth movements, increasingly one of the most crucial aspects of achieving treatment goals, especially for aligner treatments, which are on a significant popularity rise. Furthermore, when a patient is being self-scanned on a 4-, 7-, 10-, or 14-day basis, he is also aware that the hygienic status of his teeth will be assessed and visible to the doctor, assistants, and even third party (the software staff as well), which, overall, leads to improvement in his dental hygiene . The software uses a knowledge-based algorithm that evaluates the data patients send to the app after taking a series of photos with their smartphone. An automatic preset for feedback and comments is then sent back to the patient, containing a lot of data for the patient about their current dental status . Unlike other telecommunications systems such as Skype, Google Duo, Zoom, and others , which cannot provide a standardized evaluation of the clinical situation, the DM system provides process automation through a knowledge-based algorithm that is based on a combination of robotic and deep learning processes, with information systems that act like a semi-intelligent user . The aim of this article was to investigate the use of advanced AI software in orthodontics, particularly for the purposes of CBCT diagnosis and assessment, treatment progress assessment, and outcome stability in the follow-up phase. We evaluate the accuracy and efficiency of these AI tools compared to conventional methods and discuss the potential benefits of using such software in orthodontic practice, including the ability to closely monitor each patient, set specific treatment goals and track their achievement, and detect changes in occlusion, jaw translation, and tooth movement. The secondary objective was to summarize reported limitations of implemented AI-powered systems in orthodontics. 2. Materials and Methods 2.1. The Research Question The question for the literature research was defined specifically enough to allow the review team to identify relevant studies, but broadly enough to capture the full scope of the topic being reviewed. How are AI systems currently assisting the assessment of the treatment or retention of orthodontic treatment clinically implemented, and what are their advantages and limitations? 2.2. The Search Strategy The search strategy aimed to identify all relevant studies on the topic being reviewed. This involved searching databases and grey literature to ensure that this review was as comprehensive as possible. For this review, PubMed, Scopus, the Web of Science--Core Collection, and Google Scholar were queried. The query was developed in dialogue with AI ChatGPT 3.5 Dec 15 Version (OpenAI Inc., San Francisco, CA, USA). Databases were queried on 20 December 2022 with the following query: (orthodontic treatment OR orthodontics) AND (artificial intelligence OR machine learning OR deep learning) AND (assessment OR evaluation OR prediction) AND (course OR retention OR outcomes) The definition of the query was suggested upon drafts of this review title, abstract, and defined research question and was accepted by all four evaluators. This search query would find articles that discuss the use of artificial intelligence systems in evaluating the course and retention of orthodontic treatment and contain the relevant terms "orthodontic treatment", "artificial intelligence", "evaluation", and "course" or "retention". 2.3. The Review Process All studies returned by search were analyzed for duplicities followed by analysis from four evaluators for title and abstract evaluation. Only studies relevant to the topic were selected, and relevant data were extracted. 3. Results All articles below dating before 2020 were eliminated from the study, as only the most contemporary and relevant data were to be gathered. We excluded 17 articles that complied with queried keywords but were not addressing the topic even marginally. Table 1 shows most cited articles relevant to the queried keywords. 3.1. Cephalometric Landmark Detection and Placement by Artificial Intelligence Multiple studies confirmed a wide range of software enabling recognition and detection and automatic placement of cephalometric landmarks, detecting pathologies using CBCT images, pathologies ranging from tumors, cysts, periapical lesions, caries, supernumerary teeth, tissue alterations as present in infectious processes, and abscess formations. In various measurements, they compared the accuracy of these evaluations to the skills of a trained dentist, all showing more than 95% compatibility with the findings of the dentists . Juerchott et al. are also studying whether MRI can serve as an alternative to CBCT for 3D cephalometric analysis. Mean values were found to be equivalent, which supports this thesis, which could possibly reduce radiation exposure for many patients . Moreover, segmentation of the facial skeleton was carried out by automatized MS-D convolution networks then compared to a segmentation set by orthodontists; the mean difference was insignificant, whereas the amount of time needed for segmentation was about 5 h for 1 CBCT for an orthodontist and 25 s for the CNN. This study showed that an incredible amount of time was possibly saved by this AI . Ren et al. gathered data that also claim AI and deep machine learning is not already utilized for a cephalometric landmark, but it is already being used for determination of cervical vertebrae stages, oral cancer detection, cancer margin assessment, its prognosis, dental caries detection, root morphology, the presence of periapical lesions, and facial attractiveness evaluation . 3.2. Dental Monitoring System Applications A study by Dallesandri et al. studied the approach of patients and dentists toward a DM system throughout their orthodontic treatments. Collected data showed that all dentists judged telemonitoring positively, as 96.25% of them considered telemonitoring indicative of high-tech and high-quality treatment, and 100% considered it a way to reduce the number of in-office visits. In addition, 97.5% of patients judged telemonitoring positively; 81.25% of them considered telemonitoring indicative of high-tech treatment; 81.25% declared themselves to be interested in reducing the number of in-office visits through telemonitoring. Telemonitoring was assessed as plausible both by patients and dentists; it was also understood as a high-tech tool that could improve quality and effectiveness of the treatments. Both groups were also pleased by possibly reducing the number of in-office visits. However, additional funding for this utility from the side of the patient was less welcomed, and compliance would be put to the question if such was the case . Caruso et al. carried out a two-case study where they assessed treatments of patients using DM. Both patients displayed good compliance and successfully reached all established treatment goals. The needed movements were difficult to achieve, yet, owing to being able to be monitored, they completed treatment quickly; they both followed a seven-day exchange protocol, which is slightly faster than the usually observed treatment speed. There were phases in treatment when it was necessary to prolong the time on each aligner, while maintaining adequate tracking. After this period, the speed adaptively returned to the previous schedule. Patients assessed that monitoring was easy to use; it detected debonding auxiliaries and thus improved quality of the treatment . Impellizzeri et al.'s study suggests that using DM with 0.014 x 0.025 CuNiTi wires in a self-ligating straight-wire appliance successfully reduced the number of appointments for each patient from 3 appointments in 10 weeks to 2 per 10 weeks. Naturally, a reduction in chair time and material costs was observed. Moreover, more precise evaluation of treatment by the doctor was possible . Another study by Sangalli et al. revealed that when patients were equipped with a cheek retractor and scan box by Dental Monitoring and instructed to take monthly intra-oral scans, this study group of patients showed a significant improvement in plaque control compared to the control group. A decreased number of emergency appointments in the study group was also registered, although it was not significant. The patients were not orthodontic treatment cases . Maspero et al., in a 2020 article, confirmed that this application saved 5.8 appointments over a 2-year treatment. Its software platform was observed by patients as user-friendly and they noted improvement of communication with the doctor. Moreover, it was observed that stability of the result could also be measured and, if relapse of misalignment of the teeth were to occur, swift measures could be enacted to interfere with relapse development. Measurement was carried out by Moylan et al. in 2019. They compared intercanine and intermolar measurement differences between plaster models based on impressions taken by a dentist versus measurements from data from Dental Monitoring software. The differences ranged from 0.17 mm and -0.02 mm; this was assessed as sufficiently accurate . Another publication measured the difference in STL (Stereolithography) files provided from the iTero scanners and STL files generated by DM software. Differences ranged from 0.0148 mm to 0.0275 mm; thus, they safely stated the method is accurate enough for clinical applications . 3.3. Other AI and Teldentistry Applications An article by Achmad utilized teledentistry in order to connect with distant patients for consultations throughout the COVID-19 pandemic, which was exceptionally well-accepted by both groups . Another purpose of teledentistry was documented by Deshpande et al., who found out that if trained general dentists were remotely communicating with orthodontists via teledentistry, more accurate interceptive orthodontic treatments would be made available, which thus led to a reduction in severity of malocclusions in disadvantaged children where referral was not plausible. Moreover, unnecessary referrals were filtered out, which is an advantage both for specialist and patient. They also warn of the risk that diagnosis based on clinical photography made by the patient may not be accurate, and the practitioner may not collect all necessary data, since other diagnostic procedures such as percussion and palpation cannot be performed via photography . Asiri et al. summarized in their review that most commonly utilized AI domains were intended for diagnostics and treatment planning, followed by automated anatomic landmark detection used for cephalometry. Marginally, AI was used for assessment of growth and development and evaluation of treatment outcome . 4. Discussion Contemporary data show that there is a growing trend towards the use of telemedicine in modern dental and orthodontic practices, as it has been proven to increase efficiency and allow dentists to specifically monitor each case and focus on the most important goals for each patient, while saving chairside time and patient resources and preventing deterioration of their dental status, from which they also benefit financially, psychologically, and esthetically. Likewise, the quality of treatment is improved, and the time needed to resolve problems is reduced. Although the benefits for the patient are not yet fully known, since the willingness to use the modern aids is not yet as high as the doctor would like, the demand is increasing . The availability for the patient and the practice is indeed very high: the only technical requirement for the patient is a smartphone and an internet connection. The rest is provided by the dental practice. Patient compliance is also statistically higher. Undoubtedly, more and more applications will be developed to facilitate the treatments even more and increase the comfort for the user during the treatment . In comparison with conventional methods of treatment management, physicians will be able to increase the number of patients they can treat at one time without compromising the quality of the services provided. They can, in fact, observe the patient's dental status more often, with great detail, instruct the patient remotely to aid in his or her treatment, or change instructions for further steps, e.g., change of placement of inter-maxillary elastics. They do not have to rely on a patient s observation skills in terms of debonding of brackets, attachments, or other auxilliars, and problems can be detected much sooner than 3-4 weeks of the next appointment. Moreover, the treatment doctor can very quickly detect the first signs of relapse of the malocclusion, even at the slightest movement of a singular tooth. In addition, improved compliance is observed through the use of the new, attractive AI software. Finally, the ability to seek treatment over long distances is highly desirable, both for patients who travel frequently or live abroad and during pandemics such as those that have occurred in recent years . Additionally, when comparing traditional diagnostic methods, the use of AI systems can speed up and enhance even the development of complicated orthognathic surgery treatment planning, where fast cephalometric tracing is performed by software. Jaw segmentation is also faster when performed by AI then by even skilled practitioners. Furthermore, dental and skeletal pathologies can be detected easier and not be omitted from an orthodontist's line of sight, as during cephalometric analysis his focus is mostly on the landmarks and bigger picture of a patient s skeleton rather than singular teeth. The combination of AI and teledentistry introduces a historical paradigm shift in orthodontic care. Software enhanced by advanced AI provides not only sophisticated evaluations of clinical situation and post-treatment stability but also pre-treatment diagnostics or even automated segmentations of CBCT utilized for cephalometric , airway , or forensic applications . AI-powered software for orthodontic cephalometric analysis recently became a common tool for a reliable and accurate cephalometric tracing method , which represents a significant evolution from the times of analog cephalometric processing . This review identified several limitations to using AI-powered systems in orthodontics:Accuracy: AI-powered systems can help with diagnosis and treatment planning, but they are not as accurate as a trained orthodontist in identifying and treating complex cases , although some reports have shown that the level of accuracy is nearing the human level. Expertise: AI systems do not have the same level of clinical expertise as a trained orthodontist. They may not be able to fully understand the patient's needs and cannot provide the same level of individualized care . Ethical concerns: There are also ethical concerns about the use of AI in healthcare, including the possibility of biased algorithms and the potential to replace human labor with automation . Cost: AI systems can be expensive to implement and maintain and may not be accessible to all patients or clinicians. Regulation: the use of AI in healthcare also comes with regulatory challenges. These include the need for oversight to ensure the accuracy and safety of AI-powered systems . A limitation of this paper is that there is a wide range of different attributes and parameters that could be used to evaluate the benefits to both parties, and further studies should be conducted that explore each parameter in more depth. This paper also highlights that the use of AI software in orthodontics raises questions about reliability, as these tools can contain errors and bias that can lead to mistakes or mishaps during treatment. The review included most impactful studies on the use of AI in orthodontics and summarized the characteristics of current software alternatives. The accuracy and expertise have been evaluated as sufficient, albeit a sufficient number of studies on this matter have not been published yet. The value of AI-powered monitoring of the orthodontic retention phase is not completely appreciated yet and very few studies are focusing on this aspect. The authors of this paper see unexplored potential in this direction. Current clinical decision support systems in orthodontics are already supported by AI. Commercial companies that manufacture clear aligners use data from millions of digital intraoral scans sent by clinical providers and apply AI algorithms to predict and plan tooth movement after they perform tooth segmentation. However, such AI algorithms are not validated and require clinicians to exercise caution when using the predictions provided and monitoring treatment outcomes . Scientific reviews mapping the clinical application of orthodontic AI show a significant increase since 2020, recognizing the potential to support the assessment of orthodontic treatment and retention in a variety of ways. This has been accelerated by the global pandemic and technological AI breakthroughs. In 2022, AI algorithms were used to analyze and interpret digital images and diagnostic data, such as dental radiographs, photographs, CBCT, or intraoral photos and video scans, to identify problems and predict treatment course, outcome, or stability. AI has also been widely used to monitor patients during treatment and provide real-time feedback and alerts to ensure treatment is going as planned. AI-based systems and their application have even reached university orthodontic curricula . In addition, AI can be used to help orthodontists track and analyze patient data over time, allowing them to identify trends and patterns that may be useful in predicting treatment outcomes and optimizing treatment plans. This could be especially useful for patients with complex or difficult cases, where traditional methods of assessment may not be sufficient . Non lege artis treatment can take many forms, such as using treatments that have not been proven effective, using treatments in an inappropriate or dangerous manner, or failing to follow accepted protocols for diagnosing or treating a particular condition. Such treatment may also involve exploitation or abuse of patients, such as taking advantage of their vulnerability or trust. AI implementations in orthodontic software are no exception. In 2023, the European Union announces the idea of creating the world's first comprehensive standards for regulating or prohibiting certain applications of artificial intelligence . The EU's AI law is expected to lead the world in regulating AI. The AI Act is a proposal for a European law on artificial intelligence (AI)--the first law on AI to be passed by a major regulator. The law assigns applications of AI to three categories of risk. First, applications and systems that pose unacceptable risk, including state-run social assessments such as those used in China, are banned. Second, high-risk applications, such as a CV scanning tool that ranks job applicants, are subject to specific legal requirements. Finally, applications that are not explicitly banned or classified as high-risk are largely unregulated . 5. Conclusions The use of AI in the assessment and retention of orthodontic treatment is an emerging area with significant potential for improving patient care and outcomes. It is likely to see many more AI-powered tools and systems being developed and adopted in the field of orthodontics in the coming years. Literature research concludes that while AI-powered systems already effectively assist in orthodontic treatment, they must be used in conjunction with properly trained orthodontists to achieve the best possible outcomes for patients. Unsupervised applications of AI-assisted systems in orthodontics are not in accordance with the standards of good medical practice or the principles of medical ethics. With current unresolved risks of AI bias and incoming AI governmental regulations, such an unsupervised orthodontic treatment would be considered as non lege artis. This scoping review proves that the current clinical adoption of AI-powered systems has already reshaped the form of modern orthodontic practice, albeit they are still rife with limitations such as: accuracy, expertise, ethical concerns, cost, and regulatory issues. Acknowledgments The authors gratefully acknowledge the technological support of the digital dental lab infrastructure of the 3Dent Medical Ltd. company, (Bernolakovo, Slovakia) as well as the dental clinic, Sangre Azul Ltd., (Chiyoda City, Tokyo). Author Contributions Conceptualization, A.T., M.S., R.U. and J.S.; methodology, A.T.; software, A.T.; validation, A.T., M.S., R.U. and J.S.; formal analysis, A.T.; investigation, resources, A.T.; data curation, A.T. and J.S.; writing--original draft preparation, A.T., M.S., R.U. and J.S.; writing--review and editing, A.T., M.S., R.U. and J.S.; visualization; supervision, A.T.; project administration, A.T.; funding acquisition, A.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. healthcare-11-00683-t001_Table 1 Table 1 The most cited articles relevant to the queried keywords in researched topic. # Authors Title Citations FWCI Reference Published 1 Kunz et al. Artificial intelligence in orthodontics: Evaluation of a fully automated cephalometric analysis using a customized convolutional neural network 65 12.89 2020 2 Maspero et al. Available technologies, applications and benefits of teleorthodontics. A literature review and possible applications during the COVID-19 pandemic 59 3.44 2020 3 Yu et al. Automated Skeletal Classification with Lateral Cephalometry Based on Artificial Intelligence 57 10.21 2020 4 Lee et al. Automated cephalometric landmark detection with confidence regions using Bayesian convolutional neural networks 40 7.51 2020 5 Leite et al. Radiomics and Machine Learning in Oral Healthcare 38 1.83 2020 6 Wang et al. Multiclass CBCT Image Segmentation for Orthodontics with Deep Learning 27 11.36 2021 7 Bichu et al. Applications of artificial intelligence and machine learning in orthodontics: a scoping review 20 6.35 2021 9 Schwendicke et al. Deep learning for cephalometric landmark detection: systematic review and meta-analysis 18 3.06 2021 10 Deshpande et al. Teledentistry: A boon amidst COVID-19 Lockdown--A narrative review 16 1.67 2021 11 Ahmed et al. Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry--A Systematic Review 16 1.34 2021 12 Mohammadad-Rahimi et al. Machine learning and orthodontics, current trends and the future opportunities: A scoping review 14 4.34 2021 13 Juerchott et al. In vivo comparison of CBCT-based 3D cephalometric analysis: beginnning of a non-ionizing diagnostic era in craniomaxillofacial imaging? 14 1.44 2020 14 MacHoy et al. The ways of using machine learning in dentistry 14 0.84 2020 15 Ren et al. Machine learning in dental, oral and craniofacial imaging: A review of recent progress 13 1.39 2021 18 Dalessandri et al. Attitude towards telemonitoring in orthodontists and orthodontic patients 11 4.8 2021 20 Caruso et al. A knowledge-based algorithm for automatic monitoring of orthodontic patients: The dental monitoring system. Two cases 10 1.81 2021 21 Impellizzeri Dental Monitoring Application: I tis a valid innovation in the Orthodontics Pracice? 9 0.86 2020 22 Monill-Gonzalez et al. Artificial intelligence in orthodontics: Where are we now? A scoping review 9 2.58 2021 23 Thurzo et al. Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis 8 5.15 2022 24 Bulatova et al. Assessment of automatic cephalometric landmark identification using artificial intelligence 3.72 2021 25 Park et al. Teledentistry platforms for orthodontics 8 3.39 2021 26 Sangalli et al. Effects of remote digital monitoring on oral hygiene of orthodontic patients: a prospective study 7 3.05 2021 27 Achmad et al. 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PMC10000480 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050711 cells-12-00711 Article Ezrin and Its Phosphorylated Thr567 Form Are Key Regulators of Human Extravillous Trophoblast Motility and Invasion Tabrizi Maral E. A. 1 Gupta Janesh K. 23 Gross Stephane R. 1* Rivero Francisco Academic Editor 1 School of Life and Health Sciences, Aston University, Birmingham B4 7ET, UK 2 Institute of Metabolism and Systems Research, University of Birmingham, Birmingham B15 2TT, UK 3 Fetal Medicine Centre, Birmingham Women's NHS Foundation Trust, Birmingham B15 2TT, UK * Correspondence: [email protected]; Tel.: +44-0121-204-3467 23 2 2023 3 2023 12 5 71106 1 2023 16 2 2023 17 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The protein ezrin has been shown to enhance cancer cell motility and invasion leading to malignant behaviours in solid tumours, but a similar regulatory function in the early physiological reproduction state is, however, much less clear. We speculated that ezrin may play a key role in promoting first-trimester extravillous trophoblast (EVT) migration/invasion. Ezrin, as well as its Thr567 phosphorylation, were found in all trophoblasts studied, whether primary cells or lines. Interestingly, the proteins were seen in a distinct cellular localisation in long, extended protrusions in specific regions of cells. Loss-of-function experiments were carried out in EVT HTR8/SVneo and Swan71, as well as primary cells, using either ezrin siRNAs or the phosphorylation Thr567 inhibitor NSC668394, resulting in significant reductions in both cell motility and cellular invasion, albeit with differences between the cells used. Our analysis further demonstrated that an increase in focal adhesion was, in part, able to explain some of the molecular mechanisms involved. Data collected using human placental sections and protein lysates further showed that ezrin expression was significantly higher during the early stage of placentation and, importantly, clearly seen in the EVT anchoring columns, further supporting the potential role of ezrin in regulating migration and invasion in vivo. ezrin motility trophoblasts migration invasion cytoskeleton placenta Research Group and Biomedical Sciences Research funding schemes at Aston UniversityLife and Health Sciences PhD studentshipThis work was supported by grants from both the Research Group and Biomedical Sciences Research funding schemes at Aston University and a Life and Health Sciences PhD studentship to M.E.A.T. pmc1. Introduction During the early stage of development, trophoblast invasion into the decidualised endometrium is a key regulator to establish the precursor of the placenta, the first step of implantation. During this phase, the controlled invasion and migration of extravillous trophoblast cells (EVT) into the maternal decidua is a vital aspect of placental development. Shallow invasion has been linked to poor supplies of both blood and nutrients to the developing foetus, whilst excessive invasive trophoblast cells lead to the loss of the normal plane of cleavage from the uterine wall and massive haemorrhage at delivery. Both of these conditions have been shown to ultimately lead to pregnancy complications such as placenta accreta, preeclampsia, and foetal growth restriction. A factor whose expression has been linked to foetal growth restriction is the ezrin protein . Ezrin is a member of the ERM (ezrin, radixin, moesin) protein family that has been shown to function as an important linker protein between F-actin filaments in the cellular cortical layers and membrane-associated proteins on the cell surface . Among different functions, ezrin has been shown to be a key regulator of plasma membrane activities such as cell shape and cell surface structure , as well as cell adhesion and cellular migration/invasion . Significant work has now established the molecular signature of the ezrin protein and demonstrated how the different domains found within are responsible for some of its functions. An N-terminal four-point-one, ezrin, radixin, moesin (FERM) region facilitates the interaction, either directly or indirectly, of ezrin with transmembrane domains, and in doing so, allows for anchoring to the plasma membrane. The C-terminal region of ezrin interacts with cortical F-actin . The unmodified full length ezrin protein is usually found in a dormant configuration and not bound to actin due to the masking of the actin-binding domain at the C-terminus by its own N-terminal FERM region . One the other hand, the phosphorylation of the residue threonine Thr567 and/or the addition of phosphatidylinositol bisphosphate leads to conformational changes that uncover the C-terminus region and therefore promote binding to cortical F-actin. The interaction of ezrin with F-actin has been significantly studied in the cancer setting, where ezrin is thought to facilitate cancer cell motility and invasion . Elevated levels of ezrin are considered to be an important step towards carcinogenesis with increased levels seen in prostate and pancreatic cancer, to highlight just a few . There is also a clear link between high expression and the metastasis of numerous solid tumours . A role for ezrin in the reproduction field is, however, much less characterised. Ezrin has been suspected to play a role in blastocyte adhesion and has been shown to be distinctively expressed in the primitive endoderm as well as the trophectoderm cell surface . It has been shown in placental microvilli of human and rat origin , where it is a major component of actin cytoskeletal structures. Ezrin is the most abundant of the ERM proteins and has been reported to be expressed in the apical membrane of syncytiotrophoblasts in the microvillous membranes . It was initially discovered and characterised in choriocarcinoma trophoblast Jeg-3 cells but also found in BeWo cells as well as in extravillous and villous trophoblasts . The roles and functions of ezrin in trophoblast and placental development are, however, not clear, especially in the early stages of gestation. Significant similarities have been highlighted between the physiological process of trophoblast invasion during placental implantation and the pathological effects of cancer invasion . The functions of proteins known as metastasis-inducing proteins (MIP) such as S100P have been liked to trophoblast migration . Given the importance of ezrin expression and Thr567 phosphorylation as key regulators of cellular motility and cancer metastasis, we sought to determine whether ezrin could equally contribute to cellular motility and invasion in the context of EVT cells. In this study, we show that reducing either ezrin protein levels and/or its phosphorylated activated form, through the use of siRNA delivery and/or specific inhibitors, respectively, leads to a significant reduction in EVT lines and primary cells' abilities to both migrate and invade with significant changes made to key motile markers of their cytoskeletal organisation. We further show that levels of ezrin are significantly increased in the early stages of human placental implantation and its expression can be clearly seen in EVT anchoring columns, indicating that this protein may be a key regulator of the physiological process of trophoblast implantation, offering a yet-unexplored role for ezrin in non-diseased states. 2. Materials and Methods 2.1. Human Placental Tissues All the works using placental samples were performed in accordance with the ethical principles for medical research outlined in the Declaration of Helsinki 1964 and per subsequent revisions accessed on 5 June 2018). Samples of placenta tissues obtained either after the elective termination of pregnancy from the first trimester (n = 3) or second trimester of gestation, (n = 3) as well as after delivery (n = 4) were collected with approval by the National Research Ethics Service (NRES) Committee North West--Haydock (study approval number 13/NE/2005). Samples were fixed in 4% (w/v) paraformaldehyde and embedded in paraffin wax prior to further processing. Samples of placenta tissues for EVTs isolation were obtained immediately after the elective termination of pregnancy from the first trimester of gestation (8-12 weeks). Placental samples were collected with the approval of the Health Research Authority--West Midlands, Edgbaston Research Ethics Committee (NHS REC 15/WM/0284 and AHRIC REF 1245-SG). All samples and tissues were collected in accordance with relevant guidelines and regulations and written informed consent was obtained from all women recruited into the study. 2.2. Cell Lines and Culture Cells lines used were characterised as first-trimester extravillous trophoblasts EVT HTR8/SVneo, Swan71, and SGHPL4/SGHPL5, which were all kind gifts from Prof. Charles Graham (Queen's University, Canada), Prof. Gil Mor (Yale University, USA) and Prof. Guy St J. Whitley (St George's, University of London, UK), respectively. Jeg3 cells and BeWo are well-characterised choriocarcinoma cells which were obtained from Dr Emmanuel Karteris (University of Brunel, UK). Cells were cultured in their respective media, as previously described . NSC668394 was purchased from Merck (UK) and prepared/used as previously described . 2.3. EVT Purification The protocol for isolating EVTs was adapted as previously described . Briefly, first-trimester placental samples were gently washed in Ham's F12 (Sigma, Welwyn Garden City, UK). Chorionic villi were physically separated and digested in 0.25% (w/v) trypsin solution (Sigma, UK). Placental tissue was filtered and diluted in 25% (v/v) FBS in Ham's F12 medium (Sigma, UK) before centrifugation for 5 min at 450x g. The supernatant was discarded and the pellets were pooled and resuspended before being layered over a Pancoll solution (Pan Biotech, Aidenbach, Germany. Density 1.077 g/mL). Samples were spun at 750x g for 20 min and the EVT band was aspirated and collected into clean tubes prior to a final centrifugation at 500x g. The resulting EVTs were resuspended in trophoblast complete medium (TCM; Ham's F12 without Phenol red, 20% (v/v) FBS, 100 units and 0.1 mg/mL penicillin/streptomycin, 2 mM L-Glutamine), seeded onto 35 mm tissue culture dishes, and left to settle overnight before changing the medium to fresh TCM. 2.4. siRNA Ezrin and Control Delivery Cells seeded in 24-well plates were grown to 25-50% confluency before being transfected with double-stranded siRNA (Qiagen, Manchester, UK) for ezrin (siRNA 7: SI02664228) and siRNA 9 (SI04384170)) or with a mock control siRNA (SI03650318) in OptiMEM (Gibco, Paisley, UK) and normal medium using INTERFERin transfection reagents (Polyplus, Illkirch-Graffenstaden, France). The concentration of siRNA used throughout the experiments was 5 nM. Cells were left in the presence of the different siRNAs for 72 h prior to collection for Western blotting analysis. For motility/invasion and immunostaining, cells were left to grow for 48 h prior to starting the analysis. 2.5. Western Blotting Cell lysate samples were collected by either scrapping or homogenisation, respectively, in 1x PBS with protease inhibitors prior to sonication and dilution in 5x Laemmli buffer and equal loading (15 mg), then separated onto 10% (w/v) polyacrylamide gels and transferred to PVDF membranes with 80 mA per blot for 2 h prior to blocking in blocking buffer (3% (w/v) BSA in PBS). Ezrin/phospho Thr567-ezrin, a-tubulin antibodies (all from Abcam, UK; See supplementary Table S1), as well as moesin and radixin (Insight Biotech, Wembley, UK; See supplementary Table S1), were diluted in blocking buffer and incubated overnight at 4 degC, prior to washing and incubation with the relevant secondary antibodies conjugated to HRP and ECL development (anti-mouse or anti-rabbit, Dako and Sigma, Ely, UK). Original, uncropped, and unadjusted images are available as Supporting Information in Supplementary Figure S2. 2.6. Immunofluorescent Staining Immunofluorescence was carried out as previously described . Briefly first-trimester trophoblast HTR8/SVneo, Swan71, or SGHPL4/SGHPL5 as well as BeWo or Jeg-3 cell lines, either untreated or 48 h following treatments, were plated at a concentration of 15 x 103 cells/well onto fibronectin-coated (2.5 mg/cm2) glass coverslips in a 24-well plate. The cells were washed once in cytoskeleton buffer (CB: 150 mM NaCl, 5 mM MgCl2, 5 mM EGTA, 5 mM glucose, 10 mM 2-(N-morpholino)ethanesulfonic acid, pH 6.1) and fixed with 3.7% (w/v) paraformaldehyde in CB at 37 degC for 20 min, followed by permeabilisation with 0.1% (v/v) Triton X-100 in CB for 10 min. Blocking solution (5% (v/v) goat serum in CB) was added and incubated for 60 min. Primary antibodies against ezrin/phospho Thr567-ezrin (Abcam, Cambridge, UK) and paxillin (Invitrogen, Paisley, UK) (Supplementary Table S1) were incubated for 45 min at 37 degC. After washing three times with blocking solution, the cells were incubated with the appropriate secondary anti-rabbit or antibodies labelled with FITC or TRITC (Dako, Ely, UK), respectively, in blocking solution for 45 min at 37 degC. For actin staining, rhodamine phalloidin (Invitrogen, Paisley, UK) was also added with secondary antibodies at a concentration of 0.6 mm. After washing with blocking solution, coverslips were rinsed once with water and mounted in Vectashield mounting medium (Vector Labs, Peterborough, UK) before being viewed using an Epifluorescence Leica DMI400B microscope. Regions of specific cellular localisation were magnified 13x to highlight distinctive morphologies. Focal adhesion numbers as well as cell numbers were counted on each image to quantify the average focal adhesion count per cell. 2.7. Immunohistochemistry Immunohistochemical staining for ezrin and counterstaining were performed on human placental tissues, as previously described . Tissue sections were deparaffinised, and heat-induced antigen-retrieval was performed in citrate buffer (pH 6.0) using a pressure cooker (Prestige Medical, Blackburn, UK). Non-specific protein binding was blocked by incubation with 10% (v/v) normal goat serum (Vector Labs, UK) for 1 h. Primary antibody against ezrin (Abcam, UK), anti-HLA-G antibody (Abcam, UK), or an anti cytokeratin7 antibody (Leica Biosystems, Newcastle Upon Tyne, UK) were carried out at 4 degC overnight (Supplementary Table S1). After washing in 0.1% (v/v) Tween 20 (Sigma-Aldrich, Gillingham, UK) in Tris-buffered Saline pH 7.4, sections were then incubated with the appropriate second antibody conjugated to horseradish peroxidase (HRP). The staining was analysed by using a Nikon inverted microscope and Image-J analysis software. The quantification was performed using the Optical Density Calibration--ImageJ software 1.52a accessed on 4 September 2022). First, optical density (OD) was calibrated on FIJI-Image J, and then the images were analysed by selecting the following options: Image, Colour, Colour Deconvolution, and H DAB. Then, "Colour_2", which shows the brown DAB staining, and therefore is the equivalent of the expression of the protein of interest, was used to measure the OD. The desired areas in each image were selected through Analyse, Tools, ROI manager and by manually choosing the areas with tissues. The OD in each image was measured by selecting Analyse and then Measure. Finally, the average ODs from each trimester were compared with each other. To quantify the ratio of ezrin-positive pixels to total pixels in each image, Colour Deconvolution and H DAB were selected in Image J. Then, the threshold was automatically adjusted on "Colour_2" (DAB), and the DAB-positive pixels along with total pixels per image were measured. 2.8. Motility/Invasion Assay Motility and invasion abilities were measured using Boyden polycarbonate transwell membranes, as described previously . Following siRNA treatment for 48 h or NSC668394 and serum deprivation by growing the cells in 0.5% (v/v) FBS-containing medium for a further 24 h, 25 x 104 or 50 x 104 cells, for Swan71 and HTR8/SVneo, respectively, were seeded in 0.5% (v/v) FBS-containing medium on 8 mm polycarbonate transwell membranes (Greiner, Stonehouse, UK) without (motility) or with congealed Matrigel (invasion; Sigma, UK) against a gradient of 5% or 10% (v/v) FBS medium in the outer wells for HTR8/SVneo and Swan71, respectively. Cells were left to migrate through the membrane for 24 h prior to fixing and staining using a Diffquik histochemical kit (Reagena, Toivala, Finland) following the manufacturer's instructions. The stained cells on the lower side of the membrane were counted using a light microscope with a 20x objective lens, selecting 5 random fields. Data for this experiment are presented as the mean values +- S.E. relative to controls (percentage) from 4 replicate wells for each set of conditions. 2.9. Trypan Blue Exclusion/MTT Conversion To measure the cell growth rate, 15 x 103 HTR8/SVneo and Swan71 cells were seeded in 24-well plates along with the desired treatments, as described earlier, and left to grow for 24-72 h. For the trypan blue exclusion, wells were washed once with PBS and trypsinised prior to being counted using a haemocytometer. MTT in PBS (Thermo Fisher Scientific, Oxford, UK) was added into each well for 1 h prior to cells being washed in PBS and solubilised in DMSO. Absorbance was measured at 570 nm using a plate reader (BioTek Potton, Peterborough, UK). Data for this experiment are presented as the mean values +- S.E. relative to controls (percentage) from 4 replicate wells for each set of conditions. 3. Results 3.1. Ezrin Is Expressed in Human Extravillous Trophoblasts in Anchoring Columns In Vivo The high expression of ezrin has been shown during blastocyst activation prior to implantation, being found in the apical domains of the outer cells during blastocyst formation . The expression of ezrin in extravillous and villous trophoblasts has also been reported before (mRNA and protein levels) , but no information is available, to our knowledge, to detail ezrin's localisation during gestation, especially in the early stages of trophoblast invasion in the anchoring columns. Human placental sections from the first and second trimesters, as well as at term, were processed using immunohistochemistry staining for ezrin as well as the trophoblast markers cytokeratin 7 and HLA-G . Significant differences in expression were found between the different stages of pregnancy. These changes could be seen at the protein levels either by Western blotting or after immunohistochemistry , resulting in a 45% decrease in the levels of ezrin as gestation progresses to term. Levels of ezrin were significantly reduced throughout the gestational period between the first trimester and second trimester (p = 0.0027 for Western blot analysis and p = 0.0014 for immunohistochemistry quantification) or at term (p < 0.0001 for Western blot analysis and p < 0.0001 for immunohistochemistry quantification). Further analysis of the immunohistochemistry was conducted using the percentage of cell positivity quantifications to analyse expression levels in the different trophoblast subtypes (Table 1). As a whole, we found that significant reductions were seen from both the first and second trimesters compared to full term (p < 0.001 and p < 0.01 respectively). It is interesting to note that these significant changes in ezrin expression throughout gestation were also found across the majority of the different trophoblast subsets, as all cytotrophoblasts, syncytiotrophoblasts, and proximal column extravillous trophoblasts showed a significant reduction in protein levels as the pregnancies progressed (Table 1). At the cellular level, ezrin was found mainly in the cytoplasm of cytotrophoblasts and syncytiotrophoblasts, with the highest levels seen in the apical membranes of the syncytiotrophoblasts . To further establish if ezrin could also be found in extravillous trophoblasts (EVT) and invasive anchoring columns, samples were analysed using serial sections of placental villi from the first trimester . HLA-G was used as a prominent marker of EVT and its expression was clearly visible at the tip of the anchoring columns. Interestingly, high levels of ezrin were found in these cells, although, unlike HLA-G, the staining was also observed in cells at the proximal and middle ends of the anchoring columns. Expression was also seen in the proximal syncytiotrophoblasts. Taken together, these results show that the ezrin protein is predominantly expressed in the trophoblast cells, including the extravillous trophoblast subsets and their anchoring columns, and that ezrin levels appear to be highest at times when trophoblasts are the most invasive during the early stages of placental implantation. 3.2. Expression and Localisation of Ezrin in Trophoblast Cell Lines Having shown that ezrin is found to be expressed in EVT cells in human placental sections, we sought to establish whether ezrin could also be seen in cell lines in order to provide a tractable experimental system. Using a panel of lines, including the choriocarcinoma cell lines Jeg-3 and BeWo, and the EVT cells HTR8/SV neo, Swan71, SGHPL4, and SGHPL5 cells, we sought to analyse both ezrin expression levels as well as its subcellular location. Western blot analysis was performed and quantification was assessed . Robust and similar expressions of ezrin were seen in all cells tested. Immunofluorescence was also carried out to seek further information about ezrin's cellular localisation . In the Jeg-3 cells, ezrin was found mainly in the cytoplasmic and pericellular organisation, whilst the EVT-like cells demonstrated a very specific localisation with an abundant presence of ezrin in protrusions. These extensions were particularly extensive in number and length in the HTR8/SVneo and Swan71 cell background (Table 2). Ezrin activation and its ability to bind both to membrane and cytoskeletal structures are regulated by conformational changes. Intramolecular interactions in the C-terminal domains mask the actin-binding sites , but the phosphorylation of a conserved threonine residue at position 567 releases this inhibition and results in the relocalisation of the protein to the actin-rich membrane extensions . To determine the extent of Thr567 phosphorylation in the different trophoblast cell lines, we measured its levels and its cellular localisation. A significant difference in the levels of phosphorylated Thr567 ezrin was seen across the different cells, with HTR8/SVneo trophoblasts demonstrating high levels of the phosphorylated proteins, whilst the Swan71 cells, in contrast, offered much lower levels . It is also interesting to note that beyond the different levels of Thr567 phospho-ezrin in the trophoblast cell lines, there were some equally clear changes in the migration patterns of the different proteins, suggesting, most likely, changes in post-translational modifications, including phosphorylation at Thr567 in these cell populations . Choriocarcinoma Jeg-3 cells showed important levels of phosphorylated Thr567 ezrin, and these proteins were seen as intense clusters in the cytoplasm and pericellular space, as well as defined fibrillary foci at the membrane periphery . EVT-like cells HTR8/SVneo and SGPHL4 demonstrated the localisation of phosphorylated Thr567 ezrin either in the nucleus or in very defined cellular microvilli structures at the cell periphery, most of them colocalising with the actin cytoskeleton . Interestingly, staining in the Swan71 cells was similar to that of the other EVT-like cells, but much weaker across, still presenting defined protrusion structures, which were also more difficult to observe, and confirming the low phosphorylated Thr567 ezrin levels seen . These data demonstrate that endogenous levels of ezrin, as well as its phosphorylated form, can be detected in all trophoblast cell lines and can therefore be used as models to silence ezrin expression. Given that HTR8/SV neo and Swan71 cells are some of the best-characterised EVT models and given the significant differences between the levels or localisation of both ezrin and its phosphorylated Thr567 state in these two cells, we decided to use both lines for further studies. 3.3. Regulating the Expression and Activity Levels of Ezrin in EVT Cell Lines To study the potential role of ezrin in EVT trophoblast behaviours, we first sought to establish strategies to successfully regulate the levels and/or activity of the protein. For the former, targeted siRNA delivery was used. Cells were treated with different ezrin-targeted siRNAs or their mock control counterpart for 72 h prior to cell lysate collection and Western blotting analysis in both EVT HTR8/SVneo and Swan71 lines . The addition of specific siRNAs was found to significantly reduce the levels of ezrin expression . Treatment with siRNA7 reduced the ezrin concentration in cells by more than 40% (p < 0.05) and 75% (p < 0.0001) in HTR8/SVneo and Swan71 cells, respectively. siRNA9 led to the lowering of protein expression by 60% (p < 0.0001) and 80% (p < 0.0001) in HTR8/SVneo and Swan71 cells, respectively. Given the high sequence homology between ezrin and other ERM proteins and the possible cross-reactivities of antibodies, it was also important to identify that our analysis affected specifically ezrin levels only. Both moesin and radixin were found to be expressed in the HTR8 and Swan71 trophoblast cells but with some cell-specific differences, as a double band could be visible for moesin in the Swan71 trophoblast cell extracts. Moesin has been shown to be post-translationally modified and the presence of different bands has been shown in the context of ERM proteins in numerous cells lines and tissues , and it is unclear whether these bands are the result of post-translational modifications or the cross-reactivity of the antibodies. Treatment with either siRNA7 or 9 did not lead to any significant changes in the levels of radixin or moesin (p > 0.05 for all conditions) in our experiments, further demonstrating the specificity of both the knock-downs and our ability to detect ezrin levels in relation to other known ERM factors. To determine the effects of the ezrin loss-of-function on these cells, we also set about to reduce Thr567 phosphorylation using inhibitors. NSC668394 has been shown to interact specifically with ezrin and inhibits both its phosphorylation as well as actin binding . To verify that this inhibitor reduced Thr567 phosphorylation without affecting the overall levels of ezrin, HTR8/SVneo and Swan71 cells were incubated with 5 mm NSC668394 for 24 h prior to either the collection of cell lysate for Western blotting or fixation for immunostaining . Phosphorylated Thr567 ezrin pools were found to be significantly reduced in HTR8/SVneo cells but not in Swan71, with levels lowered by more than 80% in the former (p < 0.001) and remaining close to the untreated ones in the Swan71 cells . Across all the conditions, the concentrations of total ezrin were found to be unaffected after treatments, indicating that the inhibitor does not actually affect the overall levels of expression (p > 0.05). To gain further insights regarding the cellular localisation of the different ezrin forms, mock or NSC668394-treated HTR8/SVneo and Swan71 cells were stained for either form of the protein . The localisation of the proteins was seen throughout the cytoplasm but also present at the cell periphery, in specific protrusions. Treatment with the NSC668394 inhibitor resulted in a general reduction in these protrusions with a significant reduction in their numbers in both the ezrin and Thr567-phosphorylated experiments in the HTR8/SVneo background (70% p < 0.001) but also in the Swan71 cells, albeit to a much lesser effect (15% reduction p < 0.05), as determined after the quantification of the number of protrusions per cells (Supplementary Table S2), whilst the overall levels of total cellular ezrin were not affected. Altogether, this analysis shows that ezrin protein levels and potential activities can be significantly and specifically affected by siRNAs and inhibitor delivery and that the two EVT-like cells offer differential responses in relation to the treatment carried out. 3.4. The Knock-Down or Inactivation of Ezrin Results in Significant Reductions in EVT-like Cell Motility Ezrin has been shown to be a key regulator of cellular migration in multiple human cancer lines . Its activation via Thr567 phosphorylation has also been reported to be key in this process for both healthy and diseased-state cells . We therefore sought to determine whether ezrin or its potential Thr567-phosphorylated form can similarly promote EVT cell migration. Cell motility was monitored using Boyden chamber assays after ezrin knock-down by siRNA delivery or treatment with the NSC668394 inhibitor in the HTR8/SVneo and Swan71 trophoblast cells . Mock-treated samples demonstrated no significant changes in the number of cells able to migrate across the Boyden membranes (p > 0.05 for HTR8/SVneo and p > 0.05 for Swan71) in the two cell systems used. HTR8/SVneo cells grown in the presence of siRNA7 or siRNA9 presented a significant reduction, by at least 30% (p < 0.05) and 60% (p < 0.0001), respectively, in their motility . Similar observations could be made when using the Swan71 cells, as treatment of these cells with the same siRNAs equally resulted in a significant reduction in migratory abilities by about 50% (p < 0.0001) and 72% . To determine whether phosphorylation of ezrin was also crucial for motility changes, the same trophoblast cells were treated with 5 mm NSC668394 inhibitor for 24 h prior to seeding into Boyden chambers . Incubation with NSC668394 induced a significant 80% reduction in cellular motility in the HTR8/SVneo background. A comparison between the inhibition of the phosphorylation status and the knock-down of the protein was also assessed in relation to cellular motility to determine the levels of inhibition following either NSC668394 or ezrin siRNA treatment (Table 3). Both treatments were seen to significantly reduce cellular motility in the HTR8/SVneo background (all p < 0.01) with further reduction seen when treating the cells with NSC668394 (p < 0.05 against both siRNAs). This was in stark contrast to the work conducted in the Swan71 cells, where treatments only with siRNAs were shown to result in significant decreases in cell migration. Migratory rates after treatment with NSC668394 were found to be lowered by around 15% in the Swan71 cells . This result could be explained by the low levels of phosphorylated Thr567 levels seen in these cells and the inability of NSC668394 to affect these levels in this line at the concentrations used , further supporting the specificity of this small molecule. Changes in cellular motility can be associated with the remodelling of cytoskeletal architecture and cellular protrusion, as we have shown for S100P and trophoblasts previously . Furthermore, ezrin has been shown, at least in cancer cells, to regulate the number and size of focal adhesion when affecting their migration/invasion. Here, we now sought to determine if the motility of trophoblast cells might also be affected by ezrin through a similar mechanism. The focal adhesion marker paxillin was used, as it is considered a vital adapter that aggregates into the focal complex at the early stages of their formation and because focal adhesion assembly is a key process regulating cellular motility and the proteins within undergo profound remodelling over time . Its localisation within the focal adhesion, as well as the actin cytoskeleton, was studied in control cells and in their treated counterparts incubated with ezrin siRNAs or NSC668394 , and the total numbers of focal adhesions per cell were quantified (Table 4 and Table 5). siRNA7 and siRNA9 treatments in both HTR8/SVneo and Swan71 cells resulted in significant increases of 45-92% in the number of focal adhesions per cell (Table 4). The biggest increases in their numbers were seen when using siRNA9 and correlated with the reduction in cell motility in both cell types. Treatment with the ezrin inhibitor NSC668394 also demonstrated a significant increase by over 60% in the number of focal adhesions in the HTR8/SVneo background (p < 0.0001; Table 5). All in all, these data show that affecting either the activation or the level of ezrin in trophoblast cells leads to significant changes in EVT cell motility and that these changes correlate with the number of paxillin-containing focal adhesions. 3.5. The Knock-Down or Inactivation of Ezrin Results in Significant Reductions in EVT Cell Invasion Ezrin has also received a large amount of interest in relation to its ability to promote cancer cell invasion and metastasis with the inhibition of its phosphorylation at Thr567 being seen as one avenue to prevent its activation and reduce cancer cell invasiveness as well as potential metastasis . Having shown that ezrin regulated trophoblast cell motility, we set about to study its potential role in promoting the invasion of the HTR8/SVneo and Swan71 cells. As before, loss-of-function experiments by the knock-down of the expression of ezrin via siRNA or the inhibition of its phosphorylated Thr567 status through the addition of NSC668394 were carried out prior to Boyden chamber Matrigel invasion . Invasion was seen to be inhibited with either siRNA used in all trophoblast cells and resulted in a reduction of 30% (p < 0.05) and 65% (p = 0.0001) with siRNA7 and siRNA9 in HTR8/SVneo, respectively, and 50% (p = 0.01) and 60% (p = 0.0001) with siRNA7 and siRNA9 in Swan71, respectively. These numbers were similar to those observed with the migration experiments. Incubation with the NSC668394 compound led to different responses with the cells used. Whilst its presence resulted in a significant reduction of more than 70% of the invasive properties of the HTR8/SVneo cells (p < 0.01), the same concentration was found to insignificantly change (p > 0.05) the invasion of Swan71 cells, again mirroring data obtained in the migration experiments of the same cells. 3.6. The Knock-Down or Inactivation of Ezrin Does Not Lead to Changes in Cell Viability and Proliferation We have shown that modulating ezrin expression affects both the motility and invasion of trophoblast cells. The expression of ezrin has been linked to cell proliferation, at least in the cancer state , but, to date, there is no evidence of this protein regulating such processes in trophoblasts. To determine whether the effects reported so far in HTR8/SVneo and Swan71 are linked to increases in cell viability, we measured cell growth over 48 h after either ezrin levels had been knocked down or after NSC668394's addition. The incubations used were well within the time frame used to measure invasion and migration . Incubation with either of the siRNAs resulted in no significant changes in the cell numbers when compared to either untreated or mock-treated samples for both the HTR8/SVneo (p > 0.05) or Swan71 cells (p > 0.05). Similarly, the addition of the NSC668394 inhibitor did not affect the proliferation of the cells over the course of the experiment in all conditions tested (HTR8/SVneo (p > 0.05) or Swan71 cells (p > 0.05)), indicating that cell viability was probably not compromised in our experiments, as the cells were proliferating normally over the course of the experiment, with a doubling of the population every 24 h indicating that the defects seen in motility are not due to a reduction in cell numbers. 3.7. Inhibiting Ezrin Phosphorylation in Primary Extravillous Trophoblasts Results in a Significant Reduction in Motility and Invasion Our data so far show that the expression and activation of the ezrin protein differentially regulate both the migratory and invasion rates of trophoblast cell lines. To determine whether similar observations could also be observed in primary trophoblast cells, first-trimester human EVT cells were isolated and studied . Staining for these cells using the HLA-G marker demonstrated that more than 80% of the cells were differentiated EVT cells after immunofluorescence. High levels of the ezrin proteins were seen in these cells , and its localisation was found to be similar to that observed in the different lines, with an extensive organisation in cellular protrusions at the cell periphery . Interestingly, phosphorylated Thr567 ezrin was found to be present at high levels, as demonstrated by the significant intensities obtained after Western blot analysis, especially when compared to other trophoblast cell lines , whilst its localisation mirrored that of the total ezrin pools, with a large amount detected in numerous cellular protrusions along with the cortical actin network . Both the levels and localisation seen in primary EVTs mirrored data obtained with the HTR8/SVneo cell lines . To establish whether we could inhibit the levels of phosphorylated Thr567 ezrin, EVT primary cells were treated with the NSC668394 inhibitor for 24 h prior to analysing the changes by staining . The addition of the NSC668394 inhibitor resulted in a significant reduction of more than 50% in the overall phosphorylated Thr567 signal (p< 0.001). The same concentration of the small molecule led to a significant reduction of about 30% (p < 0.05) and 40% (p< 0.01) in their rates of migration and invasion, respectively . These data demonstrate that primary human extravillous trophoblasts express ezrin and that this protein is actively phosphorylated at residue Thr567 and that inhibiting such post-translational modifications leads to a significant reduction in their motility and invasion. 4. Discussion Elevated levels of ezrin are considered to be an important step towards carcinogenesis, with increased levels seen in numerous cancers and its expression linked to the metastasis of numerous solid tumours . A role for ezrin in the reproduction field is, however, much less characterised and its functions in trophoblast and placental development in the early stages of gestation are not clear. Because significant similarities have been highlighted between the physiological process of trophoblast invasion during placental implantation and the pathological effects of cancer invasion , functions of proteins known as metastasis-inducing proteins (MIP), such as S100P, have been liked to trophoblast migration . We initially sought to establish whether ezrin is expressed in the early stages of placental development and whether it could be found in human extravillous trophoblasts and within their anchoring/invading columns. To achieve this, human placental sections (and protein samples) at differential gestation periods were used. Significant levels of ezrin were found in the cytoplasm of cytotrophoblasts and syncytiotrophoblasts, with the highest levels seen in the apical membrane of the syncytiotrophoblasts , similar to what has been reported previously . This is not surprising, as ezrin has been shown to be a major component of placental microvilli . It is thought that the protein plays some key role in regulating the overall microvillus formation at least in epithelial cells . Microvilli in the placental syncytium effectively sense and interact with the fluid environment , and recent work has shown that these microvilli regulate the transfer of material between the foetal and maternal blood flow . In this work, BeWo and villous trophoblast cells were found to form abundant microvilli of varying lengths where ezrin was relocalised to the apical membrane, further suggesting a role for ezrin to facilitate these exchanges. Interesting and novel was the fact that we could also detect ezrin in the invasive trophoblast columns, localised within the cytoplasmic and apical membrane of the EVTs . To determine if there were changes in the expression of ezrin in trophoblasts over the course of gestation, we stained and quantified the levels of expression for the whole tissues as well as within the different trophoblast populations. We found that the highest level of ezrin was seen during the first and second trimesters of gestation in all trophoblast subtypes analysed, while the expression was significantly reduced at term . This suggests a potential involvement of the protein in earlier stages of gestation. This observation correlates with prior studies, where placental ezrin expression was shown to decrease in late pregnancy in rats . Moreover, the involvement of ezrin and the two other members of the ERM family in implantation was recommended previously by another study, as they detected higher expression of ERM proteins in implantation-competent blastocysts compared with dormant blastocysts in mice . It is, however, important to highlight that another piece of work suggested an inverse expression pattern when high levels of ezrin protein were shown to offer a stronger signal in the later stage of gestation, but no quantification of the immunohistochemistry analysis was provided. We also wanted to characterise the expression levels of ezrin in trophoblast cells and used a collection of background lines as well as first-trimester isolated primary cells. Whilst extensive work has been done to document its expression in the choriocarcinoma Jeg-3 linage, there is, to our knowledge, no report that has characterised ezrin in EVT cells. We found that, in all cases, ezrin protein levels were relatively consistent in all trophoblast cells used. There were, however, significant differences in ezrin subcellular localisation and its Thr567-phosphorylated state in the different cell systems . Whilst ezrin offered a cytoplasmic and microvilli-like organisation in choriocarcinoma lines (BeWo and Jeg-3), some pools were found to be specifically localised near or at the plasma membrane in long cellular protrusions in all EVT cells, including primary cultures. This observation was even more pronounced when looking at the phosphorylated Thr567 version of the protein. Levels of phosphorylation were found to be different whereby HTR8/SV neo and primary cells demonstrated very high levels compared to other EVT cells, with Swan71 cells presenting very low levels of phosphor-Thr567 ezrin. To our knowledge, it is the first time that ezrin has been shown in such a specific cellular location in extravillous trophoblasts. Although we are aware that other data using Jeg-3 trophoblast cells have also indicated the organisation of ezrin into microvilli or in trophoblast giant cells . Ezrin's presence in cellular protrusion has been evidenced in transfected MCF7 and observed by immunoelectron microscopy as well as in keratinocytes and breast cancer cells using immunofluorescence . Furthermore, ezrin has been reported to be a component of actin-rich structures such as focal adhesion and filopodia, lamellipodia, and membrane ruffles . Structures found in EVT cells were, however, very different in terms of number and length. Interestingly, our data suggest that the Thr567-phosphorylated ezrin pools were enriched in the cellular protrusions. This was clearly observed after the use of the NSC668394 inhibitor and the fact that whilst overall ezrin localisation and intensity were not affected following such treatments, there were important reductions in the presence of phosphorylated-Thr567 ezrin in these protrusions in the HTR8/SVneo and primary extravillous trophoblast backgrounds . This is, again, in line with the presence of the phosphorylated active form present in microvilli and other observations that have shown that the localisation of the proteins might indicate the level of protein activation. It is known that the active (open) ezrin, similar to other ERM family members, links the cytoskeleton to the plasma membrane via PIP2, and therefore is localised within the cell cortex, while the inactive (closed) ezrin is located in the cytoplasm . We found that ezrin and its phosphorylated form were present in cellular protrusions in specific locations of the extravillous trophoblast cells, whether lines or primary. Given that these extensions are finger-like cytoplasmic structures containing F-actin filaments and that they extend well beyond the leading edge, we speculate that these structures are filopodia. Numerous migrating cells have been shown to display filopodia, including trophoblast cells . Whilst our data suggest the importance of ezrin and its phosphorylation for the formation of these filopodia, the mechanisms as to how these are regulated are not known. One of the most likely scenarios is that ezrin and its phosphorylation may regulate Rho activity. Ezrin has been shown to regulate members of the Rho family , including Rho guanine nucleotide exchange factors, Rho GTPase-activating proteins, and Rho GDP-dissociation inhibitors. Given the wealth of work that has been carried out to link filopodia formation and extension being regulated by the Rho family through actin filament polymerisation, there are multiple factors within this extensive family which may be controlled by ezrin and lead to the changes seen. There is a large amount of evidence that has shown that ezrin expression is associated with enhanced cellular motility and invasion, as well as metastasis and poor prognosis for cancer patients . Consequently, we aimed to see how this protein regulates trophoblast motility and invasion through loss-of-function experiments via ezrin knock-down or the inhibition of Thr567 phosphorylation. For the former, two different sequences of siRNA against ezrin were presented (siRNA 7 and 9), as they were the most effective in knocking down ezrin in HTR8/SVneo and Swan71 cells and resulted in a significant reduction in motility and invasion . This is in line with current work using siRNA delivery to monitor motile and invasive phenotypes in cancer cells . This is also the first time that ezrin has been directly linked to changes in migration and invasion in extravillous trophoblasts, although we are aware that the roles of this factor in the choriocarcinoma Jeg-3 linage were recently reported . Thr567 ezrin phosphorylation levels were seen to be significantly different across the trophoblast cells studied. Both HTR8/SVneo and primary extravillous trophoblast cells demonstrated high levels confirming the suitability of this cell line as a good model of the first-trimester trophoblast line. Interestingly Swan71, as well as the SGHPL4 and SGHPL5 background, presented much lower levels, although the localisation of the phosphorylated form was seen in the cellular protrusion, presumably resulting in its activation and its phenotypical relocation to key structures, such as that shown for the promotion of apical microvilli formation . Ezrin is activated through phosphorylation at thr567 by different kinases. Members of the PKC serine/threonine kinase family such as PKCa, I, and g and redundant kinases lymphocyte-oriented kinase (LOK, STK10) and sterile 20-like kinase (SLK, Ste-20) phosphorylate ezrin at Thr567. Given that both PKC and LOK/SLK have been found in trophoblasts, we decided to use the cell-permeable quinoline NSC668394, which inhibits ezrin Thr567 phosphorylation primarily via its binding to ezrin and not through the inhibition of kinase activity . Interestingly, NSC668394 treatment was found to lead to a significant reduction in both the Thr567-phosphorylated status and motility/invasion, in the HTR8/SVneo background as well as in primary extravillous trophoblasts, but had little effect in the Swan71 cells. This, again, may be explained by the generally very low levels of phosphorylation seen in the latter. Differential responses in relation to ezrin phosphorylation in cells following incubation with the NSC668394 inhibitors have been reported, for instance in cancer states such as myeloid leukaemia cell lines, where different cells treated with the same dose resulted in differential levels of phosphor-ezrin, especially at concentrations below 12.5 mm . All in all, these data indicate that both ezrin and its phosphorylated form play important roles in motility and invasion in line with work carried out in cancer cells where the relocalisation of ezrin in membrane and microvilli also improved these properties . During the promotion of cellular migration, rapid formation and the turnover of the FAs during directional cell movement pulls the cell body forward, while their rapid turnover at the rear end detaches them from the extracellular matrix. We therefore sought to determine if the ezrin-induced cell motility reported in extravillous trophoblasts involved observable FA changes by analysing the localisation pattern of paxillin, an FA component, upon ezrin knock-down or after inhibiting Thr567 phosphorylation. Reducing ezrin expression in both HTR8/SVneo and Swan71 cells resulted in a significant increase in the number and size of the paxillin-containing focal adhesion, in line with previous work showing a reduction in FA dynamics in breast cancer for the proper disassembly and turnover of FA and invadopodia structures . The role of ezrin in this cellular signalling is not well characterised, especially in EVT cells, but a possible candidate could be the protein calpain, which is yet another factor that has been linked, albeit indirectly, to the promotion of focal adhesion disassembly through cleavages of specific targets . Ezrin is a calpain substrate and has been shown to positively regulate calpain activity.. Ezrin has also been shown to interact with the focal adhesion kinase (FAK ) and regulates its activation. Given that both calpain and FAK expressions have been found in trophoblasts , including the extravillous HTR8/SVneo line , these are some of the potential mechanisms by which ezrin could regulate the changes in focal adhesion seen in our work. Whilst the work carried out in this report concentrated on ezrin and its phosphorylated Thr567 residue, we are also aware that there are other phosphorylated sites on the protein that could explain the significant changes in separation on gels , such as Tyr477 , Ser66 , Thr235 , and Tyr145 . Tyr353 is also one of the important amino acid residues that can be phosphorylated and is involved in the PI3-kinase/Akt signalling . It is possible that these and other post-translational modifications may also be associated with ezrin's activation. It is therefore important to consider that studying the role of these other regions of ezrin is essential to offer a better understanding of how ezrin regulates the cytoskeletal changes in trophoblasts and its potential role in early placenta development. Acknowledgments The authors are extremely grateful to Melissa Westwood from the Maternal and Fetal Health Research Centre, University of Manchester and St Mary's Hospital, at Manchester Academic Health Sciences Centre (Manchester, M13 9WL) for her support, time, and kindness in providing us with samples and resources to be able to conduct some of the work presented. The authors would also like to thank Margherita Turco and Lisa Gardner (Department of Pathology, University of Cambridge, Cambridge, UK) as well as Tara Lancaster (Aston University) for their help and time to allow us to successfully isolate and culture primary extravillous trophoblasts. The authors would like to thank Charlie Bland for technical support related to the work using microscopy at ARCHA at Aston University. A special thanks to all volunteers who have provided the invaluable samples that have been used throughout the work carried out. Thanks also to Aston University for providing financial support from the Life and Health Sciences PhD studentship scheme supporting Maral E.A. Tabrizi. The authors acknowledge support from the Research Group and Biomedical Sciences Research funding schemes for the provision of consumables. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Ezrin is highly phosphorylated in primary EVTs compared to all trophoblast cell lines; Figure S2: Original blots for all Western blot analysis presented in the manuscript; Table S1: Antibodies used in this study; Table S2: Total number of cells counted for motility and invasion of HTR8/SVneo and Swan71 trophoblast cell lines and primary EVT cells after ezrin knock down or NSC668394 treatment. Click here for additional data file. Author Contributions S.R.G. conceived and designed the experiments. M.E.A.T. and S.R.G. performed all experiments. J.K.G. provided some of the human placental samples used in part of this study. S.R.G. and M.E.A.T. analysed the data. S.R.G. wrote the paper. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the National Research Ethics Service (NRES) Committee North West--Haydock (study approval number 13/NE/2005) for samples of placenta tissues obtained either after the elective termination of pregnancy from different trimesters prior to being embedded in paraffin or by the Health Research Authority--West Midlands, Edgbaston Research Ethics Committee (NHS REC 15/WM/0284 and AHRIC REF 1245-SG) for samples obtained immediately after the elective termination of pregnancy from the first trimester of gestation (8-12 weeks) for EVT isolation. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper. Data Availability Statement The data presented in this study are available within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Ezrin is expressed in trophoblasts, including extravillous trophoblasts and anchoring columns during the first trimester in human placental tissues. Expressions of ezrin proteins were analysed on both lysates (A,B) and paraffin-embedded placental sample sections (C,E) obtained from different gestational periods (first trimester (n = 3), second trimester (n = 3), or full term (n = 4)). Protein lysates of equal loading were separated by SDS-PAGE electrophoresis and transferred onto PVDF membranes before Western blotting for ezrin or a-tubulin, and cropped images are presented (A). Levels of ezrin were measured by densitometry analysis after Western blotting and normalised to a-tubulin for all samples. Data are presented as percentage means +- SEM of 2 independent experiments compared to the first trimester (B). Immunohistochemistry staining using either ezrin (C) or a panel of trophoblast marker antibodies (HLA-G as well as cytokeratin 7 (CK7)) as well as ezrin (E) were also counterstained as described in the methods section. Images for (C) show the overall structures of the placental sections with enlarged sections corresponding to the focused regions of the highlighted cells. Bar corresponds to 150 mm in the wide views and 25 mm in the zoomed-in regions. Images of anchoring columns of serial human placental tissues are also presented (E). Bar corresponds to 100 mm. Arrows indicate cytotrophoblast cells (CT); syncytium (ST) and stroma are also highlighted (C,E). The quantification of ezrin DAB staining and intensity in the 1st, 2nd, and full-term sections (D). Data of an individual representative experiment are presented as the mean values +- SD of 3 independent samples (D). Statistical analysis (B,D) shows +- SD compared to the first-trimester samples of an individual representative experiment. * p < 0.05 and *** p < 0.001 (one-way ANOVA); N.S.: not significant. Figure 2 Ezrin is expressed in all trophoblast cell lines. Choriocarcinoma cells BeWo and Jeg-3 cells, along with EVT cell lines HTR8/SVneo, Swan71, SGHPL4, and SGHPL5 cells, were grown for 48 h prior to the collection of the protein lysates for Western blotting (A) or cell staining (C,D). Cells were collected and solubilised in Lammeli buffer and equal loadings were separated by SDS-PAGE electrophoresis. Western blotting was carried out and membranes were probed for ezrin, phosphor-ezrin Thr567, or a-tubulin and cropped images are presented (A). The expression levels of ezrin and phospho-ezrin Thr567 were measured by densitometric analysis, normalised to a-tubulin and ezrin, respectively, and presented as arbitrary units and as mean values +- SD of 3 independent samples. *** p < 0.001 or **** p < 0.0001 (one-way ANOVA) (B). For immunostaining, BeWo and Jeg-3 cells and EVT-like cell lines HTR8 SV/Neo, Swan71, SGHPL4, and SGHPL5 cells were seeded on fibronectin-coated coverslips and grown for 48 h prior to fixation, permeabilisation, and staining for ezrin (C), phospho-ezrin Thr567 (D), and actin (C,D). Cells were mounted and viewed using epifluorescence microscopy. Images in the last row correspond to the enlarged regions of the highlighted cells. Bar corresponds to 25 mm in the wide views and 5 mm in the zoomed-in regions. Figure 3 Specific knock-down of ezrin levels but not moesin or radixin or inhibitions of ezrin Thr567 phosphorylation in HTR8/SVneo and Swan71 trophoblastic cell lines. HTR8/SVneo and Swan71 cells were incubated in the presence of different ezrin siRNAs or control siRNAs for 72 h (A-D) or treated with NSC668394 inhibitors for 24 h (E-I) prior to collection for protein Western blotting (A,C,E,G) or immunofluorescence (I). For the determination of protein levels, cells were collected and solubilised in Lammeli buffer and equal loadings were separated by SDS-PAGE electrophoresis prior to PVDF transfer and Western blotting for ezrin, moesin, radixin or a-tubulin (A,C) or phosphor ezrin Thr567 (E,G), and cropped images are presented. The expression levels of ezrin, moesin and radixin or Thr567-phosphorylated ezrin and the effects of siRNAs or inhibitors, respectively, were measured by densitometric analysis, normalised to a-tubulin or ezrin and presented as percentage mean values +- SD of 3 independent samples of a representative experiment compared to non-treated control samples. ** p < 0.01 or *** p < 0.001 (one-way ANOVA). For all proteins, loading orders are the same as for the blots above (B,D,F,H). EVT-like lines HTR8/SVneo and Swan71 cells were seeded on fibronectin-coated coverslips and grown for 48 h prior to fixation, permeabilisation, and staining for ezrin and phospho-ezrin Thr567 (I). Cells were mounted and viewed using epifluorescence microscopy. Images in the last row correspond to the enlarged regions of the highlighted cells. Bar corresponds to 25 mm in the wide views and 5 mm in the zoomed-in regions. Figure 4 Reduced ezrin levels or its Thr567phosphorylation results in differential reductions in the cellular motility of HTR8/SVneo and Swan71 trophoblasts. HTR8/SVneo and Swan71 cells were incubated in the presence of different ezrin siRNAs or control siRNAs for 72 h (A,D) or treated with NSC668394 inhibitors for 24 h (B,E) prior to starvation with low-serum-containing medium. After 24 h, cells were seeded into Boyden chambers for 16 h prior to fixation and staining using the Diffquik histochemical kit for labelling of both nuclei and cytoplasm (A,B,D,E). Five random fields were quantified for each chamber. Data are presented as means +- SEM of 4 independent experiments relative to controls (percentage) from 4 replicate wells for each set of conditions. ** p < 0.01 or *** p < 0.001 compared to control and mock treatments (one-way ANOVA). Images of representative fields of motility/invasion assays were taken with the EVOS XL Cell Imaging System at x20 magnification. Bar corresponds to 100 mm (A,B,D,E). For immunofluorescence after siRNA delivery for 48 h, incubation cells were seeded on fibronectin-coated coverslips and grown for a further 48 h before fixing. For the ezrin phosphorylation experiment, NSC668394 inhibitors were added for 24 h prior to fixation, permeabilisation, and staining for paxillin and actin. Cells were mounted and viewed using epifluorescence microscopy (C,F). Images on the last row correspond to the enlarged regions of the highlighted cells. Bar corresponds to 50 mm in the wide views and 10 mm in the zoomed-in regions. Figure 5 Reduced ezrin levels or its Thr567phosphorylation results in the differentially reduced cellular invasion of HTR8/SVneo and Swan71 trophoblasts. HTR8/SVneo and Swan71 cells were incubated in the presence of different ezrin siRNAs or control siRNAs for 72 h (A,C) or treated with NSC668394 inhibitors for 24 h (B,D) prior to starvation with low-serum-containing medium. After 24 h, cells were seeded into Matrigel-coated Boyden chambers for 16 h prior to fixation and staining using the Diffquik histochemical kit for the labelling of both nuclei and cytoplasm (A-D). Five random fields were quantified for each chamber. Data are presented as the means +- SEM of 4 independent experiments relative to controls (percentage) from 4 replicate wells for each set of conditions. * p < 0.05, ** p < 0.01 or *** p < 0.001 compared to the control and mock treatments (one-way ANOVA). Images of representative fields of motility/invasion assays were taken with the EVOS XL Cell Imaging System at 20x magnification (A-D). Bar corresponds to 100 mm. Figure 6 Modulation of ezrin protein levels or Thr567-phosphorylation does not affect HTR8/SVneo and Swan71 trophoblast cell proliferation. HTR8/SVneo and Swan71 cells were incubated in the presence of different ezrin siRNAs or control siRNAs for 72 h or treated with NSC668394 during the course of the experiment (A-D). Cell lines were seeded into 24-well plates and left to grow for a further 24-72 h before trypan blue exclusion (A,C) or MTT conversion (B,D). For the former, cells were trypsinised and removed from the wells prior to counting using trypan blue exclusion. For MTT conversion, MTT was added to the wells and left to be reduced prior to washing cells, and solubilising formazan in DMSO and absorbance measurements were carried out at 570 nms. Data are presented as percentage means +- SD of 3 independent experiments relative to controls from 3 replicate wells for each set of conditions. *** p < 0.0001 (one-way ANOVA). Figure 7 Inhibiting ezrin Thr567phosphorylation results in a significant reduction in both the cellular motility and invasion of human primary extravillous trophoblast cells. Human primary extravillous trophoblasts were grown for 48 h following isolation prior to either the collection of the protein lysates for Western blotting (A) or cell staining (B,C) or seeding for motility (E) or invasion (F). Cells were collected and solubilised in Lammeli buffer and equal loadings were separated by SDS-PAGE electrophoresis. Western blotting was carried out and membranes probed for ezrin, phosphor-ezrin Thr567, or a-tubulin, and cropped images are presented (A). For immunostaining, cells were seeded on fibronectin-coated coverslips and grown for 24 h prior to NSC668394 treatment. Cells were left to grow for a further 24 h prior to fixation, permeabilisation, and staining for ezrin (B), phospho-ezrin Thr567 (C), and actin (B,C). Cells were mounted and viewed using epifluorescence microscopy. Images in the last row correspond to the focused regions of the highlighted cells. Bar corresponds to 50 mm in the wide views and 10 mm in the zoomed-in regions. Expression levels of Thr567-phosphorylated ezrin in human primary extravillous trophoblasts treated with NSC668394 inhibitors for 24 h by immunofluorescence (D) and presented as intensity percentage mean values +- SD of 3 independent samples of a representative experiment compared to non-treated control samples. *** p < 0.001 (one-way ANOVA). For motility and invasion, cells were starved with low-serum-containing medium. After 24 h, cells were seeded into Boyden chambers with or without Matrigel and NSC668394 treatment for 16 h prior to fixation and staining using the Diffquik histochemical kit for the labelling of both nuclei and cytoplasm (E,F). Five random fields were quantified for each chamber. Data are presented as the means +- SEM of 4 independent experiments relative to controls (percentage) from 4 replicate wells for each set of conditions. *** p < 0.001 compared to control and mock treatments (one-way ANOVA). cells-12-00711-t001_Table 1 Table 1 Ezrin expression reduces throughout the gestation in human placental tissues in the different trophoblast populations. Percentage Ezrin Pixel: Total Pixels in Images +- SEM (n = 50) Percentage Ezrin Pixel in STB: Total Pixels in Images +- SEM (n = 50) Percentage Ezrin Pixel in CTB: Total Pixels in Images +- SEM (n = 50) Percentage Ezrin Pixel in pcEVT: Total Pixels in Images +- SEM (n = 50) First Trimester 34.69 +- 3.28 56.24 +- 7.24 81.68 +- 8.72 94.20 +- 5.87 Second Trimester 28.24 +- 2.37 27.24 +- 19.34 55.36 +- 13.30 75.49 +- 10.52 p < 0.05 a p > 0.05 a p < 0.05 a p > 0.05 a Full Term 12.33 +- 3.41 3.76 +- 5.32 1.52 +- 2.15 29.24 +- 225.53 p < 0.001 a p < 0.01 a p < 0.001 a p < 0.01 a p < 0.01 b p < 0.05 b p < 0.001 b p < 0.05 b Expression of ezrin proteins was analysed by pixel quantification after immunohistochemistry staining using the ezrin of paraffin-embedded placental sample sections obtained from different gestational periods (first trimester (n = 3), second trimester (n = 3), or full term (n = 4)). Data of an individual representative experiment are presented as the mean values +- SD of 3 independent samples and correspond to the quantification of DAB-positive pixels against total pixels in each image in first, second, and full-term sections either globally or for specific cell types. STB (syncytiotrophoblast), CTB (cytotrophoblasts), pcEVT (proximal column extravillous trophoblast). a p-value obtained from one-way ANOVA where the ratio of ezrin positive pixels to total pixels in images from first-trimester samples was compared to the second trimester or full term. b p-value obtained from one-way ANOVA where the ratio of ezrin positive pixels to total pixels in images from second-trimester samples was compared to full term. cells-12-00711-t002_Table 2 Table 2 Inhibiting ezrin phosphorylation with NSC668394 leads to much greater reductions in cellular protrusions in HTR8/SVneo than in Swan71 trophoblast cells. Cell Lines Phospho-Ezrin Protrusions Per Cell +- SEM (n = 50) p-Value HTR8/SVneo control 41.00 +- 1.26 HTR8/SVneo treated with NSC668394 16.41 +- 0.96 p < 0.001 Swan71 control 40.81 +- 1.23 Swan71 treated with NSC668394 35.45 +- 0.91 p < 0.05 HTR8/SVneo and Swan71 trophoblast cells, as well as cells treated with ezrin inhibitor NSC668394 for 72 h, were fixed and stained for phospho-ezrin and actin after seeding on fibronectin-coated coverslips. Data shown are means +- SEM corresponding to the average number of phospho-ezrin protrusions observed per cell. The p-value was obtained from a one-way ANOVA where the total number of protrusions present in control cells was compared to the inhibitor-treated counterparts. cells-12-00711-t003_Table 3 Table 3 Comparison of trophoblast motility after inhibiting ezrin using siRNA delivery or NSC668394 treatments. Cell Lines Percentage Motility +- SEM (n = 50) p-Value a p-Value b HTR8/SVneo control 100.00 +- 3.46 HTR8/SVneo treated with ezrin siRNA7 73.92 +- 8.59 p < 0.01 p < 0.001 HTR8/SVneo treated with ezrin siRNA9 48.40 +- 7.01 p < 0.001 p < 0.05 HTR8/SVneo treated with NSC668394 24.28 +- 3.91 p < 0.001 Swan71 control 100.98 +- 8.29 Swan71 treated with ezrin siRNA7 52.17 +- 6.72 p < 0.001 p < 0.01 Swan71 treated with ezrin siRNA9 39.57 +- 5.59 p < 0.001 p < 0.01 Swan71 treated with NSC668394 79.88 +- 15.59 p > 0.05 HTR8/SVneo and Swan71 cells were incubated in the presence of different ezrin siRNAs or control siRNAs for 72 h or treated with NSC668394 inhibitors for 24 h prior to starvation with low-serum-containing medium. After 24 h, cells were seeded into Boyden chambers for 16 h prior to fixation and staining using the Diffquik histochemical kit for labelling of both nuclei and cytoplasm. Five random fields were quantified for each chamber. Data are presented as means +- SEM of 4 independent experiments relative to controls (percentage) from 4 replicate wells for each set of conditions. a p-value obtained from one-way ANOVA where the percentages of motile cells in HTR8/SVneo or Swan71 mock control cells were compared to previously ezrin siRNA-treated or NSC668394 counterparts. b p-value obtained from one-way ANOVA where the percentages of motile cells in ezrin siRNA HTR8/SVneo or Swan71 cells were compared to NSC668394 counterparts. cells-12-00711-t004_Table 4 Table 4 Reduction in ezrin protein levels in trophoblast cells by siRNA delivery significantly increases the number of focal adhesions per cell. Cell Lines Percentage Focal Adhesions Per Cell +- SEM (n = 50) p-Value a p-Value b HTR8/SVneo control 100 +- 5.22 HTR8/SVneo treated with ezrin siRNA7 170.32 +- 11.34 p < 0.0001 HTR8/SVneo treated with ezrin siRNA9 192.48 +- 14.43 p < 0.0001 0.0089 Swan71 control 100 +- 4.81 Swan71 treated with ezrin siRNA7 145.88 +- 10.23 0.0078 Swan71 treated with ezrin siRNA9 172.78 +- 12.13 p < 0.0001 0.1219 HTR8/SVneo and Swan71 mock control cells, as well as cells treated with different ezrin-targeted siRNA for 72 h, were fixed and stained for paxillin and actin after seeding on fibronectin-coated coverslips. Data shown are means +- SEM corresponding to the average number of focal adhesion-containing paxillin observed per cell, presented as a percentage of the control. a p-value obtained from one-way ANOVA where the total number of focal adhesions present in HTR8/SVneo or Swan71 mock control cells were compared to previously ezrin siRNA-treated counterparts. b p-value obtained from one-way ANOVA where the total numbers of focal adhesions present in HTR8/SVneo or Swan71 treated with ezrin siRNA7 were compared to ezrin siRNA9-treated counterparts. cells-12-00711-t005_Table 5 Table 5 Inhibiting ezrin phosphorylation with NSC668394 in HTR8/SVneo trophoblast cells leads to increases in the number of focal adhesions per cell. Cell Lines Percentage Focal Adhesions Per Cell +- SEM (n = 50) p-Value HTR8/SVneo control 100 +- 5.47 HTR8/SVneo treated with NSC668394 162.11 +- 7.94 p < 0.0001 HTR8/SVneo, as well as cells treated with ezrin inhibitor NSC668394 for 72 h, were fixed and stained for paxillin and actin after seeding on fibronectin-coated coverslips. Data shown are means +- SEM corresponding to the average number of focal adhesion-containing paxillin observed per cell, presented as a percentage of the control. p-value obtained from one-way ANOVA where the total numbers of focal adhesions present in HTR8/SVneo control cells were compared to the inhibitor-treated counterparts. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000481 | Myeloid sarcomas (MS), commonly referred to as chloromas, are extramedullary tumors of acute myeloid leukemia (AML) with varying incidence and influence on outcomes. Pediatric MS has both a higher incidence and unique clinical presentation, cytogenetic profile, and set of risk factors compared to adult patients. Optimal treatment remains undefined, yet allogeneic hematopoietic stem cell transplantation (allo-HSCT) and epigenetic reprogramming in children are potential therapies. Importantly, the biology of MS development is poorly understood; however, cell-cell interactions, epigenetic dysregulation, cytokine signaling, and angiogenesis all appear to play key roles. This review describes pediatric-specific MS literature and the current state of knowledge about the biological determinants that drive MS development. While the significance of MS remains controversial, the pediatric experience provides an opportunity to investigate mechanisms of disease development to improve patient outcomes. This brings the hope of better understanding MS as a distinct disease entity deserving directed therapeutic approaches. myeloid sarcoma chloroma acute myeloid leukemia pediatric CA204231 HL149620 S.R. is funded by CA204231 and HL149620. pmc1. Introduction Myeloid sarcomas (MS) are extramedullary tumors of myeloid blasts forming masses disrupting normal tissue architecture in patients with acute myeloid leukemia (AML) . They are also known as myeloblastomas, granulocytic sarcomas, chloroleukemia, and chloromas given the historically green appearance of the tumors resulting from myeloperoxidase exposure to air. Importantly, there is no clearly accepted definition of what qualifies as MS. Most agree that discrete tumor masses of myeloid blasts are MS; however, whether gingival infiltration and masses within lymph nodes, the liver, or spleen should also be considered MS is debated given their propensity for generalized infiltration. Central nervous system (CNS) leukemia is also a challenge with categorization including both cerebral spinal fluid (CSF)-positive disease and CNS infiltrates/masses on imaging. This has made clear, consistent reporting of clinical presentation and outcome data difficult given the lack of consensus within the literature. Given this limitation, the following terms will be used for this review: extramedullary disease and MS. Extramedullary disease will more broadly refer to leukemic disease outside the bone marrow/peripheral blood, while MS will be specific to myeloid blast tumors. These terms are not used interchangeably and are used as defined to more accurately portray the referenced literature, with extramedullary disease as an umbrella term that also includes MS. MS most frequently presents with a mass in subcutaneous/soft tissue, bone, and skin (also known as leukemia cutis). Case reports include masses and infiltrative involvement in nearly every conceivable tissue including the GI tract, reproductive organs, CNS, heart, lungs, kidneys, and breast . Interestingly, MS, while most often seen concurrently with intramedullary AML, can occur in isolation in the absence of bone marrow disease. MS can also occur in the setting of a preceding hematologic disease such as myelodysplastic syndrome (MDS) or myeloproliferative neoplasms (MPN). Finally, MS can develop as a relapse following a hematopoietic malignancy, including after allogeneic hematopoietic stem cell transplantation (allo-HSCT) . Although AML is seen primarily in older adults with a median age at diagnosis of 68 years, AML accounts for 10 to 15% of acute leukemias in children . Pediatric AML differs from AML in adults in terms of clinical course, outcomes, and genomic landscape . MS in pediatrics represent an inadequately understood aspect of AML. MS presentations offer another distinction between pediatric and adult AML with opportunities for improvement in diagnosis, management, and further investigation into the biological mechanisms of development and treatment resistance. This review will discuss the clinical presentations and reported outcomes of pediatric patients with MS including post-allo-HSCT, imaging approaches to diagnosis, and finally, the biology of MS will be addressed. While this review focuses on pediatric MS, important comparisons with adults will also be discussed. 2. Pediatric Clinical Presentation, Incidence, and Outcomes Although generally considered a rare presentation, MS and extramedullary AML are common in children with AML. Numerous cooperative groups and large institution studies have reported both characteristics and outcomes associated with extramedullary disease (Table 1). The inconsistent terminology surrounding MS and extramedullary disease prevents direct comparison across these studies. Despite this limitation, these studies provide helpful data about the clinical features and associations seen as well as insight into outcomes. 2.1. Incidence The incidence of MS varies widely, particularly when comparing adults and children. This is predominantly related to the lack of consistency in MS evaluation and reporting. There is no standard recommendation for patients with AML to undergo screening evaluation for MS and the true incidence is likely higher than that reported given the potential for asymptomatic occult tumors. Pediatric studies describe an incidence of MS ranging from 5.7% to as high as 40% with the expansive definition of extramedullary disease, although most commonly it is between 10 and 25% . The distribution of common anatomic sites in children is illustrated in Figure 1. A lower incidence of MS is generally reported in adults (4-9%) with newly diagnosed AML, although this is likely an underestimate considering a recent prospective study . It is unclear why such differences exist between children and adults, but this may be related to differences in diagnostic evaluations performed or inherent differences in the leukemias that children develop compared to adults in terms of mutational spectrum . 2.2. Clinical Associations In children, MS is typically associated with a younger age at diagnosis, particularly in infants, and more frequently in males, with 55-75% of patients with MS being male . Higher WBC counts and hepatosplenomegaly are often seen in the presence of MS, although less consistently. Additionally, the FAB M4 (acute myelomonocytic) and M5 (acute monocytic) subtypes are most commonly associated with MS. Cytogenetically, the most frequently described associations are inv(16), t(8;21), and chromosome 11 abnormalities, namely 11q23, with both deletions and rearrangements . By contrast, in adults, a recent study of 1,583 patients identified increased odds of extramedullary disease in patients with PTPN11, NPM1, and FLT3-ITD mutations with no association with inv(16) or t(8;21) and decreased odds of extramedullary disease with IDH2 and CEBPA mutations . Pediatric AML has distinct mutational profiles in comparison to adult AML, and similarly, the AML genetic profile associated with pediatric MS appears distinct from that of adults. This suggests different biologic drivers of pediatric AML and MS or extramedullary disease development, and potential significance for treatment and outcomes. 2.3. Outcomes There is no consensus on the influence of MS on prognosis in children with AML. Table 1 summarizes many of the larger studies, with notably conflicting results. Although typically considered a presentation of advanced disease, event free survival (EFS) and relapse free survival (RFS) do not consistently demonstrate worse outcomes for MS. Reports from Children's Oncology Group (COG) demonstrate an improved EFS in subsets of MS patients with non-skin MS, later defined as orbital MS and CNS MS, with otherwise similar outcomes to non-MS patients in those with other sites of MS disease including skin . A single center report from India similarly describes improved EFS and overall survival (OS) in patients with MS excluding CSF-only disease . By contrast, other studies describe no significant association between MS or more general extramedullary disease and EFS . A Turkish single center study found significant effects on outcomes for patients with MS only when less intensive treatment was given . The Japanese childhood AML cooperative study group also only found inferior EFS with extramedullary disease in the setting of WBC count >100 x 109/L . By contrast, other reports describe significantly worse EFS and OS for children with AML and MS compared to those without MS . Collectively, this indicates that whether MS is a critical driver of outcomes remains an important unanswered question within the field. Favorable cytogenetics, including core binding factor mutations, are common in patients with MS. In evaluation of children with low risk AML (e.g., inv(16), t(8;21), NPM1 mutated without FLT3-ITD mutation, and CEBPA mutation), reports demonstrated worse RFS and EFS in patients with MS present compared to those without MS present . This suggests that even in otherwise favorable AML, the presence of MS could be relevant for both prognosis and potentially risk stratification. Although controversy remains in broadly assigning prognostic impact to the presence or absence of MS in pediatric leukemia, the significance should not be simply ignored. Particularly in patients with t(8;21), inv(16), or chromosome 11/KMT2A abnormalities, evaluating for the presence of MS may be significant in considering therapeutic approaches. Additional studies are needed to prospectively identify patients with MS, as defined by clear criteria, to determine the impact on prognosis, the potential need for altering risk stratification, and defining remission status. This will be important to identify which patients may benefit from specific or intensified therapy regimens to improve outcomes. 3. Significance of Extramedullary Disease and Myeloid Sarcomas Post-Allogeneic Hematopoietic Stem Cell Transplant Relapse of AML remains the predominant cause of treatment failure and death with allo-HSCT as the only curative option for many patients. The role of allo-HSCT in the setting of MS is a moving target in children. However, new data are emerging to address this important point because anecdotal evidence suggests isolated MS relapse, in the absence of bone marrow relapse, is a common occurrence post-allo-HSCT. The Japan Society for Hematopoietic Cell Transplantation (JSHCT) used their national database to identify pediatric AML patients that underwent allo-HSCT and found that the presence of extramedullary disease (both CNS disease and MS) had no impact on OS or leukemia-free survival (LFS) after transplant. However, the patients with extramedullary disease prior to transplant were more likely to have extramedullary relapses after transplant, with 41% of relapses being extramedullary. In comparison, those without prior extramedullary disease had only 6% extramedullary relapse, although the overall rates of recurrence were the same between the two groups . Relapse with isolated MS was not separated out as a group and was therefore difficult to directly assess. The Turkish Pediatric Bone Marrow Transplantation Registry recently reported on their experience with isolated extramedullary relapse (iEMR) in children following allo-HSCT, although they included both acute lymphoblastic leukemia (ALL) and AML. They found different risk factors for medullary relapse post-allo-HSCT versus iEMR. Transplant in CR2 or later or active disease at time of transplant and matched sibling donor transplants were independently associated with increased risk of medullary relapse as well as iEMR. The presence of chronic graft versus host disease (cGVHD) was conversely associated with decreased risk of medullary relapse with no impact on the risk of iEMR. iEMR rates were, however, independently higher in those with prior extramedullary disease . A higher rate of second iEMR was also seen following a first iEMR at 58.8% versus after a first medullary relapse at 13% . Local radiotherapy of extramedullary disease sites prior to transplantation and the presence of cGVHD had no impact on post-allo-HSCT iEMR, while cGVHD was protective in preventing medullary relapse . This suggests that although a graft versus leukemia effect is helpful in preventing medullary relapse, this immune-mediated mechanism is not effective against MS masses and extramedullary sites of leukemia. A single site report from the University of Michigan found that children were also three times more likely than adults to experience an extramedullary relapse with an associated higher pretransplant extramedullary disease incidence . The significance of extramedullary relapse, particularly in these settings, provides insight into mechanisms of disease resistance specific to the MS phenotype following allo-HSCT. Despite these concerns, allo-HSCT remains the best disease management for patients with high-risk AML. Extramedullary disease prior to transplant is consistently associated with increased risk of extramedullary relapse after HSCT in both children and adults . The presence of prior extramedullary disease (including CNS disease and MS) in adults with AML was not found to be an independent risk factor for post-allo-HSCT relapse, DFS, or OS in both a large CIBMTR analysis and a Canadian report . This confirms the anecdotal clinical concern that allo-HSCT is more effective for medullary versus extramedullary disease. Adults with iEMR post-allo-HSCT are more likely to have had prior extramedullary disease and GVHD present compared to those with medullary relapse . Additionally, extramedullary relapse has a higher incidence following allo-HSCT than intensive chemotherapy alone . These iEMRs may represent sanctuary sites in which immune-based therapies may be less effective and may result from a different mechanism of pathogenesis compared to medullary relapse. There is currently no treatment consensus for iEMR post-allo-HSCT, with a range of treatment approaches taken including local radiotherapy and systemic chemotherapy . The significance of iEMR on outcomes compared to medullary relapse is more controversial, with conflicting studies limited by inclusion of both ALL and AML patients with known differences in the efficacy of graft versus leukemia effect between the two diseases . One retrospective adult study, however, did report that allo-HSCT was an effective treatment for patients with MS compared to chemotherapy alone, although lack of complete MS remission prior to transplant had independently worse OS and PFS . In summary, the presence of known or occult MS prior to allo-HSCT may be clinically important for a subset of patients, although additional studies are needed to define which groups may benefit. Furthermore, identifying the increased risk for iEMR following allo-HSCT can inform evaluations and management of patients during their post-transplant course. This emphasizes the importance of identifying and following MS in patients with AML prior to allo-HSCT and remaining vigilant to the possibility of iEMR. 4. Imaging Evaluation of Myeloid Sarcomas The use of imaging to identify occult MS as well as re-evaluation of disease presence has remained inconsistent, both in frequency and modality, particularly in children. Ultrasounds of MS lesions typically show homogenously hypoechoic lesions with hypervascularity . Computed tomography (CT) scans identify MS as isodense lesions compared to muscle with moderate enhancement with IV contrast media. Enhancement is more commonly homogenous (65%) versus inhomogenous (35%) . MRI scans demonstrate predominantly T2 hyperintense (82%) or isointense (18%) lesions compared to muscle and T1 isointense (61%) or hypointense (39%) lesions with homogenous contrast enhancement and a mean apparent diffusion coefficient (ADC) on diffusion weighted imaging (DWI) of 0.57 x 10-3 mm2/s . Fluorodeoxyglucose (FDG)-positron emission tomography (PET) scans are increasingly being used for diagnosing extramedullary disease, with MS lesions displaying moderate uptake of FDG . A retrospective study including pediatric patients showed a sensitivity of 93% and a specificity of 71.4% limited by difficulty differentiating extramedullary leukemia disease from infectious/inflammatory entities . The recent PETAML trial however prospectively evaluated adult patients with AML prior to therapy initiation with total body 18FDG PET/CT scans to determine prevalence of extramedullary disease. This showed a prevalence of 22% with a sensitivity of 77% and specificity of 97% . Interestingly, leukemia cutis and CNS meningeal involvement were not necessarily 18FDG-PET-avid . In addition, there were four patients who remained with residual 18FDG-PET-positive lesions despite complete marrow remission. Three of those four subsequently relapsed, suggesting there may be a specific role for 18FDG-PET imaging for remission evaluation of patients with AML . Consideration should be given to prospectively evaluating patients with AML to identify MS lesions requiring focused follow-up and possible treatment modifications and may be of value in designing de novo AML clinical trials, particularly in pediatrics with a high incidence of MS. 5. Pathology of Myeloid Sarcomas MS are infiltrative tumor masses of myeloid blasts that efface or disrupt the normal architecture of the involved organ. The leukemic blasts found in MS have heterogeneous morphology; however, monocytic differentiation is common where the blasts will show either myelomonocytic or monoblastic morphology . An example of the histology of MS is shown in Figure 2. Immunophenotypic profiling by flow cytometry or immunohistochemical stains is often necessary for a definitive diagnosis, as many of these tumor masses may resemble carcinoma. Evaluation of markers of immaturity, including CD34 and CD117, are helpful in addition to other markers which are variably expressed on myeloid blasts including CD13, CD33, CD68 (KP1), CD45, and myeloperoxidase (MPO). In the setting of monocytic differentiation, expression of monocytic markers such as CD68, CD163, CD14, and/or non-specific esterase (NSE) can be seen. Several translational studies have begun to investigate the genetic landscape of MS lesions in isolation as well as in comparison to their paired intramedullary leukemia counterparts. One recent study evaluated 7 adult trios of AML, MS, and normal tissue using capture-based next generation sequencing (NGS) of 479 cancer genes. Genes recurrently altered in these patients included KMT2A, FLT3, NRAS, CEBPA, TP53, WT1, and NPM1, with 84% of variants found in the AML also present in the MS . Three of the seven patients had additional variants detected in the MS compared to the AML including additional FLT3, SETD2, and NF1 mutations in the MS, while two had additional variants of U2AF1 and RAD21 in the AML but not the MS . In the relapsed MS samples, there were increased single nucleotide variants (SNV) in the MS . Another study evaluated 6 isolated MS tumors (without concurrent AML) and performed a 21 gene targeted panel of AML and MDS associated genes. They found recurrent variants in the genes for FLT3 (50%), NPM1 (33%), and KIT (67%) and additional variants in WT1, SF3B1, EZH2, ASXL1, and TET2 in one MS each . The genomic reports of patient-derived MS are all limited by targeted NGS sequencing without exploration of novel gene variants that may be specific to MS pathogenesis. Additionally, RNA transcriptome analysis of MS is lacking in the literature and provides an opportunity for investigation of transcriptome-based changes that may contribute to MS development outside of genetic mutations. Such studies may also facilitate the identification of cryptic translocations, which are common in pediatric AML . Although, typically, the genomic profile of MS is in concordance with the AML and marrow, this is not always true. Particularly in cases of isolated MS, NGS and molecular evaluation may inform targeted treatment options and should be included in diagnostic evaluation of patients. 6. Biological Understandings of Pathogenesis The biology underlying development of MS remains poorly defined with no clear molecular determinants. Biological features such as cytogenetic changes, molecular abnormalities, and cell surface marker expression are not consistent across studies. Much of the work on MS development surrounds the invasiveness of AML as studied using in vitro transwell assays and infiltration in the spleen and liver. The simple infiltration of hematopoietic organs, however, appears distinct from MS development in non-hematopoietic sites with no clear biological explanation. The development of MS appears to require leukemia mobilization/release from the marrow environment, tissue invasion, and further changes leading to a tumor/mass phenotype, as illustrated in Figure 3. These steps will be further discussed below. 6.1. CXCR4 CXCR4 (CXC chemokine receptor 4, CD184) is the receptor for the chemokine matrix cell derivative-1 (SDF-1/CXCL12) and is expressed by most tissues as well as hematopoietic stem cells and leukemic blasts wherein it facilitates the retention of hematopoietic stem cells in the bone marrow niche . The CXCR4/SDF-1 axis may contribute to chemoresistance through downstream signaling cascade dysregulation within leukemia cells . Higher CXCR4 expression has been seen in AML patients with extramedullary infiltration at diagnosis and extramedullary infiltration in childhood ALL . The proposed mechanism of extramedullary involvement in acute leukemias is altered bone marrow homing and increased peripheral blood dissemination via a chemotactic gradient of SDF-1 with increased CXCR4 expression on the leukemia cells . CXCR4/SDF-1 can promote the retention of AML cells within the skin of children with AML; however, CXCR4 expression by peripheral blood blasts was no different in patients with or without skin involvement . Furthermore, a lack of association between SDF-1 polymorphisms and MS implies that small variants do not contribute to extramedullary disease development, although these have been previously of interest and described . More common in adults, NPM1-mutated AML is associated with extramedullary disease and is associated with downregulation of CXCL12 and CXCR4 gene pathways . While CXCR4 expression and signaling may be a contributing factor to extramedullary disease, its impact appears limited to initial release and migration of leukemia cells from the marrow and is not specific to MS development. Further work is needed to better characterize this mechanism and whether or how CXCR4 is contributing to discrete MS formation. 6.2. CD56 CD56 (also known as neural cell adhesion molecule-1 or NCAM1) is normally expressed by natural killer (NK) cells and other immune cell subtypes and is housed on chromosome 11q23.1. It is frequently described as part of the immunophenotype of AML with MS . Expression patterns of CD56 are not consistently described, however, and in a population of adult t(8;21) AML patients, there was no association between CD56 expression and presence of extramedullary disease . AML in adults with CD56 positivity is more commonly associated with worse 5-year EFS and OS; however, a report in low-risk patients shows no association with outcome . Additionally, post-allo-HSCT CD56 positivity is not associated with extramedullary relapse . Despite the frequent CD56+ immunophenotype, there is no described mechanism or in vitro data to suggest the significance of this finding. Additional experimental studies are required to determine if CD56 is simply a biomarker of MS or is required for MS development. 6.3. Integrins and Cell Adhesion Molecules (CAMs) An AML-extracellular matrix interaction is likely critical to the development of MS. This is illustrated in transcriptome analysis of adult patient-derived AMLs demonstrating enrichment of cell surface gene sets in those AMLs with concomitant MS . This includes integrin-a7 (ITGA7), which showed a higher expression in AML with associated MS in addition to high expression in MS samples . Laminin 211 is a specific ligand of integrin-a7 that signals through the ERK signaling cascade . While there is much described about the role of integrins and selectins in migration and homing of hematopoietic stem cells, there remains no clear mechanism by which these molecules facilitate MS formation . Further study is needed to better evaluate the role of cell adhesion molecules in MS development and whether targeting these cell interactions may provide therapeutic benefit for patients with MS. 6.4. Vascular Endothelial Growth Factor (VEGF) and Receptor (VEGFR) Angiogenesis plays a notable role in acute leukemia with increased microvascular density in AML and adult MS . VEGFR2, the major mediator of the mitogenic, angiogenic, and permeability effects of VEGF, may contribute to the development of MS . VEGF signaling via the PI3K/Akt pathway in the setting of hERG1 expression was necessary for an in vitro migratory phenotype in AML cells . In adults, the small molecule VEGFR2 tyrosine kinase inhibitor apatinib (also known as TN968D1) demonstrated enhanced antileukemic effects in ex vivo cytotoxicity studies from patient-derived AML samples with associated extramedullary disease . Angiogenesis is well-described in the pathogenesis of other malignancies and it is reasonable to think that a unique perturbation may play a role in the migration or tumor formation of MS. 6.5. Matrix Metalloproteinases (MMP) In vitro studies have described the role of MMP secretion (MMP-2 and MMP-9) by leukemia cells contributing to invasion capacity, most notably of the blood-brain barrier, with upstream regulation by mitogen-activated protein kinases (MAPKs) and phosphoinositide 3-kinase (PI3-K)/AKT pathways . Additionally, TIMP-2 (tissue inhibitor of metalloproteinase 2) upregulation has been seen with increased leukemia cell line (i.e., SHI-1) invasion both in vitro and in vivo with more extensive and severe extramedullary infiltration through both MMP-2-dependent and independent activities . Other in vitro studies propose a role for the b2 integrin-proMMP-9 complex in the extramedullary phenotype of AML . Type IV collagenase secretion enhanced by TNFa and TGFb from a patient-derived MS cell line increased in vitro cell invasion with collagenase secretion demonstrated in the MS AML cell line but not other leukemia cell lines . While tissue invasion by leukemia cells is likely required for MS development, not all of the critical players have been identified. 6.6. Epigenetic Dysregulation Epigenetic dysregulation has been reported in the context of extramedullary disease and infiltration in AML. Enhancer of zeste homolog 2 (EZH2) is a histone methyltransferase and is the catalytic subunit of the Polycomb Repressive Complex 2 (PRC2), which deposits Histone 3 Lysine 27 trimethylation (H3K27me3). High EZH2 expression is correlated with higher peripheral blood blast percentages as well as extramedullary infiltration in patients with AML with numerous well-established biological roles. In vitro studies suggest that migration of AML cells appears to be regulated by EZH2/p-ERK/p-cmyc/MMP-2 and E-cadherin signaling pathways . EZH2 is a frequently mutated gene in AML; however, EZH2 has a variety of biologic influences and a unique role in MS formation remains undefined . Altered DNA methylation is another described mechanism in the development of extramedullary disease with key enzymes frequently mutated in AML. DNA methyltransferase 3A (DNMT3A) mutations contribute to altered DNA methylation, subsequently resulting in increased expression of a subset of genes with specific roles in myeloproliferation and extramedullary hematopoiesis . DNMT3A mutation appears to contribute to extramedullary CNS infiltration mediated by overexpression of TWIST1, a key epithelial mesenchymal transition transcription factor, which is not otherwise well described in AML . Furthermore, TET2 is a member of the ten-eleven translocation (TET) gene family and is a key enzyme for DNA demethylation and a critical regulator for hematopoietic stem cell homeostasis. Models using TET2-deficient mice demonstrated not only high incidence of MS development but also transplant ability of the MS cells as well as an in vivo response to azacitidine treatment . Decreased TET2 expression was also seen in patient-derived MS samples with further suggestion of methylation changes impacting MS development . AML has many examples of mutations in epigenetic pathways that are enriched in AML more than many other disease entities and may not be directly related to their involvement in MS . The role of epigenetic dysregulation in leukemia migration and invasion with described MS phenotypes is intriguing yet requires further study. Additional research may uncover future targetable pathways for MS treatment, and as noted below, case reports have demonstrated the safety and efficacy of hypomethylating agent use for patients with MS. 6.7. Other Biological Associations Mesothelin (MSLN) is a cell surface protein hypothesized to be involved in cell adhesion and is overexpressed in a subset of AML patients. MSLN overexpression was strongly associated with KMT2A-R, t(8;21), and inv(16) as well as the presence of extramedullary disease in children and young adults with AML. Methylation profiling further demonstrated an inverse association between MSLN promoter methylation and MSLN expression, suggesting another impact of epigenetic dysregulation . Versican (VCAN) overexpression in the setting of NPM1-mutated AML is associated with an invasive phenotype and higher expression levels in patients with skin infiltration . Lysyl oxidase (LOX), which has roles in pediatric acute megakaryoblastic leukemia and in the creation of a growth permissive fibrotic microenvironment, was associated with increased extramedullary disease in adults with AML and high plasma LOX activity . WT1 overexpression has also been described in MS cases as well as in extramedullary relapsed disease . ERG transcription factor overexpression, similar to that of Ewing sarcoma, has been seen in patient-derived MS samples . Multiple studies describe other associations observed in AML and extramedullary disease, including increased expression of amyloid precursor protein (APP) in AML1/ETO leukemia cells perhaps mediating the p-ERK/c-Myc/MMP-2 pathway, expression of miR-29c&b2, circular RNA expression patterns, and expression of CD25 and CD117 . Polo-like kinase 1 (PLK1), which is involved in cell cycle control, was effectively inhibited in vivo using a patient-derived leukemia in mice with improvement in extramedullary disease . PD-1 and PD-L1 have been investigated given the described efficacy of checkpoint inhibitors; however, there was no difference in expression of PD-1/PD-L1 in MS tested, and they may instead have more impact in the surrounding tumor microenvironment . Using mouse models, others observe a maturation plasticity of leukemia cells, with potential implications for chemotherapy resistance as a mechanism for extramedullary relapse . A PIM2/MYC co-expressed mouse model demonstrated consistent and lethal in vivo MS development with MYC expression likely contributing to the phenotype . Mouse models have also demonstrated cooperation between MLL/AF10 and activating KRAS mutations, with increased cell adhesion properties contributing to in vivo MS formation via Adgra3 and Hoxa11 . While many different mechanisms have been suggested in the development of MS, there remains no clear understanding of the pathogenesis. As such, it is hard to definitively identify the potential molecular determinants causing MS formation is some AML patients but not others. While the pathogenesis remains to be fully elucidated, prior studies suggest that there are likely multiple steps leading to MS development, including release from the bone marrow (which may be represented by higher WBC counts associated with MS), tissue invasion, and discrete mass formation, with the latter being the most consequential with regards to leukemia and the least described. Investigating how these different steps may cooperate and ultimately how the leukemia cells aggregate and sustain an aggregated phenotype requires dedicated study. Furthermore, the immune evasive or immunosuppressive microenvironment of MS illustrated in the post-allo-HSCT setting highlights that there is much more to learn about the pathogenesis of MS and its uniqueness with respect to its systemic/intramedullary AML counterpart. 7. Treatment Considerations There is no consensus on the best treatment approach for management of MS, particularly isolated extramedullary disease. In pediatrics, systemic chemotherapy has been favored with consideration of allo-HSCT independent of the presence of MS. The general approach to management in pediatric patients has evolved over the last three decades. In prior large cooperative group study treatment protocols (e.g., CCG 2961), children with MS would receive radiation therapy to the affected sites following initial induction chemotherapy, given MS responsiveness to irradiation. Although part of protocol therapy, many patients were not irradiated and outcomes demonstrated no difference in 5-year EFS, similar to smaller cohorts . In adults, radiation therapy is more commonly used to treat isolated relapses, but the effects are not typically sustained and both localized and medullary relapse following radiotherapy are common . Although prior COG studies included radiotherapy for treatment of MS sarcomas, this is no longer standard of care in the US; however, it continues to be recommended for MS in Berlin-Frankfurt-Munster (BFM) studies . Given the epigenetic basis of AML development, inclusion of novel epigenetic approaches in treatment are increasing in utility for AML . The hypomethylating agents azacitidine and decitabine have demonstrated efficacy in management of extramedullary disease in AML, including in pediatric patients . Case reports in pediatrics have demonstrated complete response to monotherapy with azacitidine in MDS patients who received allo-HSCT as consolidation . In the setting of post-allo-HSCT relapses of MS, multiple case reports in adults demonstrate efficacy of azacitidine or decitabine including complete response . Hypomethylating agents in adults with AML and extramedullary disease showed improvement after one-two cycles and complete or near complete resolution of MS following four-five cycles . Venetoclax has also shown activity against MS . The utility of venetoclax and hypomethylating agents suggests a role for epigenetic reprogramming as a means for MS treatment, although DNA methylation-based mutations including DNMT3A, IDH1, IDH2, and TET2 are far less common in children than in adults and translation of utility is more challenging . While no consensus exists regarding optimal treatment of MS, particularly in pediatrics, radiation therapy is unlikely to contribute to durable remission of disease and expanding chemotherapeutic options to include hypomethylating agents and venetoclax in both initial chemotherapy regimens or as maintenance therapy following allo-HSCT should be considered and deserves further investigation. 8. Conclusions: Knowledge Gaps and Areas for Improvement Children with AML and MS are distinct from adults. Given these differences, it is necessary to further study MS in the context of the driver lesions specific to children. MS remains a known clinical presentation with unclear impact on prognosis, risk stratification, and potential consequences in the setting of allo-HSCT. The advancement of imaging techniques and data for MS provides the opportunity for more directed and prospective evaluation in children. Collectively, this highlights the need for further large-scale cooperative group studies with clear criteria for the identification of MS in children. While there is no specific treatment approach for children with MS, the use of intensive systemic chemotherapy remains at the forefront. However, additional studies are required to determine if epigenetic or immuno-oncology therapies may be beneficial. The role of allo-HSCT continues to be important as a curative option for many patients with high-risk AML; although, considering its potential lack of efficacy in the setting of extramedullary disease, the role of an immunosuppressive microenvironment in MS requires additional study. Further investigation into the potentially immunosuppressive MS microenvironment will be crucial to improving efficacy of allo-HSCT and managing isolated extramedullary relapses post-HSCT. Although many different biological associations exist, there is an ongoing lack of clarity as to how leukemic blasts can not just invade tissues but form discrete tumors. Experiments delineating the potential epigenetic and transcriptomic differences between medullary AML disease and MS are required to identify the underlying molecular mechanisms that promote MS development. Understanding how leukemic blasts transform into and sustain an MS phenotype is critical to identifying specific targetable mechanisms. Understanding and combatting chemotherapy resistance and immune escape will ultimately improve survival in patients with AML and MS. Author Contributions Conceptualization, K.E.Z. and S.R.; writing--original draft preparation, K.E.Z., A.M.C., and S.R.; writing--review and editing, K.E.Z., A.M.C., A.E.M., K.S.C. and S.R.; visualization, K.E.Z. and A.M.C.; supervision, S.R.; project administration, S.R.; funding acquisition, S.R. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Common locations of initial presentation of MS in children with percentage of MS site involvement. Abbreviations: CNS, central nervous system; MS, myeloid sarcoma . Figure created with BioRender.com. Figure 2 Histology of myeloid sarcoma involving the psoas muscle. (A, 500x). The tumor cells are blasts with irregular/convoluted nuclei, finely dispersed chromatin, and small distinct nucleoli. The inset (400x) shows the tumor cells infiltrating between skeletal muscle fibers. The tumor cells are immunoreactive for CD33 (B, 100x), CD163 (C, 100x), and CD45 (D, 100x). Figure 3 Depiction of MS development in AML with proposed mediators. Initial release/migration of leukemic blasts from the bone marrow into the peripheral blood circulation, followed by extravasation and invasion into distant tissue spaces (e.g., subcutaneous tissue). This results in organization of those extravasated cells into a mass with subsequent tissue architectural distortion and gross observation and clinical symptoms. Abbreviations: CAMs, cell adhesion molecules; MMPs, matrix metalloproteinases; VEGF, vascular endothelial growth factor; VEGFR, vascular endothelial growth factor receptor. Figure created with BioRender.com. cancers-15-01443-t001_Table 1 Table 1 Summary of survival outcomes of pediatric patients with AML and extramedullary disease. Described terminology as per original report. Abbreviations: YO, years old; EMD, extramedullary disease; CSF, cerebral spinal fluid; EML, extramedullary leukemia; EMI, extramedullary infiltration; MS, myeloid sarcoma; EFS, event free survival; OS, overall survival; RFS, relapse free survival; SE, standard error; AML, acute myeloid leukemia; CI, confidence interval . Study/Publication Age Extramedullary Disease Involvement Study Definitions Population Incidence 5-Year Estimated EFS (+-SE) or (95% CI) 5-Year Estimated OS (+-SE) or (95% CI) POG8821 (Chang, et. al., 2000) <21 yo EMD: including CSF disease, not defined n = 492 Any EMD 10.4% 4-year EFS Not available CSF only 4.7% CSF only: 34.8 +- 9.9% p = 0.91 Non-CSF EMD 5.7% Non-CSF EMD: 21.6 +- 8.6% p = 0.043 No EMD: 34.4 +- 2.5% p = 0.18 DCLSG (Bisschop et. al., 2001) 0-16 yo EML: Clinically obvious infiltrate in soft tissues, skin, muscles or bone, gingiva, CSF or brain n = 477 EML in 25.1% No EML 38% +- 3% p = 0.85 Not available Myeloblastoma (MS) 43 +- 13% Skin infiltrates 45 +- 21% Children's Cancer Group, CCG AML 213 and 213P, 2861 and 2891 (Dusenbery et. al., 2003) 0-21 yo "Chloroma" on data entry form yes or no, gum only not included n = 1832 Skin EML +- other 5.9% Skin +- other: 26% (17-35%) p = 0.005 Not available "Skin involvement" yes or no Non skin EML 4.9% Non skin EML: 46% (34-58%) EML 10.9% Non EML: 29% (27-32%) Single Center--Turkey (AML-90 and AML-94 protocols) (Hicsonmez et. al., 2004) <17 yo EMI: involvement of gingiva, CNS, orbit, soft tissue, bone, pleura n = 127 EMI total in 40% 4-year EFS: Not available Gingiva only in 11% AML-90 therapy: MS = 0% p < 0.05 Orbital in 10% Without EMI = 37 +- 11% MS in 21% AML-94 therapy: MS = 56 +- 17% p > 0.05 Without EMI = 31 +- 1% Japanese childhood AML cooperative study group (Kobayashi et. al., 2007) <16 yo CNS disease (>5 WBC/mL with blasts) n = 240 EMI in 23.3% 3-year estimate EFS 3-year OS EMI: leukemic infiltration in organs other than liver, spleen, lymph nodes (including CNS disease) (Excluding CSF only: 20.4%) EMI: 53.3 +- 6.7% p = 0.11 EMI: 77.3% No EMI: 62.5 +- 3.6% No EMI: 77.6% EMI + WBC > 100 x 109/L: 23.8 +- 12.9% p = 0.0052 No EMI or EMI + WBC < 100 x 109/L: 60 +- 3.5% Children's Oncology Group (CCG 2861, 2891, 2941, 2961) (Johnston et. al., 2012) 0-21 yo CNS3 (>=5 WBC/mL with blasts) n = 1459 CNS3 11% No MS 40 +- 3% p = 0.005 No MS 50 +- 3% p < 0.001 CNS MS (brain or spinal cord tumor) CNS MS 1% CNS MS 52 +- 21% CNS MS 73 +- 19% Orbital MS 2% Orbital MS 76 +- 17% Orbital MS 92 +- 11% Non CNS MS 4% Non CNS MS 34 +- 13% Non CNS MS 38 +- 13% European AML Study Groups (Creutzig et. al., 2017) 0-17 yo CNS involvement n = 2365 CNS 11.0% CNS + 48 +- 3% p = 0.11 CNS + 64 +- 3% p = 0.23 (CSF with >5 WBC/mL with blasts or intracranial infiltrates on imaging or neurologic symptoms) CNS--52 +- 2% CNS--67 +- 1% NOPHO AML 2004 (Stove et. al., 2017) 0-17 yo MS: myeloblast tumor n = 322 MS (+- CNS disease) 15.8% EML: 54% (42-65%) p = 0.57 p = 0.008 CNS disease (>= 5 WBC/mL with blasts or new neurologic symptoms) CNS only an additional 7% No EML: 45% (37-51%) EML: 64% (51-74%) EML: MS or CNS disease No EML: 73% (66-78%) Single Center--India (Pramanik et. al., 2018) 0-18 yo MS (did not include CSF only disease) n = 570 MS in 21.2% Median EFS: p = 0.002 Median OS: p = 0.002 AML with MS: 21.6 months With MS: 26.3 months AML without MS: 11.1 months Without MS: 12.7 months TARGET dataset (COG-NCI) (COG AAML03P1, AAML0531, CCG-2961) (Xu et. al., 2020) <18 yo MS on biopsy diagnosis, excluding CSF disease n = 884 MS in 12.3% MS: 35.4 +- 4.6% p = 0.001 MS: 53.4 +- 4.8% p = 0.008 Non-MS: 48.5 +- 1.8% Non-MS: 64.0 +- 1.8% Single Center--Korea (Lee et. al., 2020) <18 yo EMI: excluded CSF only n = 40 EMI in 30% EMI: 50.0 +- 14.4% p = 0.022 Not available Only RUNX1-RUNX1T1 AML No EMI: 78.6 +- 7.8% Single Center--China (Hu et. al., 2020) <=18 yo MS: including lymph nodes >2cm, excluded CNSL n = 214 MS in 20.6% 3-year RFS p = 0.000 3-year OS p = 0.01 Only Low Risk AML (includes Hu et. al., 2021 study) With MS: 62.6 +- 7.5% With MS 73.5 +- 7.1% Without MS: 87.0 +- 2.8% Without MS 88.8 +- 2.6% Single Center--China (Hu et. al., 2021) 1-18 y MS: clinical, biopsy, radiology findings n = 127 MS in 23.6% 3-year RFS p = 0.004 3-year OS p = 0.249 Only t(8;21) AML CNS MS: dura deposits or paraspinal tumor With MS: 68.8 +- 8.8% With MS: 78.1 +- 8.1% o Without MS: 88.0 +- 3.4% Without MS: 86.4 +- 3.7% Polish Pediatric Leukemia and Lymphoma Study Group (Samborska et. al., 2022) 0-18 yo MS: pathology diagnosis or extramedullary tumor and concurrent bone marrow disease (AML, MDS) n = 43 MS in 100% De novo: 0.56 +- 0.12 p = 0.0247 pOS p = 0.0251 De novo/isolated in 37.2% Concurrent: 0.82 +- 0.08 De novo: 0.56 +- 0.12 Concurrent in 55.8% Concurrent: 0.84 +- 0.09 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000482 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050694 healthcare-11-00694 Article Attitudes and Knowledge Regarding the Therapeutic Use of Cannabinoids among Community Pharmacists: A Pilot Cross-Sectional Study in Amman, Jordan Bazzari Firas H. 1* Bazzari Amjad H. 2 Sessa Francesco Academic Editor 1 Faculty of Pharmacy, Jerash University, Jerash 26150, Jordan 2 Department of Basic Scientific Sciences, Faculty of Arts & Sciences, Applied Science Private University, Amman 11931, Jordan * Correspondence: [email protected] 26 2 2023 3 2023 11 5 69412 1 2023 02 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). There is an increasing interest in the therapeutic use of cannabis worldwide, with a number of cannabinoid-derived drugs currently approved by the Food and Drug Administration (FDA) for certain indications. This study was conducted via a printed questionnaire and aimed to explore the attitudes and knowledge regarding the therapeutic use of cannabis and cannabinoids among community pharmacists residing in Amman, Jordan. The results revealed a neutral to low agreement level regarding the medical usefulness of cannabis; however, a higher agreement level was observed for FDA-approved cannabinoid-derived drugs. The majority of the participants reported that they did not learn enough regarding cannabinoids, do not adequately remember what they have learned, and do not actively look for information after graduation. The average percentages of correct identification of cannabis/cannabinoid FDA-approved drug indications, common adverse effects, interacting drugs, and cautions/contraindications were 40.6%, 53%, 49.4%, and 57.3%, respectively, with an overall correct identification rate of 51.1% of the participants. In conclusion, the results indicate an inadequate level of knowledge with a significant room for improvement regarding the various aspects of cannabinoid pharmacology. pharmacy practice medicinal cannabis cannabinoids cannabinoid-derived drugs pharmacology community pharmacy This research received no external funding. pmc1. Introduction Cannabinoids are naturally derived compounds from Cannabis sativa, family Cannabaceae, which has been cultivated by mankind since old times for medical applications . The recorded history of cannabis use dates back to ancient China and was pharmacologically described as a medicine in Chinese early medical books for a number of uses, such as chronic pain associated with rheumatoid arthritis, gastrointestinal-related disorders, gynecologic pain conditions, and malaria among multiple other uses . The therapeutic use of cannabis flourished in the west in the late 19th and early 20th century. However, the active constituents of the plant were yet to be determined at the time and the first active compound, tetrahydrocannabinol (THC), was later isolated in 1964 . This delay has led to the displacement of cannabis with other medications, such as aspirin, for their well-defined safety and efficacy profiles when compared to the variations of cannabis extracts . Cannabis was brought back to the picture as a potential therapeutic candidate following the discovery of the endocannabinoid system, which consists of endogenous cannabinoids, such as anandamide and 2-arachidonoyl-sn-glycerol (2-AG), and cannabinoid receptors (i.e., CB1 and CB2) . Endocannabinoids are found to play a role in tuning synaptic function and, in turn, influence a variety of physiological and behavioral processes . This is in addition to a multitude of central effects attributed to the use of cannabis . Extensive scientific research efforts have warranted Food and Drug Administration (FDA) approval for a number of cannabis-derived and synthetic cannabis-related drug products for selected indications . Currently, Epidiolex(r) (a purified cannabidiol) is approved for the use in patients >=2 years old with Lennox-Gastaut syndrome and Dravet syndrome and for patients >=1-year old with tuberous sclerosis complexes . In addition, Marinol(r) and Syndros(r), both containing dronabinol (a synthetic derivative of THC), are approved for nausea associated with cancer chemotherapy and anorexia associated with weight loss in acquired immunodeficiency syndrome (AIDS) patients . Lastly, Cesamet(r), which contains nabilone (a synthetic derivative of THC), is approved for the nausea associated with cancer chemotherapy . On the other hand, the FDA is aware of the use of multiple unapproved cannabis and/or unapproved cannabis-derived products for the management of certain conditions and, thereby, the FDA highlights a caveat regarding the safety and effectiveness of unapproved compounds . In contrast, the European Medicines Agency (EMA) only authorized the use of Epidiolex(r) (cannabidiol) and for the same indications approved by the FDA . Pharmacists are primary healthcare providers with an integral role in medication stewardship. In some countries, pharmacists are the point of access to medicinal cannabis and the main reference for patients and prescribers regarding the proper medical use of cannabis . The use of medicinal cannabis is not permitted and no FDA-approved cannabinoid-based medication is currently available in Jordan, which is similar to other Middle East countries (except for Lebanon) . While no specific number for pharmacists is available, recent reports by the ministry of foreign affairs and expatriates show that there is well over a million Jordanian citizens (around 10% of the total population) living abroad . In addition, a total of 18,373 international students from 64 different countries are currently enrolled in Jordanian universities, 19.9% of whom are medical and health-related students, according to the 2019/2020 annual report by the ministry of higher education and scientific research . From a national point of view, the Jordan FDA (JFDA) is the official body responsible for the registration of new drugs in the country and among the basic requirements is the approval and registration of the drug in the country of origin . These findings and the unique position of pharmacists as drug experts necessitates them to be knowledgeable enough regarding herbal and synthetic pharmacologically active compounds, even with unavailable status as for cannabinoids, to ensure patient safety . This entails the ability to evaluate approved drug indications, contraindications, interactions, and adverse events through an evidence-based approach. This pilot study aims to assess the attitudes and knowledge regarding the therapeutic use of cannabinoids and cannabinoid-derived drugs among community pharmacists in Amman, Jordan, in order to identify areas for improvement in pharmacy program curricula and/or continued education to ensure that community pharmacists are equipped with adequate and accurate knowledge to provide patient education regarding the medical use and harms of cannabis and cannabinoid-based drugs if required. 2. Materials and Methods 2.1. Sample The pilot sample size was determined as described by Viechtbauer et al. using the following equation:n=ln(1-g)ln(1-p) The required sample was 59, confidence interval 95% (g = 0.95) with probability (p = 0.05), and a total of 60 participants were included in the study. 2.2. Protocol and Ethical Considerations The pilot survey was conducted using a printed questionnaire in English, the official teaching language for pharmacy programs in Jordan, and distributed by the researchers among community pharmacists residing in Amman during working hours. An explanation of the study aims was provided prior to handing the questionnaire. The participants were informed that no personal identifying information will be asked and the collected data will be solely used for scientific research purposes. The participation was voluntary, and the participants were not paid or compensated. The study was approved by the department of pharmacy council at Jerash university (approval number: 2/'/2022, date: 21 November 2022), and was conducted with strict adherence to the guidelines of the declaration of Helsinki regarding anonymity, voluntary participation, and data protection . 2.3. Questionnaire The study questionnaire included three main domains: (1) demographics, (2) attitudes (i.e., personal opinions), and (3) knowledge. The demographics domain included questions regarding the age, gender, graduation date, years of community pharmacy practice, grade point average (GPA) rating, and educational level (i.e., if the participants hold any postgraduate degree). The attitudes domain included a total of 6 questions; (1) "Do you think that cannabis has medical usefulness?", (2) "Do you think cannabis-derived FDA-approved drugs are useful?", (3) "Do you think medicinal cannabinoid benefits outweigh their risks?", (4) "Do you think you learned enough about medicinal cannabinoids during your undergraduate studies?", (5) "Do you think you adequately remember what you learned?", and (6) "Do you think you are knowledgeable enough to educate patients on the adverse effects, interactions and contraindications of cannabinoids?". The responses to the previous questions were based on a 5-point Likert agreement scale; (1) "To a very high degree", (2) "To a high degree", (3) "Moderate", (4) "To a low degree", and (5) "To a very low degree". In the knowledge domain, the participants were initially asked whether they learned about cannabis and cannabinoids after graduation to account for any influence of self-learning, if yes, the participants were then asked if they purposely sought the information or if it was by chance and which sources of information they used (i.e., books, scientific articles, news, or the Internet). Then, the participants were asked "What central pharmacological effects do cannabis or cannabinoids have?", to assess their general perceptions of central cannabinoid effects, and given the following options "Hallucinogenic", "Depressant", "Stimulant", "All answers", or "None of the answers". Lastly, the participants were asked to answer 4 checkbox questions regarding the indications of FDA-approved cannabinoid-derived drugs as well as cannabis/cannabinoids adverse effects/events, moderate/major drug interactions, and contraindications. The aforementioned questions were developed based on the discussion of scientific literature and reputable sources . 2.4. Statistical Analysis The data analysis was conducted using JASP software (Version 0.16.2, www.jasp-stats.org). All the results are presented as mean +- standard deviation (+-SD) or as counts (n) and percentages (%). The gender-based differences between the participant demographic variables were assessed using either t-test for parametric data (age and years of experience) or Chi-square test for non-parametric data (education and GPA rating). The distribution of the participant responses to attitudes questions, based on a 5-point Likert agreement scale, and knowledge questions were compared across genders and GPA ratings using Chi-square test. To assess the influence of age and experience on participant attitudes, the responses were coded into ordinal variables and Spearman's rank correlation test was conducted. The reliability of the attitudes questions was assessed using the single-test reliability analysis, and the Cronbach's a was calculated. For all the statistical tests, a p value less than 0.05 was considered significant (*). 3. Results 3.1. Participant Demographics The study included the responses of a total of 60 on-duty community pharmacists residing in Amman, Jordan, from both genders: males (n = 18, 30%) and females (n = 42, 70%). All 60 participants completed their undergraduate degree in pharmacy from universities in Jordan and all completed the questionnaire; thus, no responses were excluded. The mean age of all the participants was 30.48 years (SD +- 8.6), ranging from 22 to 59 years of age with from 1 to 38 years of experience in community pharmacy (6.37 +- 7.53 years). The mean age, and accordingly years of experience, was higher for males (35.06 +- 10.95 years of age) compared to females (28.52 +- 6.6, p < 0.05). The vast majority of participants (95%) had a bachelor level of education while three participants (5%) were master's degree holders. The self-reported undergraduate GPA rating was collected as well. The number of participants reporting an Excellent, Very Good, Good, and Satisfactory GPA rating was 8 (13.3%), 22 (36.7%), 26 (43.3%), and 4 (6.7%), respectively. The GPA rating variable was dependent on gender (kh2 = 10.7, p < 0.05) with a higher percentage of females exhibiting an Excellent GPA rating (16.67%) and a lower percentage with a Satisfactory rating (0%) compared to the male participants (5.56% and 22.2%, respectively). The collected participant demographics are summarized in Table 1. 3.2. Attitudes towards Medicinal Cannabinoids The attitudes of the participants toward the medical usefulness of and their education regarding medicinal cannabinoids were assessed using six questions based on 5-point Likert agreement scale ranging between "To a very high degree" and "To a very low degree". The internal reliability of these questions was adequate with a Cronbach's a of 0.71 (95% confidence interval: 0.57-0.81). The attitudes questions and participant responses are summarized in Table 2. When asked about their opinion on whether cannabis has medicinal usefulness, most participants (36.7%) were neutral with a "Moderate" response, followed by "Low" agreement (25%), "High" agreement (20%), "Very low" agreement (15%), and lastly "Very high" agreement (3.3%). The response distribution of this question was dependent on gender (kh2 = 15.2, p < 0.01) as most male participants (61.1%) were in disagreement while most females (45.2%) were neutral. However, the agreement rate was similar between genders (22.2% and 23.8% for males and females, respectively). The participant agreement rate was higher (35%) when asked regarding the medicinal usefulness of cannabis-derived FDA-approved drugs while the majority (41.7%) were neutral. In contrast to medicinal cannabis, most males were in agreement with FDA-approved cannabinoid medications (44.4%) while most females (47.6%) were neutral; thus, the responses to this question were gender-dependent (kh2= 12.6, p < 0.01). On the other hand, gender did not influence the third question responses on whether the benefits of medicinal cannabinoids outweigh their risks (kh2 = 6.08, p > 0.05) as the majority (50%) of participants were in disagreement including both males (44.4%) and females (52.4%), while only 15% agreed. Regarding their personal opinions on their undergraduate education about medicinal cannabinoids, most participants do not think they learned enough (53.3%), adequately remember what they learned (50%), or are knowledgeable enough to educate patients on corresponding adverse effects, interactions, and contraindications (46.7%). A summary of participant attitude responses can be found in Table 2. The distribution of participant responses to all six attitudes questions was independent from the GPA rating (p > 0.05) and did not correlate with either age or years of experience (p > 0.05). The impact of participant demographics on the attitude responses is summarized in Table 3. 3.3. Knowledge of Medicinal Cannabinoids Following the collection of participant demographics and attitudes, the third part of the questionnaire focused on assessing the knowledge of participating community pharmacists regarding the pharmacology of medicinal cannabinoids. In order to control for the potential influence of self-learning, the participants were first asked whether they learned about cannabis or medicinal cannabinoids following the completion of their undergraduate studies, if it was by chance or out of self-interest and which sources they sought the information from. One third of the participants (n = 20) reported learning about cannabinoids following graduation, of whom 14 participants (23.3% of total) actively sought the information; however, the most-sought source of information was the Internet (n = 9), followed by scientific articles (n = 7) and books (n = 4); therefore, none of the participants received formal postgraduate education on medicinal cannabinoids. Then, the participants were asked about the central pharmacological effects of cannabis and given the following options: "Hallucinogenic", "Depressant", "Stimulant", "All answers", and "None of the answers". Most participants answered with "Hallucinogenic" (40%), followed by "All" (25%), "Stimulant" (20%), "Depressant" (11.7%), and "None" (3.3%). As summarized in Table 4, the distribution of answers to this question was independent from gender (kh2 = 1.53, p > 0.05) and the self-reported GPA rating (kh2 = 7.13, p > 0.05) and was very similar between the participants who did not learn about cannabis or medicinal cannabinoids following graduation and those who reported learning (kh2 = 3.08, p > 0.05). The participants were then assessed regarding four key pharmacological aspects of medicinal cannabis and cannabinoids: FDA-approved indications, adverse effects, drug interactions, and cautions/contraindications, Table 5. For each of these categories, the participants were presented with options that included correct and incorrect answers and asked to identify the correct ones. The options were provided for each pharmacology question in no particular order and each participant was allowed to choose one, multiple, or all answers. The average percentages of the correct identification of cannabis/cannabinoid FDA-approved drug indications, common adverse effects, interacting drugs, and cautions/contraindications were 40.6%, 53%, 49.4%, and 57.3%, respectively, with an overall correct identification rate of 51.1% of the participants. On the other hand, the percentages of identifying an incorrect indication, adverse effect, interacting drug, and caution/contraindication were 44.6%, 24%, 20.4%, and 22.2%, respectively, with an overall incorrect identification rate of 27.9% of the participants. Interestingly, out of a total of 35 options, the identification of only 3 was dependent on gender, which were incorrect options, and of only 2 was dependent on the self-reported participant GPA rating, 1 of which was incorrect. The category with the lowest correct and also the highest incorrect identification rate was the FDA-approved indications of cannabinoid-derived drugs. 4. Discussion This pilot study is the first to explore the attitudes and knowledge regarding the therapeutic use of cannabinoids among community pharmacists in Amman, Jordan. The overall results show a low level of knowledge with a significant room for improvement in terms of cannabinoid pharmacology. The sample was consistent with the general distribution of community pharmacists in Jordan in terms of gender with a total of 64.26% females and 35.74% males as highlighted in the latest report by the Jordan Pharmacists Association (JPA) . In addition, the sample included a wide range of participants' age (from 22 to 59 years old) and experience (from 1 to 38 years). Moreover, the participants' GPA was distributed among all categories. Nevertheless, neither the GPA nor years of experience of the participants had any significant influence on their responses. Furthermore, the majority of the participants reported that they did not learn enough regarding cannabinoids, do not adequately remember what they have learned, and do not actively look for information after graduation. All combined, these factors can be considered the major contributors to the current status of pharmacological knowledge regarding the proper medical use of medicinal cannabis and cannabinoid-derived drugs. However, from a different perspective, it can be argued and justified that there is no actual need in this regard since there are no approved cannabinoid-derived drugs in Jordan. On the other hand, the recreational use of cannabis is another major factor to be considered. In countries where cannabis is legalized, recreational use was found to be dominant when compared to medical use . Consequently, calls are rising for public education and awareness regarding the harms and adverse effects of cannabis, especially given that the legalization of cannabis is generally perceived as risk free . Furthermore, the abuse of illicit synthetic cannabinoids is also rising and is considered a global health concern . A recent study by AbuAlSamen et al., conducted to assess the knowledge and perceptions of illicit synthetic cannabinoids among Jordanian university students, revealed the poor knowledge of the students about illicit synthetic cannabinoids; nevertheless, the vast majority of the students considered the use of illicit synthetic cannabinoids to be ethically unacceptable and associated with detrimental health effects . These findings are consistent with the careful attitude observed among the sample regarding the medical use of cannabinoids. Despite that a minor fraction of participants reported looking for information regarding cannabinoids, the majority of them used the Internet as their primary sought source. On the positive side, online platforms and social media can be utilized by official bodies for spreading awareness and public education regarding the proper use and harms of certain medicines . Nevertheless, due to the limitless freedom offered by the Internet with the ability to access and share virtually anything, the accuracy of medical information remains a concern . Accordingly, the Internet can be a "dangerous" source of knowledge, since there is much news that is unofficial or incorrect. For instance, anecdotal evidence suggests that medicinal cannabis may benefit the management of chronic neuropathic and cancer-associated pain ; however, robust investigations either proved the opposite or highlighted the lack of conclusive evidence . Such claims and many other examples can sometimes be inflated by certain online news outlets and social media platforms, therefore providing inaccurate description and, in turn, creating misconceptions among the public . Therefore, continued education courses, conferences, or webinars can be considered for improving knowledge. All in all, pharmacists should always follow an evidence-based approach and be aware of such issues to ensure patient safety. In comparison to other populations, similar patterns can be found in the literature. For instance, studies of several states in the USA with implemented cannabis programs have revealed that, even after years of program implementation, there is still a significant need for further pharmacists training and education regarding various regulatory and clinical aspects of cannabinoids . Furthermore, studies conducted in Australia, Canada, European countries, and Lebanon, in addition to others, have also highlighted the need for further cannabinoid education and training for pharmacists and other healthcare professionals . On the other hand, numerous studies assessing the knowledge among pharmacy students also revealed a gap in pharmacy teaching curricula, as students were found to be neither knowledgeable enough nor confident to council patients regarding cannabinoids. These findings further necessitate the importance of incorporating competency-based courses in order to address this gap and ensure optimal patient care . Therefore, the implementation of both post-graduate courses and training are key factors to be considered. 5. Conclusions In conclusion, community pharmacists in this sample have a low and neutral agreement level regarding the therapeutic usefulness of cannabis and FDA-approved cannabinoid-derived drugs, respectively. In addition, the current results have demonstrated the inadequacy of the pharmacological knowledge of community pharmacists in Jordan regarding cannabis and cannabinoid-derived drugs. This is true across all aspects of cannabinoid pharmacology including their indications, side effects, interactions, and contraindications. The results, therefore, highlight the need for improvements in undergraduate and/or continued education in this regard. Author Contributions Conceptualization, F.H.B. and A.H.B.; methodology, F.H.B. and A.H.B.; software, A.H.B.; formal analysis, A.H.B.; investigation, F.H.B. and A.H.B.; data curation, A.H.B.; writing--original draft preparation, F.H.B.; writing--review and editing, A.H.B. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the department of pharmacy council at Jerash university (approval number: 2/'/2022, date: 21 November 2022), and was conducted with strict adherence to the guidelines of the declaration of Helsinki regarding anonymity, voluntary participation, and data protection. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Available on request from the corresponding author, F.H.B. Conflicts of Interest The authors declare no conflict of interest. healthcare-11-00694-t001_Table 1 Table 1 Participant demographics. Variable All Males Females p Value Age in years: mean (SD) 30.48 (8.6) 35.06 (10.95) 28.52 (6.6) 0.006 a,* Experience: mean (SD) 6.37 (7.53) 10.17 (10.29) 4.74 (5.36) 0.009 a,* Education: count (%) 0.897 b Bachelor 57 (95%) 17 (94.4%) 40 (95.2%) Masters 3 (5%) 1 (5.6%) 2 (4.8%) GPA Rating: count (%) 0.013 b,* Excellent 8 (13.3%) 1 (5.6%) 7 (16.7%) Very Good 22 (36.7%) 6 (33.3%) 16 (38.1%) Good 26 (43.3%) 7 (38.9%) 19 (45.2%) Satisfactory 4 (6.7%) 4 (22.2%) 0 (0%) * Significant difference between genders (p < 0.05), a t-test, and b Chi-square test. healthcare-11-00694-t002_Table 2 Table 2 Participant attitudes towards medicinal cannabinoid usefulness and education. Questions Participant Agreement Level, Count (%) Very Low Low Moderate High Very High Do you think that cannabis has medical usefulness? 9 (15%) 15 (25%) 22 (36.7%) 12 (20%) 2 (3.3%) Do you think cannabis-derived FDA-approved drugs are useful? 6 (10%) 8 (13.3%) 25 (41.7%) 13 (21.7%) 8 (13.3%) Do you think medicinal cannabinoid benefits outweigh their risks? 10 (16.7%) 20 (33.3%) 21 (35%) 7 (11.7%) 2 (3.3%) Do you think you learned enough about medicinal cannabinoids during your undergraduate studies? 13 (21.7%) 19 (31.7%) 19 (31.7%) 8 (13.3%) 1 (1.7%) Do you think you adequately remember what you learned? 7 (11.7%) 23 (38.3%) 18 (30%) 10 (16.7%) 2 (3.3%) Do you think you are knowledgeable enough to educate patients on the adverse effects, interactions, and contraindications of cannabinoids? 9 (15%) 19 (31.7%) 18 (30%) 9 (15%) 5 (8.3%) healthcare-11-00694-t003_Table 3 Table 3 Impact of demographics on participant attitudes. Questions Impact of Demographics, p Value Age a Experience a Gender b GPA b Do you think that cannabis has medical usefulness? 0.316 0.44 0.004 * 0.154 Do you think cannabis-derived FDA-approved drugs are useful? 0.476 0.528 0.016 * 0.84 Do you think medicinal cannabinoid benefits outweigh their risks? 0.08 0.096 0.193 0.275 Do you think you learned enough about medicinal cannabinoids during your undergraduate studies? 0.517 0.473 0.141 0.884 Do you think you adequately remember what you learned? 0.858 0.769 0.454 0.866 Do you think you are knowledgeable enough to educate patients on the adverse events, interactions, and contraindications of cannabinoids? 0.349 0.522 0.318 0.542 * Significant (p < 0.05), a Spearman's correlation test, and b Chi-square test. healthcare-11-00694-t004_Table 4 Table 4 Impact of demographics on participant perceptions of central cannabinoid pharmacology. Answers Count (%) a What Central Pharmacological Effects Do Cannabis or Cannabinoids Have? Hallucinogenic Stimulant Depressant All None p Value b Total 24 (40%) 12 (20%) 7 (11.7%) 15 (25%) 2 (3.33%) Gender 0.821 Males 6 (33.3%) 5 (27.8%) 2 (11.1%) 4 (22.2%) 1 (5.6%) Females 18 (42.8%) 7 (16.7%) 5 (11.9%) 11 (26.2%) 1 (2.4%) GPA rating 0.849 Excellent 5 (62.5%) 1 (12.5%) 1 (12.5%) 1 (12.5%) 0 (0%) Very Good 7 (31.8%) 6 (27.3%) 3 (13.6%) 5 (22.7%) 1 (4.6%) Good 11 (42.3%) 3 (11.5%) 3 (11.5%) 8 (30.7%) 1 (3.8%) Satisfactory 1 (25%) 2 (50%) 0 (0%) 1 (25%) 0 (0%) Self-learning after graduation 0.544 Yes 7 (35%) 6 (30%) 1 (5%) 5 (25%) 1 (5%) No 17 (42.5%) 6 (15%) 6 (15%) 10 (25%) 1 (2.5%) a Within row percentages and b Chi-square test. healthcare-11-00694-t005_Table 5 Table 5 Participants' knowledge of medicinal cannabis and cannabinoid pharmacology. Questions and Answers Count (%) a Gender, p Value b GPA, p Value b Which indications are cannabinoid-based drugs approved for by the FDA? Seizures in Lennox-Gastaut syndrome c 21 (35.0%) 0.859 0.756 Nausea associated with cancer chemotherapy c 35 (58.3%) 0.391 0.171 Anorexia in AIDS patients c 17 (28.3%) 0.574 0.168 Pain associated with cancer i 40 (66.7%) 0.550 0.226 Chronic neuropathic pain i 31 (51.7%) 0.338 0.933 Resistant major depressive disorder i 25 (41.7%) 0.153 0.214 Weight loss in obese patients i 11 (18.3%) 0.216 0.604 Which adverse effects/events are commonly caused by cannabis/cannabinoids? Anxiety c 43 (71.7%) 0.574 0.800 Memory/cognitive impairment c 42 (70.0%) 0.806 0.799 Insomnia c 30 (50.0%) 0.573 0.764 Tachycardia c 31 (51.7%) 0.866 0.995 Orthostatic hypotension c 13 (21.7%) 0.945 0.628 Anemia i/u 9 (15.0%) 0.813 0.444 Loss of appetite i/u 28 (46.7%) <0.001 * 0.402 Constipation i/u 17 (28.3%) 0.01 * 0.558 Hyperglycemia i/u 5 (8.3%) 0.61 0.727 Glaucoma i/u 13 (21.7%) 0.047 * 0.966 Which drugs have moderate or major interactions with cannabis/cannabinoids? Alprazolam c 31 (51.7%) 0.128 0.857 Fluoxetine c 25 (41.7%) 0.391 0.138 Diphenhydramine c 19 (31.7%) 0.672 0.917 Pregabalin c 27 (45.0%) 0.101 0.863 Phenytoin c 33 (55.0%) 0.955 0.635 Warfarin c 43 (71.7%) 0.574 0.629 Amoxicillin i 6 (10.0%) 0.851 0.559 Ibuprofen i 9 (15.0%) 0.581 0.208 Omeprazole i 20 (33.3%) 1.000 0.439 Acetaminophen i 14 (23.3%) 0.424 0.913 Which conditions are cautions/contraindications for cannabis/cannabinoid usage? Schizophrenia c 27 (45.0%) 0.533 0.464 Major depressive disorder c 25 (41.7%) 0.391 0.055 Cardiac arrhythmia c 36 (60.0%) 0.301 0.047 * Cardiovascular disorders c 36 (60.0%) 0.645 0.947 Pregnancy c 48 (80.0%) 0.260 0.569 Glaucoma i 15 (25.0%) 0.329 0.800 Hypothyroidism i 12 (20.0%) 0.673 0.240 Cancer i 13 (21.7%) 0.538 0.034 * * Significant (p < 0.05), a % of all, b Chi-square test, c correct, i incorrect, and u uncommon. 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PMC10000483 | Malignant pleural mesothelioma (MPM) is an aggressive thoracic cancer that is mainly associated with prior exposure to asbestos fibers. Despite being a rare cancer, its global rate is increasing and the prognosis remains extremely poor. Over the last two decades, despite the constant research of new therapeutic options, the combination chemotherapy with cisplatin and pemetrexed has remained the only first-line therapy for MPM. The recent approval of immune checkpoint blockade (ICB)-based immunotherapy has opened new promising avenues of research. However, MPM is still a fatal cancer with no effective treatments. Enhancer of zeste homolog 2 (EZH2) is a histone methyl transferase that exerts pro-oncogenic and immunomodulatory activities in a variety of tumors. Accordingly, a growing number of studies indicate that EZH2 is also an oncogenic driver in MPM, but its effects on tumor microenvironments are still largely unexplored. This review describes the state-of-the-art of EZH2 in MPM biology and discusses its potential use both as a diagnostic and therapeutic target. We highlight current gaps of knowledge, the filling of which will likely favor the entry of EZH2 inhibitors within the treatment options for MPM patients. EZH2 malignant pleural mesothelioma epigenetic tumor microenvironment macrophages immune infiltrate immunotherapy targeted therapy This research received no external funding. pmc1. Introduction Malignant pleural mesothelioma (MPM) is an aggressive thoracic cancer that derives from the mesothelial cells of the pleura and is mainly associated with prior exposure to asbestos fibers . Even though it is a rare cancer, the global rate of MPM is increasing because of the constant use of asbestos in some countries and the difficulty in its removing from the environment, even in countries that banned its use in the 1990s . MPM has long been classified in three main histological subtypes, which are characterized by different frequencies and prognoses . Specifically, epithelioid MPM represents the most common (50-70%) and the less aggressive subtype; sarcomatoid MPM is the rarest (10-20%), most aggressive and chemo-resistant subtype; and biphasic MPM is characterized by epithelial and mesenchymal components and is the subtype whose frequency and outcome are in between the previous ones. In addition to histology, both their stromal and molecular features are increasingly recognized as important prognostic determinants and are included in the updated classification of pleural tumors published by the World Health Organization (WHO) in 2021 . Due to the long latency of tumor development--which usually takes approximately 40 years--and the poor specificity of the clinical symptoms, MPM is usually diagnosed in old individuals at an advanced stage, when malignant cells have already spread to all the pleural layers . Therefore, MPM clinical management is challenging, and the high resistance of malignant cells to treatments further worsens the patient's outcome. Overall, this results in a dismal prognosis and a-5-year survival rate of approximately 10%. Despite its poor effectiveness, the combination chemotherapy with cisplatin and pemetrexed has remained the only first-line therapy for MPM for almost two decades . The addition of bevacizumab to combination chemotherapy showed a two-month-survival improvement, but it didn't receive any approval because of the increased frequency of severe adverse events . In contrast, the combination of Tumor Treating Fields (TTFields)--which is a non-invasive approach based on the transcutaneous delivery of low-intensity alternating electric fields--with gold standard chemotherapy showed promising results in terms of safety and efficacy in a single-arm phase-II multicentric study. As a result, it was approved in 2019 by the Food and Drug Administration (FDA) as a front-line therapy for unresectable, locally advanced or metastatic MPM. Nevertheless, the lack of randomized evidence limits its entry into the clinical guidelines. Meanwhile, the success of immune checkpoint blockade (ICB)-based immunotherapy for the treatment of melanoma has fostered its evaluation for other deadly cancers, such as MPM. Despite the disappointing results of the first trials, in 2021 the publication of the Checkmate 743 trial, which was a large randomized open-label phase III study, showed that the combination of ipilimumab (anti-CTLA-4) and nivolumab (anti-PD-1) in a frontline setting is more effective than standard chemotherapy. As a result, both the FDA and the European Medicines Agency (EMA) rapidly approved the combined ICB as a new first-line treatment option for unresectable MPM. Although this undoubtedly represents a breakthrough for MPM, many patients are still refractory or relapse after a few months of therapy. Thus, MPM is still a fatal cancer that urgently needs new treatment options. The identification of reliable biomarkers that enable researchers to anticipate the diagnosis at a "pre-invasive" stage is obviously a key step towards better clinical management. Equally important are new therapeutic strategies along with predictive biomarkers to guide clinical decision making toward the best treatment for each patient, which are very active fields of research that challenge physicians and scientists. Enhancer of zeste homolog 2 (EZH2) is a well-known oncogenic driver in different malignancies, wherein it regulates gene expression in a PRC2-dependent and -independent manner . Although EZH2 alone is enzymatically inactive, biochemical and structural studies have shown that in association with EED, SUZ12 and RbAp46/48, it becomes the catalytic subunit of polycomb repressive complex 2 (PRC2), which represses gene expression by the trimethylation of histone H3 on lysine K27 (H3K27me3) . Although this epigenetic repression of genes plays a key role during tissue development and stem cell fate decision, its dysregulation can bring about the silencing of tumor suppressor genes and the promotion of carcinogenesis. Additionally, emerging studies have pointed out that EZH2 can promote the activation of key oncogenic programs through its direct interaction with transcription factors, such as NF-kB, estrogen and androgen receptors . Collectively, the overexpression or gain-of-function mutations of EZH2 have been reported in a variety of solid and hematological cancers . Accordingly, EZH2 has been recently introduced by the WHO as a diagnostic marker that enables the distinction of MPM from benign mesothelial proliferation . Because of the association between its overexpression and a worse outcome , its inhibition has also been evaluated for new therapeutic perspectives. In models of MPM overexpressing EZH2 due to BRCA-1-associated protein 1 (BAP1) loss, pharmacological EZH2 inhibition showed significant anti-tumor activity . However, treatment with tazemetostat, an EZH2 inhibitor that has recently been entered into the clinical treatment for epithelioid sarcoma , showed only a modest response rate in patients with relapsed or refractory BAP1-inactivated mutations . Therefore, there is a need to better understand the mechanisms that sensitize cancer cells to EZH2 inhibitors, along with their effects on the tumor microenvironment (TME). Indeed, EZH2-dependent epigenetic reprograming has emerged as a crucial modulator of tumor-infiltrating immune cells in different types of malignancies, but it has never been fully explored in MPM. As a result, combining EZH2 inhibitors with other treatment approaches, including immunotherapy, is currently a hot topic of research in solid tumors and might represent the next key challenge for the clinical management of MPM. Based on these premises, this manuscript reviews the current state-of-the-art of EZH2 in MPM pathogenesis, diagnosis and therapy. Specifically, we provide a comprehensive narrative synthesis of the evidence regarding the identification of EZH2 in the context of MPM, we critically describe its value as a diagnostic biomarker, and we discuss the pre-clinical and clinical studies that identify EZH2 as a new promising therapeutic target. We also highlight current gaps of knowledge and argue about the putative therapeutic perspectives of EZH2 inhibitors in combination with ICBs for MPM. 2. EZH2 in MPM The mutational landscape that has emerged over the previous years has highlighted extensive genetic variation and gene expression deregulation both between and within MPM patients . This molecular heterogeneity suggests the existence of a continuum of MPM clinical phenotypes whose understanding will remarkably improve MPM classification and prognostication. In addition to the mutated genes that characterized each tumor, most MPMs also harbor loss-of-function mutations or the genetic loss of a few tumor suppressor genes (CDKN2A/2B, BAP1, NF2, TP53, LATS2 and SETD2), which likely plays a key role in neoplastic transformation . The inactivation of such tumor driver genes is mainly due to chromosomal instability rather than point mutations. As a result of chromoplexy or chromothripsis, multiple chromosomal rearrangements and deletions are commonly observed in MPM cells . In addition, tumor suppressor genes can be silenced by epigenetic modifications. Since 2009, it has been known that the expression of up to 11% of the genes in MPM cells are repressed by histone and DNA methy24 is nowlation . With the exception of some overlaps, the majority of the genes enriched with H3K27me3 have no detectable level of DNA hypermethylation on the CpG promoters, while most of the DNA hypermethylated genes have no H3K27me3 marks. Thus, it appears that H3K27me3 and DNA hypermethylation may contribute to MPM development through the silencing of specific target genes. Two years later, Kemp C.D. et al. provided the first evidence of the aberrant expression of the polycomb group (PcG) proteins in MPM and proposed its targeting as a new potential treatment for this malignancy . They revealed that the majority of MPM cell lines and primary MPM cells express higher levels of EZH2--a core component of PRC-2--than normal mesothelial cells. More importantly, the immunohistochemical (IHC) analysis of the MPM specimens demonstrated that EZH2 overexpression was associated with aggressiveness and the advanced stage of disease, and it decreased patient survival. Albeit poorly studied in the context of pleural mesothelial cells , it is widely recognized that the balanced activity of EZH2 methyltransferase with KDM6A (UTX) and KDM6B (JMJD3) demethylase controls the physiological levels of H3K27me3, which drives proper cell differentiation during development. Accordingly, an accumulating amount of evidence has indicated that the dysregulated activity of these proteins is linked with cancer cell features (e.g., proliferation, survival, stemness, migration, epithelial-mesenchymal transition) in different tumor types . However, the interplay between EZH2 methyltransferase and KDM6A (UTX) and KDM6B (JMJD3) demethylase has yet to be explored in MPM. The analysis of surgical samples from MPM patients showed that both KDM6A and KDM6B transcript levels were increased in malignant tumors . However, their pharmacological inhibition resulted in stronger anti-proliferative effects in normal mesothelial compared to MPM-derived cell lines, reducing the interest in KDM proteins as therapeutic targets . In contrast, the upregulation of EZH2 observed in tumor tissue biopsies were retained in the MPM-derived cell lines, suggesting that EZH2 expression is under the control of tumor-specific factors. Specifically, the expression of a number of PcG genes, including EZH2, is transcriptionally regulated by E2F1. Nevertheless, this control can be dysregulated in MPM due to frequent CDKN2A deletions or epigenetic modulation . Loss of BAP-1, which is another common oncogenic driver in MPM, was also found to be associated with EZH2 upregulation in human MPM cell lines . Additionally, epigenetic regulators such as microRNA (miR)-101 and miR-26a, which are down-regulated in primary MPM, negatively affect the expression of EZH2 . Recently, we have demonstrated that the silencing or inhibition of SIRT1 in MPM cells induces EZH2 protein acetylation and stability, as well as augmented H3K27me3 levels . Over the last years, the analysis of TCGA data has confirmed that EZH2 mRNA is highly expressed in MPM and is significantly associated with decreased survival . Along the same line, the analysis of transcriptomic datasets of MPM by bioinformatic tools, which allows for the prediction of protein-protein interaction networks (PPIs), has recently identified EZH2 as well as Hyaluronan Mediated Motility Receptor (HMMR) as "core" genes of MPM development, progression and outcome . In agreement with in silico analysis, the role of PRC2-dependent gene expression in MPM pathogenesis has been strengthened by different in vitro studies . Having corroborated the observation that a subset of genes repressed in MPM exhibits H3K27me3 without DNA hypermethylation, McLoughlin K.C. and co-workers used microarray, qRT-PCR, immunoblot and immunofluorescence techniques to examine PcG gene/protein expression in a panel of MPM cell lines and normal mesothelial cells. The results demonstrated that the overexpression of EZH2 and, to a lesser extent, EED and SUZ12 is associated with the increase of H3K27me3 in approximately 80% of primary MPMs. EZH2 or EED knock-down by shRNA decreased global H3K27me3 levels and significantly inhibited the proliferation, migration, clonogenicity and tumorigenicity of MPM cells . BAP1 loss has been found functionally linked with EZH2 overexpression. Data obtained by LaFave L.M. et al. suggested that BAP1 interacted and co-occupied the EZH2 promoter with L3MBTL2, a protein that binds E-box motifs and maintains H4K20me1. BAP1 loss led to reduced L3MBTL2 stability and increased EZH2 transcription. Therefore, the silencing or pharmacological inhibition of EZH2 has been reported to induce apoptosis in BAP1-mutant MPM cell lines and reduce their growth when subcutaneously injected in mice . Recently, we have reported that low SIRT1 sensitized MPM cells to EZH2 inhibition, which significantly reduced MPM cell proliferation in vitro by arresting cells in the G0/G1 phase and inducing a senescent phenotype . Collectively, these studies indicate that despite the existence of different mechanisms leading to EZH2 overexpression, this epigenetic regulator is a central orchestrator of MPM pathogenesis. Therefore, EZH2 might represent both a reliable diagnostic marker of malignancy and a novel target for the development of new therapeutic interventions. 3. EZH2 Is a Novel Diagnostic Biomarker for MPM Currently, MPM is primarily diagnosed with imaging procedures, followed by the immunophenotyping of paraffin-embedded sections from thoracoscopic biopsies or, in some cases, of cells recovered from pleural effusion samples . In addition to cytological/histological analyses, molecular markers are essential to differentiate MPM from either metastatic adenocarcinoma or reactive mesothelial hyperplasia (RMH) . Despite being a benign process, RMH cytologically resembles epithelioid MPM, which is the most common and diverse subtype in terms of cytological and architectural complexity . Moreover, in the attempt to advance both the diagnosis and prognosis of MPM, a growing number of researchers have focused their attention on the identification of a reliable panel of biomarkers for distinguishing mesothelial tumors at the "pre-invasive" stage from those that have already infiltrated the pleural layers. These studies will likely pave the way for earlier therapeutic interventions, which might also be more effective. According to recent International Mesothelioma Interest Group (IMIG) guidelines , the homozygous deletion of the 9p21 locus detected by fluorescence in situ hybridization (FISH) and/or BAP1 loss detected by IHC are the most accurate biomarkers for distinguishing malignant from benign mesothelial proliferations. Nevertheless, there are some concerns regarding their clinical use. Regarding FISH analysis of the 9p21 locus, it is hard to define an appropriate cutoff to differentiate homozygous from hemizygous deletions. Additionally, FISH is an expensive and time-consuming technique that cannot be performed in every facility. Interestingly, Girolami I. et al. have recently reported high concordance between 9p21 homozygous deletion by FISH and methylthioadenosine phosphorylase (MTAP) loss by IHC. Thus, the latter could represent a reliable option for detecting 9p21 deletion in a low-resource setting. MTAP might also be useful in combination with BAP1 to improve MPM diagnosis. Although the number of studies was insufficient to perform a pooled analysis, it seems that a lack of MTAP and BAP1 has a higher sensitivity than BAP1 loss only. To distinguish MPM from RMH, additional IHC markers such as desmin, epithelial membrane antigen (EMA), insulin-like growth factor mRNA binding protein 3 (IMP3), glucose transporter-1 (GLUT-1) and CD146 have also been evaluated . Yoshimura et al. reported that GLUT1 (up to 89%) and IMP3 (up to 94%) have the highest sensitivity, while Sheffield et al. found that EMA with p53 (64%) and BAP1 with 9p21 locus (100%) are the most sensitive and specific combinations, respectively. A recent systematic literature review confirmed that, unless they are used in combination, biomarkers such as GLUT1 and IMP3 have an unsatisfactory diagnostic performance . Given that different studies have reported that EZH2 is overexpressed in a remarkable number of MPM cases (44.4-57%) but not RMH cases, EZH2 has emerged as an interesting diagnostic marker . Indeed, EZH2, which is known to be upregulated in different solid cancers, is not a tissue-specific marker of malignancy. Therefore, high EZH2 expression can be exploited to distinguish MPM from benign mesothelial proliferations, but not from other lung malignancies. In contrast, there is evidence that BAP1 is a specific and useful marker for distinguishing non-mesothelial malignancies from epithelioid and biphasic but not sarcomatoid MPM in the thoracic or abdominal cavities. The latter rarely harbors BAP1 loss and is usually well-diagnosed on the bases of its histological features only. Even though enhanced EZH2 expression can be functionally associated with BAP1 loss in MPM cell lines , different studies have demonstrated that BAP1 loss is not statistically associated with EZH2 expression in human MPM biopsies , indicating that the mechanisms underlying EZH2 overexpression and BAP1 loss may be distinct. Thus, the combination of BAP1 and EZH2 detection by IHC could be a highly sensitive (90.0%) and specific (100%) approach for MPM diagnosis. Additionally, the lack of correlation among BAP1 or MTAP loss and EZH2 overexpression (p = 0.973, p = 0.284) suggests that the combination of the three different markers might further increase the accuracy of MPM diagnosis . Recently, EZH2 has been evaluated in combination with Survivin, whose expression was detected in 67.9% of MPM cases, but not in RMH cases . With the exception of some variations in terms of the prevalence of Survivin-positive MPMs across different cohorts of patients, , this study confirmed the diagnostic value of Survivin. Along the same line, the authors corroborated a highly significant direct association between BAP1 loss and Survivin expression , but also revealed an inverse association between high EZH2 expression and either BAP1 loss or Survivin expression. Therefore, the combinations of EZH2high and/or BAP1 loss with Survivin+ might be exploited to gain sensitivity in the differential diagnosis between epithelioid MPM and RMH. It is worth noting that BAP1 and EZH2 are the only markers that are localized in the nuclei of tumor cells, whereases the IHC analysis of the other markers results in a cytoplasmic staining wherein variable intensity can challenge the detection of a positive signal from the background. Therefore, the inclusion of BAP1 and EZH2 in the panel of markers for the IHC analysis of tissue biopsies could greatly improve the accuracy of MPM diagnosis. Previous systematic reviews have failed to define a reliable panel of diagnostic biomarkers for MPM. The variations in marker expression reported across the different studies may be reasonably assumed to be due to the differences in terms of sample sizes, antibodies used, staining and quantification techniques. Therefore, the standardization of IHC procedures will likely allow for the determination of the appropriate combination of markers that, together with histologic analysis and clinical evaluation, might anticipate the diagnosis of MPM. 4. EZH2 as a Promising Therapeutic Target for MPM A growing number of studies have indicated the therapeutic potential of EZH2 targeting . The first evidence dates back to 2012, when 3-deazaneplanocin A (DZNep) demonstrated a significant cytotoxic effect against MPM cells . DZNep is a S-adenosylhomocysteine hydrolase (SAH) inhibitor that indirectly inhibits EZH2 by interfering with S-adenosyl-methionine (SAM) and SAH metabolism. However, H3K27 demethylation observed upon DZNep treatment is due to the proteolytic degradation of EZH2 and other PRC2 components, rather than specific EZH2 catalytic inhibition . In vitro, DZNep triggers the expression of several tumor suppressor genes, which inhibits MPM cell proliferation and induces cell senescence but not apoptosis . These data are in accordance with p21cip upregulation and the delay of the G2/M transition, which have been respectively observed in melanoma and breast cancer cells upon EZH2 knockdown . Additionally, the effect of DZNep was evaluated on MPM xenografts. The results demonstrated a significant reduction of tumor size after each cycle of treatment and an approximately 50% decrease in tumor mass at the end of the treatment course, along with no signs of systemic toxicity. Therefore, the authors claimed that DZNep recapitulated, in vitro and in vivo, the effects of EZH2 or EED depletion in MPM cells. Successively, LaFave L.M. et al. proved that human BAP1-mutant MPM cell lines were sensitive to the selective EZH2 inhibitor EPZ011989. Accordingly, EPZ011989 significantly reduced the growth of sub-cutaneous transplanted BAP1-mutant MPM cells and abrogated pulmonary metastasis when mice were injected with a BAP1-mutant MPM cell line with metastatic potential. Because the wild-type tumors were less responsive to EZH2 inhibition, they concluded that BAP1 mutations, which typically result in increased EZH2 expression, render MPM cells addicted to PRC-2. Despite the strong association between BAP1 mutations and repression of PRC-2 targets , it seems that BAP1 mutant MPMs harbor different clinical phenotypes, since different studies have reported an overexpression of EZH2 in BAP1 wild-type MPM biopsies . Recently, we have demonstrated that in low SIRT1 conditions, EZH2 inhibition significantly reduced the proliferation of BAP1 wild-type MPM cells . Interestingly, we have observed that EZH2 inhibition induced cell senescence by promoting CDKN2A/p16ink4a expression, whereas CDKN2A null cells underwent apoptosis upon treatment with the EZH2 inhibitor EPZ6438 . These findings indicate that patients carrying homozygous deletion or loss-of-function mutations of CDKN2A should be more responsive to EZH2 inhibition. Therefore, in a translational perspective, studies are warranted to evaluate CDKN2A status as a marker for patients' stratification and/or potentiation of EZH2 inhibition efficacy. A high-throughput screening (HTS) campaign followed by hit triaging led to the discovery of the EPZ005687 compound by the company Epizyme. This EZH2 inhibitor has a greater than 500-fold selectivity against 15 other protein methyltransferases and a 50-fold selectivity against the closely related enzyme EZH1 . The EPZ005687 has a similar affinity for wild-type and Y641 mutant EZH2, but a greater affinity for the A677G mutant. In spite of the remarkable reduction of H3K27me3 in both EZH2 wild-type and mutant lymphoma cell lines, similar to other EZH2 inhibitors, EPZ005687 significantly inhibited the proliferation of mutant EZH2 cells only. A further-improved version of EPZ005687 is EPZ-6438 (tazemetostat), which is a potent and selective SAM competitive small molecule that retains the cellular activity and selectivity of EPZ005687 but gains better oral bioavailability and pharmacokinetic properties . In addition to hematological malignancy, the inhibition of EZH2 can be beneficial for the treatment of solid cancers. Firstly, EPZ-6438 has demonstrated significant anti-tumor activity against malignant rhabdoid tumors (MRTs), provided that SMARCB1 is deleted. Indeed, EZH2 inhibition by EPZ-6438 induced apoptosis in SMARCB1-mutant MRT cells and dose-dependent tumor regression in xenograft-bearing mice . Subsequently, accumulating preclinical studies have substantiated the therapeutic potential of EPZ-6438 for a variety of solid tumors , leading to the initiation of clinical trials worldwide. In 2020, tazemetostat (TasverikTM) was approved by the FDA for the treatment of adults with locally advanced or metastatic epithelioid sarcoma not eligible for complete resection . Along the same line, a phase-1 study recently conducted in Japan has reported that tazemetostat has a favorable safety profile and promising anti-tumor activity in patients with relapsed, refractory or advanced B-cell non-Hodgkin lymphoma . However, some B-cell malignancies are resistant to EZH2 inhibitors , and in many solid cancers, despite the overexpression of EZH2, its inhibition alone doesn't achieve a sufficient level of efficacy . Consistent with that, the results of a recent multicenter single-arm open-label phase-II study with tazemetostat in BAP1-inactivated relapsed or refractory MPM patients provide the first evidence of safety along with a moderate anti-tumor activity . The study enrolled patients with a more indolent disease after initial systemic therapy and included a substantial proportion of patients who had a surgical resection that did not reflect the real average of patients usually eligible for surgery. BAP1 mutation was determined by DNA sequencing, while loss of protein expression was done by IHC. The primary end-point of the study was the disease control at 12 weeks. Indeed, meta-analyses of trials conducted in MPM patients indicates that this parameter is a reliable positive predictor of survival. The end-point was reached in about a half of the patients, and the drug showed a favorable safety and tolerability profile. Two patients had a partial response, with a 30-week median duration of response. Noteworthy, a preliminary exploration of the TME composition before and after treatment with tazemetostat highlighted a significant reduction of intra-tumoral and stromal B-cells. That effect on immune cells warrants future studies to gather its role on clinical response. Altogether, these findings indicate that tazemetostat is a promising therapeutic option, whose efficacy might likely be improved by a better definition of predictive biomarkers for the stratification of MPM patients, as well as by novel combination strategies of EZH2 inhibitors with therapies such as chemo-, targeted therapy. Indeed, many preclinical studies have demonstrated the efficacy of EZH2 inhibition in combination with cisplatin in different tumor types, such as lung, ovarian, and breast cancers . EZH2 inhibition can rescue cisplatin resistance and mitigate the adverse effects . Given that cisplatin-based chemotherapy is the standard-of-care for MPM, future studies are warranted to evaluate the putative beneficial effects of the combination of EZH2 inhibitor with cisplatin. 5. The MPM Immune Microenvironment In addition to cancer cells, the TME, including immune and non-immune cells, the extracellular matrix and the soluble mediators released by the different cells, plays a key role in MPM development, growth, progression and response to therapy . Here, we focus on immune cells only , among which macrophages emerge as key orchestrators of both early tumor-promoting inflammation in response to asbestos fibers and immunosuppression at the advanced stage of MPM. Alveolar macrophages, which efficiently eliminate dust particles and environmental pollutants , struggle to clear fibers longer than 5 mm, which consequently remain in the lungs--triggering the neoplastic transformation of mesothelial cells. Although the underlying mechanisms have not yet been fully understood, it is widely recognized that ''frustrated phagocytosis'' promotes a chronic inflammatory microenvironment that supports the carcinogenesis, survival and proliferation of neoplastic cells through the production of reactive oxygen and nitrogen species (ROS and NOS), as well as cytokines, such as IL-1b and TNFa . Additionally, High Mobility Group Box1 Protein (HMGB1), a damage-associated molecular pattern released by both mesothelial cells and macrophages, plays a key role in tumor development and progression by enhancing both macrophage-driven inflammation and mesothelial/neoplastic cell survival, proliferation, autophagy and epithelial-mesenchymal transition (EMT) . Accordingly, HMGB1 dramatically increased in the blood of asbestos-exposed individuals, and its high levels in MPM patients are associated with a worse outcome . Tumor-associated macrophages (TAMs), which are the most abundant population of immune cells in human MPM , largely stems from monocytes recruited by chemotactic factors like CCL2, which is produced abundantly by mesothelial cells exposed to asbestos . As a result, CCL2 levels increased significantly both in the pleural effusion (PE) and in the blood of MPM patients, in particular at the advanced stage, supporting the central role of macrophages across all stages of MPM development . Accordingly, the number of TAMs defined by the pan-macrophage marker CD68 was associated with worse outcomes in non-epithelioid MPM . Similar to other tumor types, TAMs upregulate M2 markers like CD163 and CD206, indicating a shift of polarized activation toward the alternative (M2) immunosuppressive program. In agreement, a positive correlation between stromal CD68+ macrophages and immunosuppressive Tregs was observed in MPM specimens . Additionally, pleural effusion is enriched in molecules, such as macrophage colony stimulating factor (M-CSF) , transforming growth factor b (TGF-b) and prostaglandin E2 (PGE2) , which are released by tumor cells and drive immunosuppressive macrophage differentiation in vitro. In line with human evidence, the accumulation of immunosuppressive and tumor-promoting TAMs was also confirmed in different pre-clinical models of MPM , where their depletion and/or M1-reprograming rescued anti-tumor immunity , in particular in combination with anti-PD1/PD-L1 blockades . Although these studies overall support the therapeutic value of the approaches that target macrophages, the increasing evidence of the inter-tumor heterogeneity of human MPM points out the need for a better understanding of TME and its cross-talk with cancer cells. Even though they account for less than 10% of immune infiltrate, both polymorphonuclear (PMN) and monocytic (M-) myeloid-derived suppressor cells (MDSCs) exert different tumor-promoting activities that negatively affect MPM outcome . Both subsets exert important immunosuppressive activities, as demonstrated by the inhibition of proliferation and cytotoxic activity of autologous human T lymphocytes . Further supporting the therapeutic potential of targeting MDSCs, the neutralization of GM-CSF in a preclinical model of MPM inhibits the accumulation of tumor-infiltrating PMN-MDSC, boosting anti-tumor immunity . Dendritic cells (DC), which play a key role in inducing an antigen-specific immune response, are not only reduced in number but also in migratory and antigen presentation capability. Although these cells maintain expression of IL-12, they also tend to produce higher amounts of anti-inflammatory and pro-angiogenic factors such as IL-10 and vascular endothelial growth factor (VEGF) . So far, cytotoxic immune cell populations like NK and NKT cells have been poorly studied in human MPM. Different evidence indicates that, despite playing a relevant role in anti-tumor immunity, NK frequency in MPM is not associated with a better outcome . A reasonable explanation is that the immunosuppressive microenvironment of MPM hampers their effector functions . According to this hypothesis, in the PE of MPM patients, NK cells express high levels of the checkpoint inhibitors T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) and lymphocyte activation gene-3 (LAG-3) . Additionally, a reduced expression of activating receptor-like NKp46 and an enrichment of a CD56Bright NK subset have been reported in the blood of MPM patients . Interestingly, anti-CTLA-4-based immunotherapy seems to enhance the cytotoxic activity of NK cells since an increase of CD56Dim/CD56Bright NK ratio has been observed in the blood of tremelimumab-treated patients . NKT cells, whose activation by alpha-galactosylceramide in combination with cisplatin has demonstrated a relevant anti-tumoral activity in mouse models of MPM , represent an additional population of cytotoxic immune cells that warrants more study in MPM patients. Beyond the impact of each immune cell population, understanding the cross-talk among the stromal, immune and cancer cells is a key challenge for improving patients' stratification and clinical management. Indeed, different studies based on the IHC analysis of immune infiltrate have observed that the combination of different immune cells has a better prognostic value than the frequency of single immune cell subsets. For example, although a high frequency of either T (CD3+, CD8+, or CD4+ cells) or B (CD20+ cells) lymphocytes has been reported as favorable prognostic markers in epithelioid MPM, CD20+B cellshigh CD163+ TAMlow and CD8+ T cellslow CD163+ TAMhigh combinations showed a superior accuracy in predicting better and worse outcomes, respectively . Additionally, in a cohort of patients with non-epithelioid MPM, it has been observed that despite the presence of a high number of anti-tumoral CD8+ T lymphocytes, when a significant level of CD68+ macrophages and PD-L1+ tumor cells are present as well, the response to chemotherapy and the outcome are poor . In contrast, a higher number of B lymphocytes, along with the presence of tertiary lymphoid structures (TLS) consisting of B and T lymphocytes, have been associated with a response to chemotherapy and a longer survival for patients with epithelioid MPM . These studies highlight the importance of TME composition not only as prognostic marker, but also as a predictor of response to therapy. Accordingly, a recent study performed on a small cohort of patients showed that a high number of CD8+ T cells is an independent factor associated with better survival in epithelioid MPMs treated with hypo-fractionated radiation therapy . Besides radiotherapy, the immune contexture obviously holds great promise as a predictor of response to immunotherapy. To overcome the limits of IHC, the development of innovative multiplex immunophenotyping techniques has marked a milestone for a more comprehensive characterization of the TME. Nevertheless, only Lee H. S. and colleagues have hitherto analyzed the MPM immune infiltrate by mass-cytometry . As a result, MPM patients were stratified in two groups characterized by a distinct immunogenic immune signature, which was associated with favorable outcomes and a response to checkpoint blockade . Although the multiplex immunophenotyping technique allows for the analysis of intratumor heterogeneity at the single-cell resolution level, transcriptional profiling is an easier approach that has become widespread over the last years. As a result, an underestimated level of cancer cell heterogeneity beyond histological subtypes has emerged. Additionally, due to the consistent increase of publicly available datasets, different algorithms have been generated to unravel the MPM microenvironment and determine the immune signatures to predict outcomes and response to treatments. For example, the application of the ESTIMATE algorithm has indicated a prognostic signature consisting of 14 stromal/immune-related genes, which could also be useful to predict response to ICB . Recently, using non-negative matrix factorization (NMF) and nearest template prediction (NPT) algorithms, Yang and co-workers developed an in silico classification system that stratifies MPM in different immune subtypes that are associated with different prognoses . In addition, because of the high lymphocyte infiltration, TCR and BCR diversity, and IFNg signature, the "immune activated" subtype has a favorable response to ICB, while the "immune suppressed" subtype, which is characterized by a huge number of immunosuppressive Treg and myeloid cells (TAM, MDSC) along with a TGF-b signature, is resistant to ICB, but it could benefit from drug targeting macrophages such as CSF1/CSF1R antibody. Therefore, improving our understanding of the TME contexture prior to therapy could be crucial to guide clinical decision making, whereases gathering the effects of treatments on TME would provide a more comprehensive knowledge of their efficacy and might open new strategies to enhance their therapeutic effects. 6. Effects of EZH2 Targeting on MPM Immune Infiltrate Are Still Largely Unknown It has long been known that, besides the cancer cell-autonomous effect, the anti-cancer activity of drugs targeting epigenetic modulators is due to the promotion of anti-tumor immunity . Although poorly studied in MPM, EZH2-dependent epigenetic reprograming can modulate tumor cell immunogenicity and TME composition, and it can directly regulate immune cell differentiation and functional activation . Specifically, in different types of both hematological (e.g., diffuse large B-cell lymphoma) and solid cancers (e.g., neuroblastoma, melanoma, breast, prostate and lung cancer), gain-of-function mutations or the overexpression of EZH2 increases H3K27me3, which represses genes encoding tumor-specific antigens and MHC molecules . Therefore, EZH2 inhibitors can enhance tumor cell immunogenicity by reshaping the epigenetic landscape of cancer cells and favoring the expression of genes associated with both the presentation of new antigens and the recruitment of anti-tumor immune cells. Consistently, in preclinical models of ovarian cancer and melanoma, epigenetic reprogramming due to EZH2 knock down or pharmacological inhibition enhanced the expression of Th1-recruiting chemokines (e.g., CXCL9, CXCL10), increased tumor-infiltrated CD8+ T cells, and improved the efficacy of ICB-based immunotherapy . Additionally, in a poorly immunogenic melanoma model, the inhibition of EZH2 triggered the expression of STING and consequently sensitized cancer cells to STING agonists. As a result, a combination of a EZH2 inhibitor and a STING agonist synergistically reduced tumor growth in association with an increased CD8+ T-cell infiltration . Although the mechanism is different, the activation of STING upon treatment with EZH2 inhibitors has been also reported in prostate cancer. Indeed, in prostate cancer cells, EZH2 inhibitors can rescue the expression of endogenous retrovirus (LTR/ERV), which results in a "viral mimicry" state. Specifically, dsRNA molecules activate STING receptors, which triggers the expression of interferon-stimulated genes (ISGs). This brings about an increase of antigen presentation, cytotoxic CD8+ T cell recruitment and anti-PD1 responsiveness . In line with these studies, using a MPM multicellular spheroid model (MCS), we have found that treatment with the EZH2 inhibitor tazemetostat lead to the upregulation of chemokines specific for the recruitment of cytotoxic immune cells such as CXCL9 and CXCL10 . However, we have also found an increased expression of different monocyte chemoattractants (e.g., CCL2, M-CSF, CCL5, CXCL12, VEGF) in association with a significantly higher recruitment of tumor-promoting monocytes in the MCS . This was the first study that had evaluated the effect of EZH2 on MPM TME composition, specifically on human monocytes and their impact on cancer cell responsiveness to tazemetostat. Subsequently, a functional association between EZH2 and TAM infiltration has been also reported in other types of tumors, such as breast and colorectal cancer (CRC) . Recently, the effect of EZH2 on the composition of human MPM immune infiltrate has been explored using bioinformatic analysis on TCGA datasets. Interestingly, the results showed that high EZH2 expression, which is significantly associated with a worse outcome, negatively correlated with the number of tumor-infiltrating mast, NK and Th17 cells . Overall, these studies provide the proof-of-concept that EZH2 modulates the composition of both innate and adaptive immune infiltrate in MPM. Besides recruitment, EZH2 affects anti-tumor immunity by modulating the differentiation and functional activation of the immune cells . Concerning T cells, EZH2 promotes the lineage-specification, identity, maintenance and survival of differentiated antigen-specific CD4+ T helper cells, whereas effector CD8+ T cell differentiation is restrained by EZH2, which favors the formation of precursor and mature memory CD8+ T cells . Additionally, Treg differentiation and suppressive activity require the EZH2-dependent deposition of H3K27me3 marks . Indeed, mice carrying Treg-specific Ezh2 deficiency showed a reduced growth of different types of tumors (e.g., CRC, melanoma, prostate cancer) in association with the reprograming of tumor-infiltrating Tregs in anti-tumor effector cells (e.g., IL-2, IFNg, and TNF) . Regarding innate lymphoid cells, EZH2 inhibits invariant natural killer T (iNKT) cell differentiation and function, as well as the maturation, activation, survival and cytotoxicity of NK cells . Accordingly, in hepatic cancer, the inhibition of EZH2 in tumor cells enhanced NK recruitment via CXCL10 , and it enhanced their activation through the expression of NKG2D ligands . EZH2 also modulates the differentiation of MDSC. In murine models of either CRC or Lewis lung cancer (LLC), blocking EZH2 with GSK126 in immunocompetent mice impaired anti-tumor immunity by boosting systemic MDSCs expansion and accumulation in TME. Depleting MDSCs by anti-GR1 neutralizing antibodies or low doses of gemcitabine/5-Fluorouracil rescued GSK126 efficacy by recovering the anti-tumor effector T-cell activity . Divergent effects of EZH2 on TAM functional activation have been reported in different settings. In a murine model of MPM, it has been observed that the treatment of murine RAW264.7 macrophages with a EZH2 inhibitor led to the upregulation of the phagocytosis inhibitory checkpoint PD-1 and, consequently, impaired their cytotoxic activity toward the MPM cells in vitro and in vivo . Accordingly, by using an MCS model consisting of human MPM cells and monocytes, we have demonstrated that tazemetostat enhances both the recruitment and M2-polarized activation of monocytes, blocking the anti-proliferative effects of EZH2 inhibition in cancer cells . Therefore, combining EZH2 inhibition with TAM-targeted therapy, such as anti-CSF1R , might synergistically improve the anti-tumoral efficacy. Along the same line, the treatment of breast cancer cells with EZH2 inhibitors promotes recruitment and favors M2 polarized macrophage activation by inducing CCL2 upregulation . In contrast, EZH2 depletion caused an miR-124-3p-dependent inhibition of CCL2 expression in the tumor cells, leading to the inhibition of M2 polarized activation . This highlighted an additional level of complexity in EZH2 activity, whose non-enzymatic modulatory functions are still poorly characterized. Moreover, cancer cell intrinsic and TME signals may account for the distinct effects of EZH2 inhibitor in different tumor types. Indeed, in a murine colorectal cancer (CRC) model, tazemetostat induced the accumulation of anti-tumor macrophages . Accordingly, in glioblastoma multiforme, EZH2 inhibition by DZNep favored macrophage M1 polarization, as demonstrated by the upregulation of pro-inflammatory cytokines and the downregulation of anti-inflammatory ones, and it enhanced phagocytic capability . These divergent results suggest that cancer cell intrinsic and TME signals may account for the distinct effects of EZH2 inhibitor in different tumor types. 7. Conclusions After decades of failed trials, the approval of immunotherapy based on the combination of ipilimumab and nivolumab has marked a milestone for MPM, particularly the sarcomatoid subtype, which is more aggressive and resistant to chemotherapy. However, MPM remains a deadly cancer with an unacceptably poor survival rate after diagnosis. Besides histology, the increasing advancements in MPM classification by molecular markers represent a key step towards better clinical management. Indeed, if we were able to bring the diagnosis toward the "pre-invasive stage" and to improve prediction of outcome, we would increase the chances of effective treatment regimens. In this context, EZH2 has emerged as a valuable diagnostic marker with a prognostic potential. Similar to many other solid cancers, its overexpression in MPM is recognized as an oncogenic driver. Consequently, inhibitors of EZH2 such as tazemetostat, which has recently entered into clinical use for epithelioid sarcoma, has attracted a lot of interest and has recently demonstrated some promising results of efficacy in preliminary clinical trials. Along with a better understanding of reliable biomarkers to identify the patients who most likely benefit from EZH2 inhibition, combinations of EZH2 inhibitors with different therapeutic modalities holds promise for enhancing efficacy. Being an epigenetic modulator, EZH2 has a profound effect not only on cancer cells, but also on TME. Given that EZH2 inhibitors can modulate both anti-tumor and pro-tumor immune cell populations, a better understanding of the effect of EZH2 inhibitors on the MPM immune infiltrate will likely help physicians determine the most effective combination approaches. Notably, the growing number of pre-clinical studies looking at different models of solid cancers indicate that EZH2 inhibitor synergizes with ICB-based immunotherapy thanks to the increased expression of PD-L1, immunogenic antigen and chemokine-recruiting cytotoxic T cells . On the other hand, it is well-recognized that the efficacy of ICB-based immunotherapy could benefit by combination therapeutic strategies. So far, clinical trials conducted with MPM patients have evaluated ICBs with chemotherapy, targeted therapy like bevacizumab, and stereotactic body radiation therapy . Epigenetic modulators, such as EZH2 inhibitors, which have been demonstrated to have a favorable safety profile along with a promising immunogenic potential, could represent a new potential therapeutic approach that warrants evaluation in combination with immunotherapy. Acknowledgments Servier provided Servier Medical Art, a free accessible website that provides pictures under a Creative Commons Attribution 3.0 unported license. Author Contributions Conceptualization, C.P., L.M.; writing--original draft preparation, M.O.A.K., and G.P.; figure design, C.P., L.M. and M.O.A.K.; writing--review and editing, C.P. and L.M.; supervision, C.P. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Effects of EZH2 inhibition in MPM. In the upper brace are reported miRNAs and proteins that have been described to modulate EZH2 expression in MPM cells. Below, the main effects of EZH2 inhibitors reported by in vitro and in vivo studies with MPM cells/tumors stratified by BAP1 or CDKN2A expression. (EZH2, enhancer of zeste homolog 2; EED, embryonic ectoderm development; PRC2, Polycomb re-pressor 2; SUZ12, suppressor of zeste 12 homolog; H3K27Me3, Histone 3 lysine 27 trimethylate; BAP1, BRCA1 associated protein 1; L3MBTL2, lethal 3 malignant brain tumor-like protein 2; SIRT1, sirtuin1; FHIT, Fragile Histidine Triad Diadenosine Triphosphatase; HIC1, HIC ZBTB Transcriptional Repressor 1, CDKN1A, cyclin dependent kinase inhibitor 1A; RASSF1A, Ras as-sociation domain family 1 isoform A; MCSF, macrophage colony stimulating factor; VEGF, vascular endothelial growth factor). The figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license (accessed on 28 January 2023) . Figure 2 Immune cell infiltrate impacts MPM outcome. On the upper left corner, the main immune cell populations associated with better outcomes are depicted, whereas on the lower right corner, the pro-tumoral and immunosuppressive immune cell populations are shown. The immune cells with a putative albeit not yet proven anti-tumor activity are indicated in the lower left corner. (Solid red arrows: anti-tumor activity, dashed red arrows: putative anti-tumor activity, black arrows: pro-tumor activity, blue arrows and inhibition arrows: putative therapeutic approaches. TLS, tertiary lymphoid structure; TAM, tumor associated macrophage; PMN-MDSC, -derived suppressor cells; M-MDSC monocytic-myeloid-derived suppressor cells; NK, Natural killer cells; NKT, Natural killer T cells; TAM, Tumor associated macrophages; DC, dendritic cells; Treg, T regulatory cells; IL-1b, Interleukin 1 Beta; IL 10, Interleukin 10; HMGB1, high mobility group box 1; PGE2, Prostaglandin 2; M-CSF, Macrophage colony stimulating factor; TNFa, Tumor necrosis factor alpha; TGF b, transforming growth factor beta; VEGF, vascular endothelial growth factor.) The figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license (accessed on 28 January 2023). Figure 3 EZH2 modulates anti-tumor immunity. EZH2 inhibition leads to the epigenetic reprograming of cancer cells, which upregulates transcriptional programs associated with increased tumor cell immunogenicity and recruitment of cytotoxic immune effector cells, but also monocytes and immunosuppressive molecules such as PD-L1. This suggests that combinatory strategies targeting the tumor-infiltrating immune cells, such as anti-PD-1/PD-L1 antibodies, might synergize with EZH2. (STING, stimulator of interferon genes; CXCL9, CXC motif ligand chemokine ligand 9; CXCL10, CXC motif ligand chemokine ligand 10; MHC 1, Major histocompatibility complex 1; LTR, Long termina repeat; EVR, endogenous retrovirus; PD-L1, programmed death-ligand 1; PD-1, programmed cell death protein 1.) The figure was partly generated using Servier Medical Art, provided by Servier, licensed under a Creative Commons Attribution 3.0 unported license (accessed on 28 January 2023). 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PMC10000484 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050877 diagnostics-13-00877 Review The Female Reproductive Tract Microbiome and Cancerogenesis: A Review Story of Bacteria, Hormones, and Disease Trifanescu Oana Gabriela 12+ Trifanescu Raluca Alexandra 34+ Mitrica Radu Iulian 12* Bran Diana Maria 2+ Serbanescu Georgia Luiza 12* Valcauan Laurentiu 2 Marinescu Serban Andrei 5+ Gales Laurentia Nicoleta 16 Tanase Bogdan Cosmin 7 Anghel Rodica Maricela 12 Giacometti Cinzia Academic Editor 1 Department of Oncology, ,,Carol Davila" University of Medicine and Pharmacy, 022328 Bucharest, Romania 2 2nd Department of Radiotherapy, ,,Prof. Dr. Al. Trestioreanu" Institute of Oncology, 022328 Bucharest, Romania 3 Department of Endocrinology, "Carol Davila" University of Medicine and Pharmacy, 011863 Bucharest, Romania 4 "C.I. Parhon" Institute of Endocrinology, 011863 Bucharest, Romania 5 Department of Surgery, ,,Prof. Dr. Al. Trestioreanu" Institute of Oncology, 022328 Bucharest, Romania 6 2nd Department of Oncology, ,,Prof. Dr. Al. Trestioreanu" Institute of Oncology, 022328 Bucharest, Romania 7 Department of Thoracic Surgery, "Prof. Dr. Al. Trestioreanu" Institute of Oncology, 022328 Bucharest, Romania * Correspondence: [email protected] (R.I.M.); [email protected] (G.L.S.) + These authors contributed equally to this work. 24 2 2023 3 2023 13 5 87715 12 2022 07 2 2023 18 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The microbiota is the complex community of microorganisms that populate a particular environment in the human body, whereas the microbiome is defined by the entire habitat--microorganisms and their environment. The most abundant and, therefore, the most studied microbiome is that of the gastrointestinal tract. However, the microbiome of the female reproductive tract is an interesting research avenue, and this article explores its role in disease development. The vagina is the reproductive organ that hosts the largest number of bacteria, with a healthy profile represented mainly by Lactobacillus spp. On the other hand, the female upper reproductive tract (uterus, Fallopian tubes, ovaries) contains only a very small number of bacteria. Previously considered sterile, recent studies have shown the presence of a small microbiota here, but there are still debates on whether this is a physiologic or pathologic occurrence. Of particular note is that estrogen levels significantly influence the composition of the microbiota of the female reproductive tract. More and more studies show a link between the microbiome of the female reproductive tract and the development of gynecological cancers. This article reviews some of these findings. microbiome carcinogenesis female reproductive tract immunotherapy University of Medicine and Pharmacy "Carol Davila"Publication of this paper was supported by the University of Medicine and Pharmacy "Carol Davila", through the institutional program "Publish not Perish". pmc1. Introduction 1.1. The Microbiome of the Female Reproductive Tract The healthy vagina harbors a microbiota characterized by a low diversity of species, represented mainly by Lactobacillus spp. (Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, Lactobacillus jensenii, Lactobacillus vaginalis) . This starkly contrasts with the high diversity of species demonstrated by the healthy colon . The vagina contains species that process glycogen and its breakdown products to produce lactic acid, thus leading to an acidic pH of less than 4.5 . This is important because it inactivates pathogens and prevents the ascent of pathogenic bacteria to the upper reproductive tract. Lactobacilli also secrete antimicrobial products and prevent the adhesion of pathogens . On the pathological side, endometriosis, gynecological cancers and fertility problems may all be related to uterine microbiota . Vaginal dysbiosis is characterized by a high diversity of bacterial species and a high pH. A diseased vaginal environment contains a mixture of anaerobic bacteria such as Sneathia spp., Atopobium spp., Porphyromonas spp., Gardnerella vaginalis etc. It can sometimes contain bacteria such as Streptococcus spp., Staphylococcus spp. and Enterobacteriaceae. In vaginal dysbiosis, the Lactobacillus spp. are low in number leading to an increased risk of bacterial vaginosis. The specific types of lactobacilli also matter. For instance, a vagina that contains mainly Lactobacillus iners frequently transitions to become anaerobe-dominant . However, not all Lactobacillus species have the same effect; for example, this transition fails to develop in a vagina with predominant Lactobacillus crispatus. This might be related to the type of lactic acid produced by each bacterium. Lactobacillus iners only synthesizes the L-isoform of lactic acid, which correlates with higher levels of metalloproteinases in vaginal secretions and lesser epithelial integrity of the vaginal wall . This is of practical importance in deciding the appropriate Lactobacillus spp. to use as vaginal probiotics. The upper female reproductive tract (uterus, Fallopian tubes and ovaries) was considered sterile for a long time. Recent molecular studies showed that it might harbor its own microbiota, but it is unclear if the samples used in studies were not contaminated during collection . The healthy upper reproductive tract would contain only a very small biomass of bacteria whose composition and implication for the woman's and baby's health is under investigation. This biomass's exact composition and diversity are still scrutinized, but it would probably contain a smaller percentage of lactobacilli than the vagina. In contrast, the diseased and pathologic upper reproductive tract often contains a large biomass. Among the bacteria that colonize the upper genital tract, some can be particularly aggressive, leading to infertility, such as Chlamydia, Mycoplasma, Acinetobacter, and Brucella. On the other hand, certain bacteria, such as Atopobium and Porphyromonas, have been shown to correlate with endometrial hyperplasia and endometrial cancer . These bacteria usually colonize the upper reproductive tract by ascending from the vagina, but there may also be direct hematogenous seeding . In addition to the female reproductive tract there are two other important female microbiomes, and they all influence each other. The other two microbiomes are that of the urethra and bladder, and that of the anus and rectum. The composition of each organ's microbiota is influenced by the direct transfer of microorganisms from the other organs. Both the urethra and rectum contain Lactobacillus spp. . 1.2. Estrogens and the Estrobolome In addition to the reproductive tract flora, another major component that influences the reproductive tract environment is represented by the female hormones, particularly estrogens. This part of the article explores the link between estrogens and the microbiome. Estrogens are conjugated in the liver by sulfotransferase and uridine diphosphate--glucuronosyltransferase enzymes and then excreted into the gut through the bile. In the gut, some conjugated estrogens are deconjugated by beta-glucuronidase and beta-glucosidase and then reabsorbed through the intestinal epithelium back into the bloodstream . Interestingly, these enzymes can be produced by some gut bacteria. Thus, the gut microbiota's composition directly impacts circulating estrogen levels . The estrobolome is nowadays defined as the aggregate of all enteric bacterial genes whose products are capable of metabolizing estrogens . The activity of different enzymes, such as b-glucuronidase, is encoded mainly by two genes. First is Gus, found in Firmicutes , and second is BG, found in Bacteroidetes . b-glucuronidase activity is also influenced by diet . A high-fat diet may increase bile acid secretion, promoting Proteobacteria growth and reducing Bacteroidetes and Firmicutes . Increases in b-glucuronidase-producing Proteobacteria increase intestinal deconjugation of estrogens and estrogens levels in circulation. This mechanism is intensified in obese patients, mainly due to peripheral aromatization of testosterone and androstenedione to estradiol and estrone . Since estrogen levels are associated with various types of cancers, such as endometrial or breast cancer, we can hypothesize that the estrobolome also impacts the carcinogenesis of these types of cancers. Moreover, the composition of the vaginal microbiome is deeply impacted by estrogen levels. Before puberty and after menopause, the vaginal microbiome consists primarily of anaerobes, whereas for healthy females of reproductive age, the vaginal microbiome consists mainly of Lactobacillus spp. . Indeed, estrogens stimulate the production and secretion of glycogen by the vaginal epithelium, promoting the growth of lactobacilli. Lactobacilli then use glycogen as a food source and degrade it through fermentation. Large amounts of the lactic acid result as a final product of this process . Therefore, we can say that the vagina's acidic environment is a direct consequence of the estrogen circulating levels. As seen above, estrogen levels are influenced, among others, by the gut microbiome. 2. The Microbiome and Cancer Development Many factors promote a healthy flora versus dysbiosis, usually promoting functioning cells versus cancer. In a considerable measure, these factors are the same. In other words, the factors associated with an unhealthy gut or vaginal flora are the ones that are also associated with cancer. Some of the factors associated with dysbiosis and cancer are low socioeconomic status, ethnicity, poor access to medical care, a high prevalence of sexually transmitted diseases, smoking, alcohol consumption, obesity, reduced physical activity, metabolic syndrome, high levels of stress, aging, hormonal imbalances, genetic and epigenetic factors, impaired immunity, the human papillomavirus . Smoking, douching, and obesity were all linked to bacterial vaginosis . Changes in the microbiome also induce complex changes in human cells . From a biological perspective, the normal cervicovaginal microbiome is composed mainly of Lactobacillus spp., thus exhibiting low bacterial diversity and protecting against carcinogenesis through various mechanisms . The lactobacilli secrete lactic acid, and the low vaginal pH promotes healthy local homeostasis. The lactobacilli also secrete cytokines, antimicrobial peptides, and other metabolites that protect the local epithelium. They promote a healthy level of physiological inflammation that stimulates the immune system to fight against pathogens. On the other hand, the dysbiotic cervicovaginal microbiome exhibits a high diversity of microorganisms, primarily obligate and strict anaerobes, that lead to a high vaginal pH. The bacteria promote the disruption of the epithelial barrier and secrete various metabolites and enzymes such as sialidase, proinflammatory cytokines and chemokines, reactive oxygen species, and other carcinogenic metabolites that lead to chronic inflammation and a dysregulated local metabolism. Further down the line, they also lead to genotoxicity and genomic instability, as well as altered proliferation and altered apoptosis. The dysbiotic environment also promotes angiogenesis. The chronic inflammation activates immune cells that secrete even more proinflammatory cytokines and chemokines such as Interleukin (IL)-6, IL-8 or Tumor necrosis factor (TNF), resulting in even more reactive oxygen species that further promote carcinogenic mechanisms. Hence, there are many different mechanisms through which the microbiota can impact carcinogenesis . 2.1. The Microbiome and Endometrial Cancer Whereas the most common gynecological cancer in developing countries is cervical cancer, because of high rates of Human Papilloma Virus (HPV) infection and low rates of vaccination, the most common gynecological cancer in developed countries is endometrial cancer . Many factors are associated with endometrial cancer, including high estrogen levels, obesity, chronic inflammation, and post-menopausal hormonal therapy. The gut microbiome and the circulating estrogen levels are intensively connected as a feedback loop, influencing each other. We can hypothesize that the gut microbiome, the estrobolome in particular, has a part to play in the development of endometrial cancer, but more research is needed. Moreover, estrogen metabolism and the gut and vaginal microbiome are influenced by obesity. There is an association between the body mass index, the estrogen metabolism and the composition of the vaginal and gut microbiome . A high vaginal pH is correlated with endometrial cancer, usually due to a disbalance of the vaginal flora. For instance, recent studies showed that Atopobium vaginae and Porphyromonas among other bacteria that raise the vaginal pH are more prevalent in the vaginal flora of women with endometrial hyperplasia or endometrial cancer . It is believed that this promotes chronic endometrial inflammation that turns on the carcinogenesis process . Compared with benign uterine lesions, endometrial cancer is associated with a decrease in the diversity of the local endometrial microbiota . Some less-represented endometrial carcinoma species are Salinibacter ruber, Bacillus tropicus, Pusillimonas sp., Riemerella anatipestifer, Nostocales cyanobacterium HT-58-2 and Corynebacterium pseudotuberculosis . This leads to an overgrowth of the remaining species. Micrococcus overgrowth is associated with an inflammatory profile in endometrial cancer, with increased IL-6 and IL-17 mRNA levels. Bilophila, Rheinheimera, Rhodobacter, Vogesella and Megamonas are overgrown in benign uterine lesions . Atopobium vaginae and Popayromonas somerae induce the production of proinflammatory cytokines IL-1a, IL-1b, IL-17a, and TNFa; they also alter the transcription of CCL13, CCL8, CXCL2, IL22 and IL9 . The production of IL-17a induces the production of IL-8 and TNFa, which are promoting factors for endometrial cell proliferation and angiogenesis . TNFa also contributes to resistance to chemotherapy and metastasis development . In endometrial cancer, IL1a and IL1b are overexpressed and promote cell proliferation, adhesion, invasion, and angiogenesis . 2.2. The Microbiome and Ovarian Cancer Ovarian cancer is a relatively rare tumor with a bad prognosis since it develops inconspicuously with no symptoms until the late stages. Genital dysbiosis has been associated with ovarian cancer, although more research is needed to draw causality conclusions . Sexually transmitted bacteria such as Chlamydia spp. and Mycoplasma spp. that cause chronic reproductive tract inflammation have been associated with ovarian cancer. For instance, more than 60% of ovarian tumors contain such intracellular bacteria . Other microorganisms associated with ovarian cancer are Proteobacteria, Acinetobacter spp., Brucella and even viruses such as cytomegalovirus or HPV . Lactobacilli species in the cervicovaginal part of the genital tract have a protective role against ovarian cancer . BRCA mutation carriers are associated with a reduction in Lactobacillus spp. This association is more substantial in younger patients . An increase in Proteobacteria and Fusobacteria characterizes the microbiome in the tumor tissue compared to normal tissue; these gram-negative bacteria make the microbiome more immunogenic . Pelvic inflammatory disease is a risk factor for ovarian cancer . Bacterial flagellin and lipopolysaccharide (LPS) have an essential role in driving inflammation in ovarian cancer by inducing a response in pattern recognition receptors TLR2, 4, and 5 , leading to activation of NF-kappa B signaling . LPS stimulate cancer cells inducing PI3K activation, EMT and overexpression of Vimentin, Snail, a-SMA, TCF, MMP2, N-cadherin, Slug, and MMP9 . Even though LPS activates tumoral-associated macrophages, pushing them towards the M1 profile and making them cytotoxic and cytostatic for ovarian cancer cells , a recent study has shown that administration of LPS does not prolong and may even shorten survival . The increase in Gram-negative bacteria leads to an increase in lysophospholipids, which are by-products of bacterial metabolism . Lysophosphatids are similar to lysophospholipids; in ovarian cancer patients, lysophosphatids plasma levels are increased . In ovarian cancer cells, lysophosphatidic acid can increase the expression of angiogenesis promoters and induce cell migration, invasion and proliferation . A short description of bacterial metabolites effects on ovarian cancer is displayed in Table 1. Bacteria metabolize tryptophan, producing indole-derivatives , which act on the aryl hydrocarbon and pregnane X receptors . Aryl hydrocarbon receptor is involved in immune regulation . Tryptophan rich diet leads to the proliferation of Lactobacilli , which prevents the proliferation of pathogenic bacteria . Tryptophan and indolepropionic acid levels are reduced in the serum of ovarian cancer patients and are inversely correlated with the stage of the disease . Antibiotics (glycylcyclines, erythromycins, tetracyclines and chloramphenicol) can block cellular proliferation and reduce the proportion of ovarian stem cells . Minocycline , Ciprofloxacin , and Salinomycin can reduce the proliferation rate of ovarian cancer cells. In murine models, antibiotics can also be used to prevent cisplatin resistance , and minocycline can potentiate the activity of topoisomerase inhibitors . Even though many studies suggest a potential benefit of antibiotic therapy, there is a study in which the treatment of mice grafted with ovarian cancer with neomycin, ampicillin, vancomycin, and metronidazole was associated with increased invasiveness and growth of the grafts . diagnostics-13-00877-t001_Table 1 Table 1 Effects of bacterial metabolites on ovarian cancer. Bacterial Flagellin Activation of NF-kappa B Signaling Lipopolysaccharides PI3K activation, EMT, overexpression of Vimentin, Snail, a-SMA, TCF, MMP2, N-cadherin, Slug, and MMP9 activation tumoral-associated macrophages Lysophosphatids angiogenesis, cell migration, invasion and proliferation Indole-derivatives immune regulation 2.3. The Microbiome and Cervical Cancer Cervical cancer is a common malignancy in women, especially in developing countries where the HPV vaccination rate is low. Over 99% of cervical cancer biopsies contain HPV Deoxyribonucleic acid (DNA) as determined by Polymerase chain reaction (PCR) . HPV is the major carcinogenic factor in the evolution of cervical cancer through the expression of E6 and E7 proteins. The most high-risk genotypes are HPV 16 and HPV 18. However, it is essential to note that 85-90% of HPV infections with high-risk genotypes are spontaneously cleared . The high-risk HPV infections that persist can, in time, lead to cervical intraepithelial neoplasia (CIN)--low grade and then high grade--and then progress to invasive cervical cancer. The link between vaginal dysbiosis and HPV persistence and neoplastic transformation is yet to be established. Still, various studies have already shown that the composition of the cervicovaginal flora differs in women with different HPV statuses . HPV persistence has been linked with bacterial vaginosis by various studies, and anaerobic flora is conducive to HPV persistence . A high vaginal bacterial diversity and a depletion of Lactobacillus spp. have been repeatedly associated with a low clearance of HPV. HPV-negative women have been shown to host mainly Lactobacillus crispatus and Lactobacillus iners. However, HPV-positive women with a normal cervix contain the two lactobacillus species in different proportions. The risk of cervical transformation is higher with Lactobacillus iners than with Lactobacillus crispatus . Once the HPV infection progresses toward cervical intraepithelial neoplasia, the cervicovaginal bacterial diversity increases correspondingly. The Lactobacillus spp is depleted, and the vaginal pH is elevated. The highest diversity is found in invasive cervical cancer (Fusobacterium necrophorum, Gardnerella vaginalis, Sneathia etc.) . Various studies have shown that vaginal Sneathia associates with HPV persistence and pathological progression to cancer. Atopobium spp. is also associated with HPV persistence . Other organisms that have been shown to influence the transformation of HPV lesions are Candida albicans, Chlamydia trachomatis and Ureaplasma urealyticum . The increase in the diversity of the microbial flora leads to the production of cytokines which amplify the inflammatory response , leading to immune dysregulation in the reproductive tract and thus creating a more suitable site for tumor development . Mycoplasma genitalium causes bacterial cervicitis and vaginitis, increasing the incidence of cervical lesions . Chlamydia trachomatis damages the cervical mucosa and promotes infection of the cervical epithelium by HPV . See Table 2 below. Fusobacterium leads to increased production of interleukin-4, interleukin-10 and in the cervix and vagina; these cytokines are also increased in cervical cancer and squamous intraepithelial disease . 3. Interaction between Cancer Treatment and the Microbiome The main pillars of cancer treatment are surgery, radiotherapy, chemotherapy, targeted molecules, and immunotherapy. This part of the article explores the interaction between cancer treatment and the microbiome. We will summarize what is known on the female reproductive tract microbiome, and in addition we will also explore the gut microbiome. The gut microbiome is much more investigated, and we hope that these insights will lead to new interesting research projects on the female reproductive tract microbiome as well. Moreover, understanding the gut microbiome is important because a lack of oestrogen-metabolizing bacteria (from a lower diversity of the gut microbiota after chemotherapy for instance) could influence the vaginal microbiome composition. Therefore, strategies targeted towards the gut microbiome might have an indirect effect on the vaginal microbiome as well. It is well-known that both radiotherapy and chemotherapy can cause gut mucositis and diarrhea. They also decrease the diversity of the gut microbiome, which is usually linked to digestive tract side effects. In contrast, radiotherapy and chemotherapy seem to increase bacterial diversity of the female reproductive tract, and increased bacterial diversity is a sign of disease, as previously explained. Immunotherapy has emerged as a treatment in multiple types of cancer in recent years. Regarding gynecological cancers, it is of interest especially in patients with MSI-H endometrial, cervical, and ovarian cancer. Not much is yet known about the effects of immunotherapy such as Nivolumab, Ipilimumab and Pembrolizumab on microbiomes. However, we can hypothesize that there is an interesting interplay between immunotherapy and microbiomes since they both act on and modulate the immune system. More research is needed in this direction. Some specific bacteria-like microorganisms, such as Bifidobacterium longum, Ruminococcaceae and Akkermansia muciniphila were found to be more abundant in fecal samples collected from PD-1-responding patients. Oral supplementation with Akkermansia muciniphila proved beneficial in restoring response to immunotherapy in mouse models of epithelial tumors. The authors noticed an increase in the recruitment of CCR9+, CXCR3+, CD4+ T lymphocytes . Proposed mechanisms involve the production of short-chain fatty acids and their pro-apoptotic role in cancer cells through activation of p21 cell cycle inhibitor and specific caspases, but also activation of the mTOR-S6K and STAT3 pathways in T-cells . Administration of an oral cocktail of live Bifidobacterium to tumor-bearing mice significantly improved tumor control for several weeks. The same mice presented elevated levels of tumor-specific T cells in the periphery and antigen-specific CD8+ T cells within the tumor. Authors noticed a lack of anti-tumor effect in immunodeficient mice or mice treated with previously heat-inactivated Bifidobacterium . Opposite results come from the study of Kim et al., who expanded on parabiotics as non-viable microbial cells in the form of heat-killed Bifidobacterium or Lactobacillus. These strains induced apoptosis of human colorectal carcinoma RKO cells in vitro and also revealed anti-tumor effects in an RKO cell-derived xenograft model through the activation of caspase-9, 3, 7 and PARP . Interestingly, antibiotics seem to decrease immunotherapy's efficacy, suggesting a link between these novel treatments and the microbiomes. Antibiotics also seem to increase the toxicity of chemotherapy. Moreover, radiotherapy, chemotherapy and immunotherapy are all less efficient in a germ-free mouse; fecal-matter transplantation and probiotics have been shown to improve the efficacy of immunotherapy . The gut microbiota may be involved in the prevention of chemotherapy-associated toxicity, improved efficacy of oncologic treatment, prevention of surgical morbidity, and quality of life. Diarrhea, abdominal pain, vomiting, and weight loss are critical adverse reactions to chemotherapy that cause significant morbidity. Preventive intervention on the gut microbiota can influence the pathogenesis of mucositis through TLR2 signaling, mediation of vitamin B production, and microbial enzymatic degradation. Additionally, prognostic markers can be derived from specific microbiota patterns. The bowel mucosa load with Fusobacterium nucleatum strains correlates with worse prognostic in patients with colorectal cancer . Modulating microbiomes had essential health benefits in many chronic and inflammatory diseases, including irritable bowel syndrome and recurring Clostridioides difficile infections and implications in cancer prevention and response to treatment. Gut microbiota modulation is represented by probiotics, prebiotics, antibiotics or other drugs, or microbiota transplantation . Bifidobacterium and Bacteroides species have been associated with immune modulation and estrogen metabolism and are under investigation for preventing estrogen-derived cancer such as breast, endometrial, and ovarian cancer . Probiotics containing Lactobacillus lactis engineered to secrete an antimicrobial peptide involved in gut homeostasis (pancreatitis-associated protein) proved to reduce enteritis induced by 5-Fluorouracil in cancer patients. The mechanism was represented by a reduced abundance of pathogenic bacteria such as Enterobacteriaceae in the intestine, thus reducing the intensity of mucositis Fecal microbiota transplantation reduced the side effects generated by chemotherapy and radiotherapy . However, the most important studies are related to fecal microbiota transplantation from responders to germ-free mice with xenograft tumors (melanoma, lung or kidney) which showed an increased response to checkpoint inhibitors . Approaches for modulating vaginal microbiomes are under investigation. They aim to modify vaginal microbiota to optimal Lactobacillus-dominant flora to prevent carcinogenesis and in cancer patients to increase the effectiveness of treatments and decrease toxicity. Novel antimicrobials and probiotics such as intravaginally delivered vaginal lactobacilli formulations, biofilm disruptors, and vaginal microbiota transplantation are being considered. Vaginal probiotic lactobacilli (L. crispatus strain CTV-05 known as ) have been tested with success in clinical trials, mainly for the treatment of bacterial vaginosis or urinary tract infection (UTI) . Vaginal microbiota transplantation (VMT) from donors with optimal vaginal flora is a novel potential treatment option under investigation for women with vaginal disorders. However, there is an unknown long-term risk of microbiome transplants (fecal or vaginal) related to the potential transfer of antimicrobial-resistant microorganisms, which may be problematic in immunodepleted cancer patients. Probiotics consisting of Lactobacillus spp. might aid in the treatment of cervicovaginal dysbiosis and persistent HPV infections . Lactobacillus spp. probiotics might increase the clearance of HPV when used long-term in certain patients . Since it is well established that persistent HPV infections increase the risk of cervical cancer, Lactobacillus spp. probiotics might be considered in HPV positive patients. However, more research is needed before establishing clear links and then guidelines. A study conducted by Tsementzi et al. showed that radiation therapy alone in post-menopausal patients with gynaecologic cancer leads to a perturbation of the vaginal microbiome with a decrease of Lactobacillus spp. The study showed a higher vaginal bacterial diversity in cancer patients with respect to healthy patients and a higher vaginal bacterial diversity in post-radiotherapy with respect to pre-radiotherapy. This might be associated with some post-radiotherapy symptoms in patients with vulvovaginal atrophy and these findings might have implications for future therapeutic interventions, such as probiotics or vaginal microbiome transplantation . Overall, not much is known about the female reproductive tract microbiome and its changes during cancer treatment, and even less is known on the influence of the female reproductive microbiome on the response to various treatments. 4. The Microbiome and Endometriosis Endometriosis is a multifactorial disease whose etiology is not entirely established. One theory is "retrograde menstruation" where the menstrual flux and viable endometrial cells go through the fallopian tubes to the peritoneum, where they adhere. There is an essential component of inflammation, but it is not yet clear if this is a cause or an effect of endometriosis. Interestingly, the composition of the gut microbiome is also linked to this disease. A healthy gut is composed of a balanced distribution of Firmicutes spp. and Bacteroidetes spp. However, in endometriosis, this balance is altered with a predominance of either one or the other species. Endometriosis development can induce a change in the gut microbiome . The complex interrelation between endometriosis, circulating estrogen levels, and gut bacteria warrants further research. 5. Conclusions The microbiome, in general, and the female reproductive tract microbiome, is an exciting research avenue. More and more studies show a connection between different microbiome compositions and various cancers. There is a low diversity of bacterial species in the vagina and cervix, represented mainly by Lactobacillus spp. which prevents colonization of the female genital tract with pathogenic bacteria. The proliferation of pathogenic bacteria leads to a higher diversity of the microbiome. This abnormally diverse microbiome can modulate the immune response in the female genital tract creating an environment characterized by chronic inflammation, which is favorable for developing neoplasia. Some products of bacterial metabolism have carcinogenic properties and act upon the normal cells of the genital tract leading to genetic alterations. Other products of bacterial metabolism have angiogenic properties and promote neovascularization, which favors vascular invasion and metastasis. Moreover, the microbiome also seems to influence the response to therapy and toxicity. The estrobolome, through its effect on estrogen circulating levels, can impact both the composition of the cervicovaginal microbiome and carcinogenesis. More research is needed to describe these interactions better and find ways of harnessing this information toward better treatments. Author Contributions Conceptualization, O.G.T. and R.A.T.; methodology, O.G.T. and D.M.B.; software, L.V.; validation, R.I.M., L.N.G. and G.L.S.; investigation, L.V. and S.A.M.; resources, R.A.T. and B.C.T.; writing--original draft preparation, O.G.T. and D.M.B.; writing--review and editing, R.I.M., D.M.B. and L.V.; visualization, L.N.G.; supervision, R.M.A.; funding acquisition, G.L.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. diagnostics-13-00877-t002_Table 2 Table 2 Examples of bacteria associated with female reproductive tract pathology. Bacteria found to be associated with female reproductive tract pathology, including cancer Popayromonar somerae, Chlamydia spp., Mycoplasma spp., Proteobacteria, Acinetobacter spp., Brucella spp., Fusobacterium necrophorum, Gardnerella vaginalis, Sneathia spp., Candida albicans, Chlamydia trachomatis, Ureaplasma urealyticum Examples of how bacteria might induce pathologic changes in the female reproductive tract Mycoplasma genitalium Cervicitis and vaginitis, chromosomal lesions Chlamydia trachomatis Increased risk of infection of the cervical epithelium by HPV Fusobacterium spp. Increased production of IL-4, IL-10 and TGF-b1 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000485 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050700 healthcare-11-00700 Article The Psychometric Properties of the DASS-21 and Its Association with Problematic Internet Use among Chinese College Freshmen Cao Cui-Hong 1 Dang Chang-Yan 1 Zheng Xia Resources 2 Chen Wang-Guang 3 Chen I-Hua Conceptualization Methodology Validation Investigation Writing - original draft Supervision Project administration 4* Gamble Jeffrey H. Writing - review & editing Visualization Project administration 5* Musetti Alessandro Academic Editor 1 School of Foreign Languages, Shandong Women's University, Jinan 250300, China 2 Mental-Health Education Center, Nanchang University, Nanchang 330031, China 3 School of Administration, Guangdong Polytechnic Normal University, Guangzhou 510665, China 4 Chinese Academy of Education Big Data, Qufu Normal University, Qufu 273165, China 5 Department of English, National Changhua University, Changhua 50007, Taiwan * Correspondence: [email protected] (I.-H.C.); [email protected] (J.H.G.); Tel.: +86-0537-4450537 (I.-H.C.); +886-4-7232105 (ext. 2526) (J.H.G.) 27 2 2023 3 2023 11 5 70012 12 2022 17 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). During transitional periods, college freshmen may experience mental health issues. The Depression, Anxiety, and Stress Scale--21-item version (DASS-21) is commonly used for mental health assessment in China. However, evidence is lacking regarding its applicability with freshmen as a demographic. Debates also exist regarding its factor structure. This study aimed to evaluate the DASS-21's psychometric properties with Chinese college freshmen and investigate its association with three kinds of problematic Internet use. A convenience sampling method was used to recruit two samples of freshmen--one of 364 (female 248; mean age 18.17 years) and the other of 956 (female 499; mean age 18.38 years) participants. McDonald's o and confirmatory factor analysis were conducted to evaluate both the scale's internal reliability and construct validity. The results indicated acceptable reliability, with a one-factor structure inferior to a three-factor structure in terms of model fit. Furthermore, it was demonstrated that problematic Internet use was significantly and positively associated with depression, anxiety, and stress among Chinese college freshmen. Based on the prerequisite of measurement equivalence across two samples, the study also found that freshmen's problematic Internet use and psychological distress were likely to be affected by the strict measures put in place during the COVID-19 pandemic. psychometrics problematic Internet use the DASS-21 Chinese freshmen COVID-19 pandemic 2022 Shandong Province Social Science Foundation22CJYJ16 This research was funded by the 2022 Shandong Province Social Science Foundation Project "Research on teaching management innovation in rural primary schools in the post-pandemic era," chaired by I-Hua Chen (Project No.: 22CJYJ16). pmc1. Introduction Adolescence is a key period when many psychological disorders can occur, and, broadly speaking, college life can be considered the final stage of adolescence for students . Previous studies have demonstrated that, due to feeling frustrated by homesickness, academic performance, pressure to succeed, and environmental changes, as well as being in a transitional period of life, college students are likely to experience more negative emotions and mental disorders in their freshman years . It was reported that college freshmen have a higher level of psychological distress, most likely stemming from experiencing the unknown, newly moving away from home, over-expectations of embarking on a new life path, or feeling overwhelmed by coursework and unfamiliar teaching methods . For all these reasons, college students' psychological distress deserves special attention , as it is not only associated with their struggles in academic performance, dropout rate, and excessive alcohol intake, but also negatively affects their professional development . Therefore, early detection, prevention programs, and mental health interventions are necessary and can have a significant, long-term impact. As such, it is necessary and important to be able to use a reliable and valid instrument to assess the levels of freshmen's psychological distress. 2. Literature Background 2.1. The Depression, Anxiety, and Stress Scale The Depression, Anxiety, and Stress Scale (DASS), is a commonly utilized instrument for screening mental health problems, the full version consisting of 42 items, and the short version consisting of 21 items . Developed by Lovibond et al., this scale takes the form of a self-report questionnaire, with the original purpose of having a consistent measurement system which could be used to distinguish between and define depression, anxiety, and stress, in order to assist with clinical diagnosis using additional psychometric indicators and provide a rapid and accurate tool for screening research subjects . The Depression, Anxiety, and Stress Scale--21-item version (DASS-21) adopted in the present study has the advantage of being able to be completed and scored more quickly. The DASS-21 has been empirically validated with college students from diverse cultures with high internal consistency . In China, several studies have been conducted to assess its psychometric properties. Gong et al. first introduced the Chinese version of this scale. They conducted a survey of college students, finding that the DASS-21 had stable psychometric properties and could successfully reflect the psychological distress status of Chinese college students . Another study also confirmed the satisfactory internal consistency indices for the three subscales--depression, anxiety, and stress (with Cronbach's as of 0.83, 0.80, and 0.82, respectively)--and a total internal consistency of 0.92 . Although this evidence shows that the Chinese DASS-21 can be a useful tool for measuring the psychological distress of college students, there has not been a psychometric evaluation of this scale specifically for college freshmen. Due to the fact that this demographic in particular may be suffering from mental health difficulties, it is important to be able to screen their mental health situations with a reliable scale in order to suggest effective intervention measures . Furthermore, even though there have been many consistent findings regarding the scale's internal consistency regarding college students, many inconsistent findings have also been found regarding its factor structure (i.e., the use of a one-factor or a three-factor structure) when used with the same demographic . Based on this gap, our primary aim was to evaluate the psychometric properties of this commonly used instrument--the DASS-21--for Chinese college freshmen. 2.2. The Association of the DASS-21 with Problematic Internet Use In addition to validating the DASS-21 in the context of Chinese college freshmen, the association of this scale with problematic Internet use (PIU) was also investigated. Existing studies have found that PIU is strongly linked to depression, anxiety, and stress . Recently, Internet and mobile technology have developed rapidly and become more widespread, as modern life has become increasingly inseparable from the Internet. Based on the 50th China Statistical Report on Internet Development released by the China Internet Network Information Center, the number of Chinese Internet users reached 1.05 billion in June 2022, with cellphone users comprising 99.6 percent of this number . Despite the many advantages of using the Internet (e.g., increased accessibility for communication, information searching, and recreation) , the fact that people can now easily obtain access to the Internet and can afford to use it globally contributes to the rising incidence of PIU , a mental disorder manifested as a result of being excessively engaged in out-of-control Internet use which is detrimental to one's well-being . Adolescents experiencing negative emotions and mental disorders have a tendency to resort to the Internet in order to escape from the anxieties or difficulties they face in their daily life . However, being absorbed by the Internet makes it more likely for them to experience both physical and psychological disorders , including insomnia, low self-esteem, depression, anxiety, and stress . These physical and mental health problems are more often found among students experiencing problematic smartphone use (PSU) , problematic social media use (PSMU) , and problematic Internet gaming (PG) . As technological devices have become more prevalent over the past few decades, many college students are now regularly using Internet-based applications and portals . Currently, smartphones are the most commonly used device for accessing the Internet due to its multi-functionality and consequent global popularity . Middle school and college students are the primary age groups of Internet users . Smartphones are a convenient tool that allows people to communicate, socialize, seek entertainment, and enhance their productivity . However, using smartphones excessively may have adverse effects, such as the development of PSU . An analysis of 117 studies concluded that PSU is linked to psychological distress symptoms . Currently, there is a debate within the literature regarding whether this is a result of being addicted to the device itself (e.g., a smartphone) or to the content and applications available and accessible on these devices (e.g., websites, applications, and social networks) . One study has suggested that applications on smartphones are the source of the problematic behavior . Meanwhile, using a single cross-sectional study, Stuart et al. concluded that the level of addiction was greater for the device as a whole than for each particular service it provided . Therefore, the influence of PSU on the emotions of college freshmen should be studied. In addition to smartphones, social media also exerts a great influence on people's living habits. Social media is defined as "Internet-based channels that allow users to opportunistically interact and selectively self-present, either in real-time or asynchronously, with both broad and narrow audiences who derive value from user-generated content and the perception of interaction with others" . PSMU, however, is characterized by the compulsive or poorly controlled use of social media that negatively impacts personal and professional functioning, with growing concern about PSMU among adolescents . Several previous studies found that the level of PSMU is positively associated with the level of psychological distress experienced . Besides smartphones and social media, Internet gaming is another relatively popular form of entertainment about which several public health concerns have been raised. Internet gaming disorder was first treated as a mental health disorder in 2013 by the American Psychiatric Association . Evidence has demonstrated that levels of anxiety, depression, and stress are significantly correlated with PG tendency . Considerable research has been conducted aiming to detect the adverse effects of PSU, PSMU, and PG on college students' psychological well-being. One study with Hong Kong University students as research subjects found that PSMU and PG had positive associations with psychological distress . To the best of our knowledge, only one research study has been conducted to investigate the correlation among three PIUs and psychological distress, and this study concerned Malaysian university students . Therefore, we note a research gap in that PSU, PSMU, and PG have rarely been examined and compared within a single study, specifically concerning college freshmen in a Chinese context. To address this gap, the second aim of this work was to assess and compare the associations between the three PIUs and psychological distress among Chinese college freshmen. 2.3. The Impact of COVID-19 The impact of the novel coronavirus (COVID-19) pandemic on the mental health of college freshmen cannot be ignored. Since the pandemic broke out in December 2019, the Chinese Government has enacted strict prevention and control measures. An early notice issued by the Ministry of Education of the People's Republic of China clarified that, in the case of an infection, campuses were expected to respond quickly to follow emergency plans, which included the quick implementation of isolation protection, on-site disinfection, dormitory lockdown, and online teaching . Two years later, the Omicron variant emerged, with increased transmissibility. To care for the lives and health of teachers and students, as well as to increase campus safety and the overall stability of the education system, as a general policy, China's national education system has unwaveringly adhered to the "dynamic zero COVID" and "external defense import, internal defense rebound" policies . At the time of writing, many universities continue to be under lockdown conditions and students are asked to stay on campus and even remain in their dorms in order to prevent infection and limit the spread of the pandemic. Given that various studies have found that the COVID-19 pandemic and social isolation policies may have resulted in the increased prevalence of serious mental health problems , it is important to investigate whether differences exist between freshmen's psychological states in 2020 and those of freshmen in 2022. To summarize, the present preliminary study had two research questions (RQs): RQ1: What are the DASS-21's psychometric properties regarding Chinese college freshmen, including its internal reliability and construct validity (i.e., factorial validity, convergent validity, and discriminant validity)? In order to find the answer to this question, the present study conducted a cross-sectional study of two groups of college freshmen (i.e., freshmen in 2020, the early stage of the pandemic; and freshmen in 2022, a more recent stage of the pandemic). In addition, a multiple-group analysis was carried out to determine whether or not there was measurement invariance across these two samples. RQ2: What is the association between the DASS-21 and PSU, PSMU, and PG? The present study hypothesized that associations would exist between psychological distress and the three PIUs in Chinese college freshmen. Furthermore, the study expected to find different results regarding mental health between the two freshmen groups as they had experienced different stages of the pandemic. It was decided that the combination of validating the instrument, analyzing the influencing factors (i.e., PSU, PSMU, and PG), and comparing freshmen's psychological states between the 2020 and 2022 cohorts could provide useful insights to both policymakers and university staff to help them better understand the psychological states of those freshmen confronted with public health emergencies, empowering them to develop effective prevention and intervention measures. The study results can also be used as a reference for the formulation and adjustment of campus pandemic prevention and control policies. 3. Materials and Methods 3.1. Participants and Procedure A total of two sets of data were collected, the first in October 2020, and the second in October 2022. The study participants were recruited utilizing convenient sampling. The selection criteria for participants included (1) being a freshman student, (2) understanding simplified Chinese, and (3) owning a smartphone with Internet access for more than three months. The demographic characteristics of the two samples are presented in Table 1. A background questionnaire was included in the survey, as well as the Chinese versions of the following three questionnaires: the DASS-21, the Smartphone Application-Based Addiction Scale (SABAS), the Bergen Social Media Addiction Scale (BSMAS), and the nine-item Internet Gaming Disorder Scale--Short Form (IGDS-SF9). The background information section included items relating to age, gender (male or female), department (science, literature, management, and other), and study program level (undergraduate or junior college). The study obtained approval from the Institutional Review Board of the Jiangxi Psychological Consultant Association (IRB ref: JXSXL-2021-J99). The first set of data, collected in October 2020, was primarily from the city of Nanchang, in the province of Jiangxi. The authors contacted psychology teachers in colleges and universities, letting them know about the purposes of the research and the estimated time needed to answer all the questions on the questionnaire by telephone. After receiving a positive response, the researcher sent the psychology teachers a hyperlink and QR code to access the measurement materials. These teachers shared the link and QR code with their students in the classroom, either before or after class, and students completed the questionnaire immediately after receiving it. During the data collection period, universities were busy adjusting teaching after experiencing the sudden impact of the pandemic in the first half of the year, so the data collection process encountered difficulties, and only 364 participants were recruited, of which 116 (31.9%) were male and 248 (68.1%) were female, the latter being more than double the number of the former. The participants' average age was 18.17 (SD = 0.42) years. All were from undergraduate colleges, studying one of the four categories of majors: literature (33%), management (14%), engineering (39.3), or "other" (13.7%). To collect the second set of data, the author sent an invitation message to research assistants and instructors, distributed an online link to the survey, and also provided information regarding the purposes of the research and the estimated time needed to complete the questionnaire. Several research assistants and faculty members sent the hyperlink and QR code onwards, providing access to the questionnaire to potential participants. The second set of data was collected in October 2022, from schools in a total of 13 provinces, including Shanxi, Guangdong, Guizhou, and Shandong, among others. A final total of 956 participants were recruited in the second round of data collection, of which 457 (47.8%) were male and 499 (52.2%) were female, representing a more balanced distribution. The participants' average age was 18.38 (SD = 1.11) years, and two thirds of the participants came from undergraduate colleges, with one third coming from junior colleges. The students reported that they majored in science (15.8%), literature (15.9%), management (16.3%), engineering (28.7%), or "other" (23.3%). 3.2. Measures 3.2.1. The Depression, Anxiety, and Stress Scale--21-Item Version (DASS-21) Developed by Lovibond and Lovibond, the DASS-21 is a shortened version of the original 42-item scale . The scale consists of three self-reported subscales for depression, anxiety, and stress that are intended to measure the psychological distress experienced by the participant over the previous week. Each subscale comprises seven items. An example of a depression subscale item is "I found it difficult to work up the initiative to do things". An example of an anxiety subscale item is "I was worried about situations in which I might panic and make a fool of myself". An example of a stress subscale item is "I felt that I was using a lot of nervous energy". The 21 items are rated on a Likert scale with four points, ranging from 0 ("did not apply to me at all") to 3 ("applied to me very much or most of the time"). An overall higher score is indicative of a higher severity of psychological distress. Previous research has already proven that the DASS-21 possesses satisfactory psychometric properties coupled with a high degree of consistency and a confirmed unidimensional structure . Moreover, it has been demonstrated that the Chinese version of this instrument has good internal consistency (a = 0.89) among Chinese college students . Please refer to the Results section, below, for information on the scale's reliability and validity for the college freshmen participating in this study. 3.2.2. The Smartphone Application-Based Addiction Scale (SABAS) The SABAS was adopted to gauge the severity of problematic smartphone use by college freshmen. Developed by Csibi, Demetrovics, and Szabo , the scale contains six items. The six items are rated on a six-point Likert scale ranging from 1 ("strongly disagree") to 6 ("strongly agree"). An example of an SABAS item is "If I cannot use or access my smartphone when I feel like, I feel sad, moody, or irritable". The maximum score is 36, with a higher score indicating that the participant is more severely addicted to smartphone use. Acceptable psychometric properties for this scale have been demonstrated in different languages in several previous studies, including English , Hungarian , Persian , and Italian . The unidimensional structure SABAS's Chinese translation has good internal reliability when used for Hong Kong University students (a = 0.75) and mainland Chinese primary school students (a = 0.81) . In the current study, the internal consistency of the SABAS had a McDonald's o of 0.745 for the first set of data and 0.884 for the second set of data. 3.2.3. The Bergen Social Media Addiction Scale (BSMAS) The BSMAS was used to assess the severity of college freshmen's PSMU. Developed by Andreassen et al. , this scale contains six items, and each evaluates a person's experience of using social media during the past year. An example item is "How often during the last year have you become restless or troubled if you have been prohibited from using social media?" The six items are rated on a five-point Likert scale with a maximum score of 30, with categories ranging from 1 ("very rarely") to 5 ("very often"). A higher total score means that the respondent's risk of PSMU is more severe . The Chinese version of the BSMAS has been previously validated for use on Chinese primary school students with acceptable psychometric properties . In the present study, the internal consistency of the BSMAS had a McDonald's o of 0.782 for the first set of data and 0.866 for the second set of data. 3.2.4. The Internet Gaming Disorder Scale--Short Form (IGDS-SF9) The current study adopted the IGDS-SF9 to assess the severity of PG in college freshmen. This measure is a self-report scale developed by Pontes and Griffiths based on DSM-5 criteria . It comprises nine items evaluating how an individual has recently experienced gaming activity. An example item is "Do you feel the need to spend an increasing amount of time engaged in gaming in order to achieve satisfaction or pleasure?" A five-point Likert scale is used to rate the nine items, ranging from 1 ("never") to 5 ("very often"). The sum of the individual item scores, with a minimum potential score of 9 and a maximum possible score of 45, is used to determine the overall result, with higher total scores indicating that the respondent has a more severe degree of gaming disorder. Previous research has proven that the IGDS-SF9 is a valid and reliable scale which can be used to measure PG . Previous studies have been conducted to assess the Chinese version among Hong Kong adults , Hong Kong university students , and mainland Chinese primary school students, all with acceptable psychometric properties . In the current study, according to the preliminary analysis, the internal consistency of the IGDS-SF9 had a McDonald's o of 0.906 for the first set of data and 0.930 for the second set of data. 3.3. Data Analysis Strategy The current study adopted descriptive statistics and Pearson correlations for the purpose of analyzing the mean (SD) of the included variables and the correlations among them. Additionally, to compare how much the variables varied between the participants of the 2020 and 2022 cohorts, an independent t-test method was adopted in order to determine whether the discrepancies between the variables were at a statistically significant level. Subsequently, McDonald's o and confirmatory factor analysis (CFA) were both utilized to assess the DASS-21's internal consistency and factorial validity. Regarding its factorial validity, two fits of structures were compared: one was a one-factor structure and the other was a three-factor structure, in addition to evaluating the individual factor structure used. It is noteworthy that we conducted an Exploratory Factor Analysis (EFA) on two separate samples. This was done to address the ongoing controversy regarding the dimensional structure of DASS-21; the EFA, which allows for the cross-loading of items, provided additional support for the use of Confirmatory Factor Analysis (CFA). However, considering the extensive testing that has been performed on the DASS-21, as mentioned previously, and that EFA is usually employed in the scale development stage , the EFA results are presented in the Supplementary Information file which accompanies the present work. We further tested the convergence, discriminant validity, and measurement invariance using CFA. Based on the standardized factor loadings, the composite reliability (CR) and average variance extracted (AVE) were computed to investigate convergent and discriminant validity. In order to evaluate DASS-21's measurement invariance across the two samples, a comparison of several models was conducted, which included (a) a configural model (i.e., no constrained model, as a baseline model); (b) a factor-loading constrained equal model (less constrained model); and (c) a factor-loading and item-intercept constrained equal model (more constrained model). When the differences of the fit indices from different models do not violate the criterion, the equivalence of the DASS-21 across distinct samples can be determined. Finally, for the examination of the associations between PIU and the DASS-21, structural equation modeling (SEM) was utilized in the current study to test the influence of the three PIUs on freshmen's DASS-21 score, with gender as the controlled variable, considering potential differences in the prevalence of PIU between males and females. In terms of the criteria of the above-mentioned statistics, several indices were used. For factorial validity and SEM, indices including the comparative fit index (CFI), non-normed fit index (NNFI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR) were selected. In order to meet the criteria, it was essential to meet the following values: the values of CFI and NNFI should not be lower than 0.95; the values of RMSEA should not be higher than 0.06; and the values of SRMR should not be higher than 0.08 . As for the model selection of the factor structure, the Akaike information criterion (AIC) was adopted by the current study to compare the models with acceptable fit indices to determine which had the best model fit (i.e., smaller AIC indicates a better fit) . For better convergent and discriminant validity, convergent validity is considered to be satisfactory when the CR is greater than 0.70 and the AVE is greater than 0.50 for each construct . Additionally, the square root of the AVE needs to be greater than the correlations between the constructs, thus supporting the discriminant validity of the construct . Regarding measurement invariance, a comparison of the models using CFI, RMSEA, and SRMR was performed to verify whether measurement invariance could be supported, with the following requirements: an DCFI higher than -0.01, an DRMSEA lower than 0.015, and an DSRMR lower than 0.03 (for factor-loading constrained) or lower than 0.01 (for item-intercept constrained) . 4. Results 4.1. Descriptive Statistics and Pearson Correlations The mean values of Sample 1 (collected in October 2020) and Sample 2 (collected in October 2022) for the observed variables and the correlations between these variables are presented in Table 2. The results show that college freshmen in 2022 had a significantly higher prevalence of depression than college freshmen in 2020 (t = 2.89, p < 0.01, Cohen's d = 0.18, with the value of 0.18 indicating a small effect size). Moreover, freshmen in 2022 also showed significantly more severe PIU than freshmen in 2020, with the differences having either small effect size, small to medium effect size, or medium to large effect size, depending on the type of PIU (PSU: t = 2.52, p = 0.01, Cohen's d = 0.16; PSMU: t = 4.66, p < 0.01, Cohen's d = 0.29; PG: t = 7.88, p < 0.01, Cohen's d = 0.49). In terms of the Pearson correlations, significant positive relationships were found among all variables. Of these coefficients, strong associations were found regarding the three emotional disorders (Sample 1: r = 0.59 to 0.74, all p < 0.01; Sample 2: r = 0.79 to 0.83, all p < 0.01). Despite the fact that the three types of PIU were mutually correlated in the two samples, we noticed that a relatively moderate magnitude of correlation was found for the three PIUs in Sample 1 (r = 0.29 to 0.47, all p < 0.01), with a relatively higher magnitude of correlation for Sample 2 (r = 0.50 to 0.61, all p < 0.01). Additionally, the three emotional disorders and three different types of PIU were all positively correlated, and paired correlations were higher in Sample 2 (r = 0.42 to 0.48, all p < 0.01) than in Sample 1 (r = 0.22 to 0.38, all p < 0.01), which is similar to the pattern seen in the association among the three PIUs. 4.2. Reliability, Factorial, Convergent, Discriminant Validity, and Measurement Invariance For Sample 1 data, the internal consistency was acceptable, and the McDonald's os for depression, anxiety, and stress were 0.789, 0.633, and 0.755, respectively. For the Sample 2 data, the internal consistency was excellent, and the McDonald's os for depression, anxiety, and stress were 0.887, 0.825, and 0.861, respectively. In terms of the factorial validity of the factor structure, the CFA results in the current study demonstrated that the scale fit the factor structure well in both samples (i.e., the fit indices mostly met the criteria (see Table 3)). Furthermore, the fit was significantly better for the three-factor structure than for the one-factor structure, due to a much lower AIC for the three-factor structure (Sample 1: one-factor structure = 652.67 and three-factor structure = 571.79; Sample 2: one-factor structure = 1043.83 and three-factor structure = 826.94). As for convergent validity, the results demonstrated that the convergent validity of the DASS-21 was ideal in Sample 2, since the CR for each factor was higher than 0.70 (the CRs of depression, anxiety, and stress in the current study were 0.94, 0.78, and 0.90, respectively) and the AVE of each factor was higher than 0.50 (the AVEs of depression, anxiety, and stress in the current study were 0.70, 0.57, and 0.59, respectively). Compared to Sample 2, although the CRs of all three dimensions were also higher than 0.70 in Sample 1 (the CR of depression, anxiety, and stress in the current study was 0.89, 0.78, and 0.82, respectively), but the value of the AVEs (the AVE of depression, anxiety, and stress in the current study were 0.54, 0.34, and 0.41, respectively) was unsatisfactory. As for the discriminant validity, the results revealed poor discriminant validity for both samples for the three DASS-21 factors because the square root of the AVE for each factor was less than the correlation between the latent factors (see Table 4). These findings are further supported by the results of the EFA. The Scree plot from the EFA results shows that the number of factors extracted from both Sample 1 and Sample 2 does not align with the initial expectations of the three factors . Additionally, the factor loadings reveal cross-loadings for some of the items (see Tables S1 and S2), indicating a potential issue with the overly high correlations among the latent variables in the DASS-21. These findings suggest that these three factors should be considered as an overall construct, namely, psychological distress, rather than three separate constructs. Regarding the examination of measurement invariance across the two sets of data, the results indicated that the equivalence of the DASS-21 was supported across the two samples in terms of both factor loadings and the item thresholds in both the one-factor structure and three-factor structures (see Table 5). Specifically, the DASS-21 had generally acceptable fit indices in the configural model, with the exception of SRMR, which had a value slightly higher than 0.80. Moreover, the results of the model comparison showed that the DCFI ranged from -0.006 to 0.001, DRMSEA ranged from 0 to 0.011, and DSRMR ranged from 0.003 to 0.011. All these values met the criteria for measurement invariance. 4.3. Associations between PIU and the DASS-21 For the purpose of examining the associations between PIU and the DASS-21 in SEM, we used the mean score of the three sub-scales (depression, anxiety, and stress) as the indicators of a general construct (i.e., psychological distress), given that the above results indicated that the score of the DASS-21 should be considered as an overall variable, due to poor discriminant validity for the three sub-factors. Using gender as the controlled variable, the results of the current study revealed that the model in both samples had generally satisfactory fit indices, despite the fact that RMSEA did not meet the criterion in Sample 1 . Subsequently, the results of the path coefficients indicated that higher PSU and PG contributed to a more severe level of psychological distress in both samples (Sample 1: PSU = 0.37, t = 3.83, p < 0.01; PG = 0.15, t = 2.55, p = 0.01) (Sample 2: PSU = 0.32, t = 6.74, p < 0.01; PG = 0.24, t = 5.42, p < 0.01). Finally, regarding the association between PSMU and psychological distress, the results showed that, although a higher PSMU was more indicative of poorer mental health in Sample 2 (b = 0.13, t = 2.66, p < 0.01), this association did not exist in Sample 1. Clearly, higher PSU and PG values reflected a more severe level of psychological distress in freshmen compared to PSMU. 5. Discussion In consideration of the unique psychological status of college freshmen and the current lack of effective measurement scales for use regarding this demographic, the current investigation evaluated the reliability and validity of the DASS-21 for use among Chinese college freshmen using two sets of sample data (from October 2020 and October 2022). In addition, due to the fact that some debate still exists regarding its factorial validity, the DASS-21 factor structure was also examined in more detail. Furthermore, this study assessed the associations between three PIUs (PSU, PSMU, and PG) and freshmen's psychological distress. The results indicated that the DASS-21 possesses robust psychometric properties for use among Chinese college freshmen and had reasonable factorial validity using either a three-factor structure or a one-factor structure, which is inconsistent with the results of previous studies . Moreover, it was also found that PIUs had a significant and positive relationship with Chinese college freshmen's psychological distress: the higher the PIU level, the more severe their psychological distress. PSU and PG, two out of the three PIUs, contributed more to harming the mental health of freshmen than PSMU, the third type of PIU. 5.1. Psychometric Properties of the DASS-21 for Chinese College Freshmen As for the evaluation of psychometric properties, the reliability of the Chinese version of the DASS-21 was deemed to be acceptable for both samples of college freshmen used. All three scales and the total scores displayed an acceptable degree of internal consistency, which means that the DASS-21 can be reliably used to assess freshmen's psychological distress. The results obtained in the current study are in agreement with those obtained in previously conducted studies using the Chinese and other versions of the measure for college students . As for the validity evaluation, the present study adopted a CFA approach to assess factorial validity, and it was demonstrated that the scale fit the one-factor and three-factor structures well in both samples; however, the three-factor structure was a better fit than the one-factor structure. This finding was in line with that of previous studies . Moreover, comparing the convergent validity of both samples, the DASS-21 was found to have unsatisfactory discriminant validity. Consequently, we recommend that the DASS-21 be treated as an overall construct of psychological distress, rather than three separate constructs. 5.2. Significant and Positive Association between the DASS-21 Results and PSU, PSMU, and PG Regarding the association between the three PIUs (PSU, PSMU, PG) and freshmen's psychological distress, the present study adopted SEM analysis. The findings demonstrated that PSU, PSMU, and PG all had a significant and positive influence on freshmen's psychological distress, which also echoes the results of previous studies . These findings affirm the association in problematic smartphone, social media, or Internet gaming use, in terms of increased likelihoods of suffering from psychological distress. We also found that PSU and PG caused more severe psychological distress for freshmen than PSMU, which is similar to that of prior findings . Despite the fact that no cause-and-effect relationship was established in this study, we speculate that, to some degree, social media platforms can be used by freshmen to maintain communication with family and friends, and also to alleviate loneliness and boredom, both of which can reduce anxiety and long-term distress, and are therefore can be helpful to students, especially when in isolation, as a means of reducing psychological distress . However, we should also note that once an individual has become accustomed to communicating online, rather than face-to-face, the individual may have difficulty communicating effectively offline, which may exacerbate their psychological problems. 5.3. Discrepancies between Two Samples Due to the Impact of the Pandemic Furthermore, it should be pointed out that, based on the fact that the DASS-21 results were found to possess characteristics of measurement invariance across the two samples, t-tests could be utilized to evaluate discrepancies between these groups without confounding the interpretation of the items. The present study also found that the state of the mental health of freshman in 2022 was worse that of the 2020 cohort. Especially in terms of depression, freshmen in 2022 were found to be more severely affected. The findings regarding the relatively poorer state of the mental health of the freshmen in 2022 are consistent with that of previous studies conducted on university students . Chinese college students were found to experience a higher prevalence of depression (26.0%) during the COVID-19 pandemic, while this prevalence was lower (23.8%) in the pre-COVID-19 era . Peng et al. suggested that college students' level of anxiety during lockdown conditions increased from June 2020 to June 2021 . In line with these findings, this study revealed that COVID-19 prevention and control policies may serve as potential risk factors for the deterioration of the psychological well-being of college students. At the end of 2019, the COVID-19 pandemic first broke out in Wuhan, China, but was largely under control by April 2020, across the country . Chinese college students began to return to campus starting in May 2020 . The freshmen in Sample 1 entered college and simultaneously started a new phase of their lives (i.e., in September 2020), after passing their college entrance examination. At that time, the Sample 1 participants did not experience much psychological pressure due to zero (or very few) pandemic cases in their cities. In comparison, Sample 2 participants took part in the current study in the second half of 2022, when the pandemic situation had begun to once again become severe in China. Many colleges and universities quickly launched pandemic prevention and control measures in response to this situation , and campuses implemented school closure management and launched fully online teaching (e.g., restricting students from leaving campus, strictly limiting campus activities, and even requiring students to stay in their dorms during emergency situations) . Although these measures effectively protected students from the infection, their harm to the students' mental health should not be ignored. Indeed, it was more challenging for freshmen, who had just entered university after experiencing an intense high school life and highly competitive college entrance examinations. The situation they faced was not the freedom they expected but, instead, strict lockdown and life in isolation in their dorms. These were huge obstacles for them to adapt to, which could have easily caused them to experience increased psychological distress. Consequently, the mental health statuses of these freshmen, who had recently left their parents, deserves more attention and the monitoring of freshmen students' psychological distress. A higher degree of correlation among PSU, PSMU, PG, and psychological distress (i.e., depression, anxiety, and stress) was noted in Sample 2 (October 2022) as compared to Sample 1 (October 2020). This is partly due to the changes in the pandemic situation and in the prevention and control measures. Compared with the second half of 2020, more Chinese colleges and universities had implemented campus closure policies in the second half of 2022 . One prior study demonstrated how people's daily lives can be adversely affected by prolonged pandemic lockdowns that limit their regular activities, including work and study habits . Students were more susceptible to be afflicted by PIUs when universities were required to cease all campus activities and move all academic activities online as a result of the COVID-19 lockdown measures , and the higher severity and prevalence of PIUs, coupled with prolonged lockdowns, has led to poorer mental health. 5.4. Summary of Findings and Limitations To summarize, the results of the present study have two similarities with previous studies. Firstly, as for the DASS-21 factor structure, both one-factor and three-factor structures were found to be acceptable, but the latter was found to be a better fit. This finding echoes that of previous studies . Secondly, PSU, PSMU and PG were all confirmed to be positively correlated with the depression, anxiety, and stress levels of Chinese college freshmen, which is in line with the findings of previous studies . The association was stronger for the data of Sample 2, which shows that college students' mental health worsened due to the pandemic. This finding is inconsistent with that of a previous study . In addition, the present study also found that the correlation among the three subscales of the DASS-21 was very high, which indicates a low discrimination rate. This finding is different from that of a previous study conducted with Chinese college students, which pointed out that the DASS-21 had good discriminant validity . There are some limitations of this study which must be addressed. First, the method of convenience sampling was adopted in order recruit participants; hence, generalizing the results reported in this study to all Chinese college freshmen would be inappropriate. In addition, the first sample we recruited was smaller than the second. Larger and more representative samples are suggested for future research in order to confirm the preliminary results obtained by the current study. Second, even though we used measurement invariance as the basis for the comparison of the means of the two datasets, we found that there was a significant difference between the two. However, because we did not track the same group of freshmen with a longitudinal design, these conclusions must be taken with caution. More longitudinal studies are necessary in the future. 6. Conclusions According to the findings of the current study, the Chinese DASS-21 is demonstrated to be valid and reliable for assessing the psychological distress of Chinese college freshmen. In addition, the study found that PIUs and psychological distress were significantly correlated, which further confirmed the current concerns centering around the problematic Internet use of Chinese college and university students, especially with regard to PSU and PG. The findings of this study reiterate the importance of paying close attention to the online behaviors of college freshmen. Moreover, given that freshmen faced many unfamiliar situations while experiencing unexpected lockdowns after they entered their universities, university faculty and healthcare providers should provide proper psychological counseling, and the relevant departments should give more consideration to their mental health when formulating and adjusting pandemic prevention policies. Acknowledgments We thank all the participants to take part in the study. Supplementary Materials The following supporting information can be downloaded at: Table S1: Factor loadings in Exploratory Factor Analysis of the DASS-21 among sample 1 (1 October 2020); Table S2: Factor loadings in Exploratory Factor Analysis among sample 2 (1 October 2022). Figure S1: Scree plot of sample 1 (1 October 2020); Figure S2: Scree plot of sample 2 (1 October 2022). Click here for additional data file. Author Contributions Conceptualization, I.-H.C. and C.-H.C.; methodology, I.-H.C.; software, X.Z.; validation, I.-H.C., C.-Y.D. and J.H.G.; formal analysis, C.-H.C.; investigation, I.-H.C.; resources, X.Z. and W.-G.C.; data curation, W.-G.C.; writing--original draft preparation, I.-H.C. and C.-H.C.; writing--review and editing, C.-Y.D. and J.H.G.; visualization, J.H.G.; supervision, I.-H.C.; project administration, I.-H.C. and J.H.G.; funding acquisition, I.-H.C. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Jiangxi Psychological Consultant Association (IRB ref: JXSXL-2021-J99). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data generated for the present study are available from the corresponding authors on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Structural equation modeling of the associations between problematic smartphone use, problematic social media use, and problematic gaming, using the DASS-21. The former and latter values were calculated using the data sets from October 2020, and October 2022. * means p < 0.05, ** means p < 0.01. healthcare-11-00700-t001_Table 1 Table 1 Demographic characteristics of study participants. Sample 1 (October 2020) n = 364 Sample 2 (October 2022) n = 956 Age in years; mean (SD) 18.17 (0.42) 18.38 (1.11) Gender; n (%) Male 116 (31.9) 457 (47.8) Female 248 (68.1) 499 (52.2) Department; n (%) Science 0 151 (15.8) Literature 120 (33.0) 152 (15.9) Management 51 (14.0) 156 (16.3) Engineering 143 (39.3) 274 (28.7) Others 50 (13.7) 223 (23.3) Study program level; n (%) Undergraduate 364 (100) 642 (68.1) Junior college 301 (31.9) healthcare-11-00700-t002_Table 2 Table 2 Descriptive and correlation values between the variables. Variable (Range) M SD 1 2 3 4 5 6 1. Depression (0-42) 5.33/6.57 5.62/7.38 1 2. Anxiety (0-42) 7.10/7.06 4.60/6.53 0.62/0.79 1 3. Stress (0-42) 8.56/8.55 5.71/7.23 0.59/0.80 0.74/0.83 1 4. PSU (6-36) 17.98/18.92 5.01/6.43 0.37/0.47 0.38/0.46 0.33/0.48 1 5. PSMU (6-30) 12.85/14.07 3.71/4.46 0.28/0.42 0.30/0.42 0.31/0.44 0.47/0.61 1 6. PG (9-45) 13.93/17.11 5.46/6.92 0.29/0.48 0.26/0.43 0.22/0.43 0.31/0.50 0.29/0.52 1 Notes: The former and latter values were calculated using data sets from October 2020 and October 2022, respectively. The severity of depression, anxiety, and stress was then assessed using the Depression, Anxiety, and Stress Scale--21-item version where the values were computed by multiplying the score by two; PSU = problematic smartphone use; PSMU = problematic social media use; PG = problematic gaming. All p < 0.01. healthcare-11-00700-t003_Table 3 Table 3 Model fit of the different factor structures. kh2 (df) CFI NNFI RMSEA (90% Confidence Interval) SRMR AIC One-factor model Sample 1 (October 2020) 568.67 (189) 0.968 0.965 0.074 (0.067-0.082) 0.091 652.67 Sample 2 (October 2022) 959.83 (189) 0.989 0.988 0.065 (0.061-0.070) 0.051 1043.83 Three-factor model Sample 1 (October 2020) 481.79 (186) 0.975 0.972 0.066 (0.059-0.074) 0.086 571.79 Sample 2 (October 2022) 736.94 (186) 0.992 0.991 0.056 (0.052-0.060) 0.046 826.94 Notes: CFI = comparative fit index; NNFI = non-normed fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; AIC = Akaike information criterion. healthcare-11-00700-t004_Table 4 Table 4 Results of convergent and discriminant validity analysis of the DASS-21. Depression Anxiety Stress Depression 0.73/0.84 Anxiety 0.92/0.92 0.58/0.75 Stress 0.82/0.93 0.99/0.98 0.64/0.76 Notes: Diagonal elements in bold are square root of averaged variance extracted. When these values were higher than the inter-latent factor correlations (off-diagonal elements), discriminant validity was supported for the respective latent variable. healthcare-11-00700-t005_Table 5 Table 5 Fit indices for measurement invariance across freshmen from two data sets. Configural Model Loadings Constrained as Equal Loadings and Thresholds Constrained as Equal One-factor model kh2(df) or Dkh2(Ddf) 1452.03 (378) 75.36 (20) 518.78 (20) CFI or DCFI 0.987 -0.001 -0.006 RMSEA or DRMSEA 0.066 0 0.011 SRMR or DSRMR 0.091 0.011 0.009 Three-factor model kh2(df) or Dkh2(Ddf) 1141.56 (372) 61.86 (18) 187.27 (18) CFI or DCFI 0.989 0.001 -0.002 RMSEA or DRMSEA 0.056 0 0.004 SRMR or DSRMR 0.086 0.003 0.003 Notes: CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual. The bold values indicate invariance, i.e., DCFI > -0.01; DRMSEA < 0.015; DSRMR < 0.03 (for factor loading) or <0.01 (for item intercept). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000486 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050655 healthcare-11-00655 Article Analysis and Forecast of Indicators Related to Medical Workers and Medical Technology in Selected Countries of Eastern Europe and Balkan Stepovic Milos Conceptualization Methodology Investigation Data curation Writing - original draft Visualization Project administration 1 Vekic Stefan Software Data curation Writing - review & editing Project administration 2 Vojinovic Radisa Validation Writing - original draft 3 Jovanovic Kristijan Formal analysis Writing - original draft Project administration 4 Radovanovic Snezana Validation Writing - review & editing 5 Radevic Svetlana Validation Writing - review & editing 5 Rancic Nemanja Conceptualization Methodology Resources Data curation Writing - review & editing Supervision Funding acquisition 67* Myint Phyo Kyaw Academic Editor 1 Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia 2 Faculty of Economics, University of Belgrade, 11000 Belgrade, Serbia 3 Department of Radiology, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia 4 Department of Anatomy, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia 5 Department of Social Medicine, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia 6 Medical Faculty of the Military Medical Academy, University of Defence in Belgrade, 11000 Belgrade, Serbia 7 Centre for Clinical Pharmacology, Military Medical Academy, 11000 Belgrade, Serbia * Correspondence: [email protected] 23 2 2023 3 2023 11 5 65511 1 2023 07 2 2023 08 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Health indicators measure certain health characteristics in a specific population or country and can help navigate the health systems. As the global population is rising, the demand for an increase in the number of health workers is simultaneously rising. The aim of this study was to compare and predict the indicators related to the number of medical workers and medical technologies in selected countries in Eastern Europe and Balkan in the studied period. The article analyzed the reported data of selected health indicators extracted from the European Health for All database. The indicators of interest were the number of physicians, pharmacists, general practitioners and dentists per 100,000 people. To observe the changes in these indicators through the available years, we used linear trends, regression analysis and forecasting to the year 2025. The regression analysis shows that the majority of the observed countries will experience an increase in the number of general practitioners, pharmacists, health workers/professionals and dentists, as well as in the number of computerized tomography scanners and the number of magnetic resonance units, predicted to occur by 2025. Following trends of medical indicators can help the government and health sector to focus and navigate the best investments for each country according to the level of their development. health indicators medical workers medical technology Eastern Europe Balkan This research received no external funding. pmc1. Introduction Health indicators measure certain health characteristics in a specific population or country . Health indicators aim to describe and monitor the health status of the population. There are many definitions of health indicator which are designed by important institutions and organizations. Some of the reasons for the utilization of health indicators are program management, resource allocation, country progress monitoring, performance-based payment and global reporting . Health indicators can be sorted into four different spheres: indicators of health status, indicators of the health system, indicators of health status and indicators of service coverage. Information concerning health workers, health financing and quality of healthcare and medical information can be provided from these indicators . Throughout the 20th century, health systems have made a huge contribution to better health in the majority of the world's population . Health systems currently play a larger and more influential role in people's lives than in the past. During the last century, health systems were subjected to different reforms, such as the establishment of different healthcare systems and propagation of social security. Primary healthcare became a path towards the ultimate goal of every health system, which is universal health coverage, affordable to all . The goal is not only to achieve care for all but also provide all with quality basic care, defined mainly by the criteria of efficiency, cost and social acceptability . As the global population is rising, the demand for the increase in the number of health workers is simultaneously rising. The United Nations High-Level Commission on Health Employment and economic growth projected that compared to the 2013 population, 80 million health workers will be needed just to keep up with the demands of the global population, compared to the number of health workers worldwide at the moment of projection, which leaves a gap of 18 million . Such a large gap will influence the likelihood of the global community achieving universal health coverage. The lack of medical workers will also influence the quality of healthcare provided for the less-developed parts of countries and will mostly affect rural areas . Inadequate health availability will end with a rise in communicable and non-communicable diseases, becoming a large part of the global burden of disease; it will create a higher necessity for additional tests, drugs and different and expensive technologies that may be lacking with respect to the numbers per capita worldwide, and eventually, it will increase mortality and morbidity rates. Another problem is the migration of health workers, thus leaving some of the less-developed countries with even bigger problems . Citizens older than 65 years are especially vulnerable as their proportion is rising every year. With this global aging also comes health expenditures for different drugs, treatments and necessary tests and examinations due to the likely presence of comorbid diseases. Countries in different states of development will be able to invest varying amounts of GDP in healthcare, which will create further problems. Communicable diseases are also unable to be entirely removed as they are also present in, and not typical for, any age group. During the COVID-19 pandemic, the necessity for good health system organization and sufficient medical workers and technologies was imperative . The last few decades have demonstrated that medical technology utilization accounts for the greatly increased percentage of health spending (of nearly 50%). New technologies improve medical care, but as mentioned they also influence the rise in healthcare expenditures that affects both governmental and individual budgets . Eastern Europe and Balkan, the Russian Federation and the former Union of Soviet Social Republics, and Turkey are countries that have a shared historical background; therefore, the way they manage different economic crises affects their similarly organized health systems. These countries have very diverse population structures when considering religion (Catholicism, Orthodox Christianity and Islam), which is very important when considering their historical approaches towards creating important solutions compared to Northern and Southern Europe. When developing their health systems, these countries also had very dependent relationships between each other, as the health systems that these countries used were those that others adapted to their own countries. There were three systems of health financing that were dominant throughout the 19th century: the Bismarck, Beveridge, and Semashko systems . Progress in medical technology and pharmaceuticals were hard to follow, as the other, more developed countries of Europe and the countries that we selected had large problems in accessing medical healthcare, especially in the rural and less-developed parts of countries. A great deal of medical expenditure was paid out-of-pocket. Those countries were less industrially developed at the time, especially during the Cold War, and much of their GDP came from their agricultural economy, which could not endure such a fast medical development, particularly when population aging became more prominent. The socioeconomic situation of these countries was weak, so healthcare was quite expensive and less available to all . The aim of this study was to compare and predict the indicators related to the number of medical workers and medical technologies in selected countries of Eastern Europe and Balkan with similar historical backgrounds in the development of their health systems. The problem of the insufficient number of medical workers and technologies in some of these countries, due to different scenarios, can affect the health coverage of citizens and health organizations. Similar articles can help notice and prevent these problems. 2. Materials and Methods This study was conducted as a descriptive data analysis of observed indicators of interest--indicators of medical workers and indicators of health expenditures. The data source was the European Health for All database (HFA-DB), where Member States of the WHO (Geneva, Switzerland) European Region have been reporting essential health-related statistics since the 1980s . This database is a cluster of different indicators that are part of major monitoring frames; it is based on reports, not estimates, and provides a large range of following years. The selected indicators were physicians per 100,000 inhabitants, pharmacists (PP) per 100,000 inhabitants, general practitioners (PP) per 100,000 inhabitants and practicing dentists per 100,000 inhabitants. PP is an abbreviation for practicing physician/persons. All medical indicators used in this article provide some aspect of medical health; persons in the educational process were not included in these indicators. Every used indicator has inclusion and exclusion criteria defined by the World Health Organization before being inputted into the HFA-DB. Indicators of increased medical expenditures were also analyzed: the total number of computer tomography scanners per 100,000 inhabitants and the total number of magnetic resonance imaging units per 100,000 inhabitants. The included countries were: Albania, Bulgaria, Bosnia and Herzegovina, Belarus, Greece, Croatia, North Macedonia, Montenegro, Romania, the Russian Federation, Serbia, Slovenia, Turkey, Estonia, Lithuania, Latvia and Ukraine. The observation period was from 1990 to 2016 (the last year available from HFA-DB after the database update in September 2022). Countries without consistent following of the defined indicators were not included in the analysis. Years that were observed varied between the countries; therefore, the first year used was the year that most of the countries had in common, and the last year used was 2014 or 2016. As we were observing changes in these indicators only through time (continuous variable), a linear trend was chosen for the analysis . With this data, we were able to access the current simple linear trends using the Excel mathematics algorithm and construct the graphs that showed us the changes in those trends. Linear regression predicted values based on the data from the available two and a half decades . Forecasting techniques are commonly utilized for historical data, as is the case in our research, and we used medium-term forecasting analysis, anticipating several years in advance (to the year 2025). Forecasting analysis was performed by combining Excel analysis and IBM SPSS program version 26.0. SPSS is an IBM (Armonk, NY, USA) product designed for statistical analysis, predictive analysis, big data integration and similar algorithms. Only one decade after the last available year was predicted with the purpose of tracking the current trends. A regression line uses a formula to calculate its predictions: Y = A + BX. Y is the dependent variable, X is the independent variable, B is the slope of the line and A is the point where Y intercepts the line. Regression gives an R-squared value; the values range from 0 to 1, with 0 being a weaker model and 1 being a stronger model. The confidence interval for prediction was 95%. Interquartile range 25-75th percentile was calculated with the purpose of enhancing the accuracy of dataset statistics by dropping lower contributions. The median operation was calculated for each country and indicator for easier comparison. The data were anonymous and do not belong to individual citizens. According to the International Ethical Guidelines for Biomedical Research involving Humans and Good Clinical Practice Guidelines, a study like this does not require consideration by the Ethics Committee, as per the International Ethical Guidelines for Health-related Research Involving Humans accessed on 9 January 2023) and European Medicine Agency (Amsterdam, The Netherlands) accessed on 9 January 2023). 3. Results 3.1. Number of Medical Workers per 100,000 Inhabitants The number of general practitioners per 100,000 inhabitants had the highest median values in Latvia (71.5) and Serbia (71.4), while the lowest median value was in Belarus (8.7) . The regression analysis shows that in all observed countries there was an increase in this number, with the highest in Latvia (y = 2.4167x + 52.227; R2 = 0.95) and Ukraine; only in Albania (y = -0.9346x + 56.908; R2 = 0.0911) did we observe a decrease. North Macedonia and Lithuania did not have data on this indicator (Table 1). The number of general practitioners per 100,000 inhabitants is expected to increase by 2025, compared to the last available year, in 13 observed countries, the highest in Latvia by approximately 26; while in two countries, Romania and Bulgaria, a decrease in this number can be expected, by approximately 6 and 4.5 fewer, respectively, compared to the last available year. The number of pharmacists per 100,000 inhabitants had the highest median values in Greece (96/100,000) and Lithuania (63/100,000), while the lowest median values were in Ukraine (3) and Russia . The regression analysis shows that in 15 of the 17 observed countries, there was an increase in the number of pharmacists per 100,000 inhabitants; the highest in Croatia (y = 1.6326x + 31.777; R2 = 0.985) and Slovenia. The decline in the number of pharmacists was particularly observed in Bulgaria (y = -1.5415x + 28.358; R2 = 0.7519) and in Latvia (Table 2). The number of pharmacists per 100,000 inhabitants is expected to increase by 2025 in 13 observed countries, compared to the last observed year, and the largest increases can be expected in Romania and Greece. A decrease is expected in three countries, and the largest decreases are expected in Bulgaria and Albania. The number of health workers per 100,000 inhabitants had the highest median values in Greece (466) and Latvia (372), while the lowest median values were in Albania (128) and Turkey . The regression analysis shows that in 15 of the 17 observed countries, an increase in the number of health workers per 100,000 inhabitants occurred, and the highest increases were in Turkey (y = 3.5474x + 94.603; R2 = 0.9923) and Croatia. A decrease in the number of health workers was observed in Albania (y = -3.0557x + 152.14; R2 = 0.2289) and in Macedonia (Table 3). The number of medical workers per 100,000 inhabitants by 2025 is expected to increase in 15 observed countries, with the most in Greece by 189 compared to the last observed year. A decline can be expected in Russia, by 50% less compared to the last observed year, as well as in Albania. The highest median value of the indicator number of dentists working per 100,000 inhabitants in the observed period was observed in Bulgaria, with 82 per 100,000 inhabitants, as well as in Estonia, while the lowest median values were observed in Bosnia and Herzegovina, with 19 per 100,000 inhabitants . Regression analysis shows that there is a growing trend in the indicator of the number of dentists working per 100,000 in most observed countries, with the most pronounced growth occurring in Slovenia (y = 2.5453x + 54.943; R2 = 0.9631) and Romania. A downward trend is expected in three countries, with the most pronounced in Albania (y = -2.5801x + 53.951; R2 = 0.9068) (Table 4). The number of dentists working per 100,000 inhabitants will increase by 2025 in almost all observed countries, and the highest will be in Ukraine, by 32 more than in 2013. 3.2. Number of Medical Technologies Used in Health Services The highest median value of the total number of computerized tomography scanners per 100,000 inhabitants in the observed period was observed in Latvia and Bulgaria, with 3 per 100,000 inhabitants, while the lowest median value was observed in Romania, with 0.8 per 100,000 inhabitants . Regression analysis shows that there is a growing trend in the indicator of the total number of scanners for computed tomography per 100,000 inhabitants in 9 out of 10 observed countries, with the most pronounced growth occurring in Romania (y = 0.1152x - 0.0636; R2 = 0.9945) and Latvia. A downward trend is expected only in Slovenia (y = -0.0112x + 1.1727; R2 = 0.1119) (Table 5). The indicator of the total number of scanners for computed tomography per 100,000 inhabitants will increase by 2025 in 9 out of 10 observed countries, with the most in Latvia, by 1.9 more than in 2016. It is expected that by 2025, this indicator will decrease only in Slovenia, by 0.2 less compared to 2016. The highest median value of the total number of magnetic resonance units per 100,000 inhabitants in the observed period was observed in Greece, with 2.2 per 100,000 inhabitants, and Turkey, while the lowest median values were observed in Serbia and Croatia, with 0.3 per 100,000 inhabitants . Regression analysis shows that there is a growing trend in the indicator of the total number of magnetic resonance units per 100,000 inhabitants in 9 out of 10 observed countries, with the most pronounced growth occurring in Latvia (y = 0.1021x + 0.1864; R2 = 0.9743) and Romania. Only in Serbia is no change expected (Table 6). The indicator of the total number of magnetic resonance imaging units per 100,000 inhabitants will increase by 2025 in 9 of the 10 observed countries, and the highest in Lithuania, by 1 more than in 2016. It is expected that by 2025, this indicator will only remain the same in Serbia. 4. Discussion Population aging is correlated with the rise of medical costs, which is becoming an established issue not only in Eastern European and Balkan countries but worldwide . With numerous advances in technology, medicine and pharmaceuticals, people are living longer today than in previous decades, leading to increased healthcare costs . Our research shows increasing numbers of medical workers in most of the observed countries, which are desirable nowadays as population aging and chronic diseases are also rising. A few countries show opposite results, which may indicate a problem forming in less-developed countries. This negative trend will continue if these countries do not undertake better organization of their health systems. Countries without established health systems that recognize the needs of elderly people will eventually suffer from large expenditure in national and out-of-pocket expenses . Elderly people may suffer from two or more combined non-communicable diseases or undergo more surgical interventions, or laboratory analyses and various radiological imaging methods . Radiographs and computed tomography have an important role in many aspects of diagnosis and evaluation of pathologies, and CBCT is used widely in dental practice with a reduced radiation dose compared to classical CT . The usage and adaptation of new technologies is particularly challenging for many more developed countries as well, such as OEC countries. Research into the health economy recognizes CT and MRI as causes of increased medical expenditure, but on the other hand, they are also key technologies mostly used in different research in various fields of medicine and dentistry, so their accessibility may also indicate the better organization of health systems . He et al. found that macroeconomic and socio-economic indicators have a significant correlation with the allocation of scans used in radiology and also with several health professionals . Our research shows a growing trend over the observed time period in the number of CT scanners and MRI units in all observed countries, and our predictions show that this number per 100,000 inhabitants will continue to grow. Latvia and Bulgaria have the highest number of CT scanners and Greece has the highest number of MRI units. The number of medical workers, doctors, pharmacists and dentists is also increasing in all observed countries in our research, which indicates an increased investment in health by the state. It is also predicted that this growth trend will continue until 2025. According to the 2018 predictions of The Department of Health, the percentage of the workforce in primary healthcare must rise by almost 50% by 2031 to meet the demands and reforms of health services . Data about trends in those numbers are needed for the determination of the necessary capacity of health systems, because good planning without investigation is not possible . Public health services had to adapt to the many challenges during the COVID-19 pandemic, especially due to a lack of medical workers. One of the reasons why some countries, particularly less-developed countries, had this issue, is due to outflow to the larger and more developed countries . The number of dentists is expected to grow the most in Bulgaria, and most countries will increase their number of dentists per 100,000 inhabitants, with the exception of three countries according to the results of our research. The elderly population is a special group in the oral health sector because of their specific needs and therapy compared the younger people. The complexity of their dental therapy is additionally challenged by multiple co-morbidities . As with the outflow of medical professionals, the mobility of dental doctors is raising problems in many countries . Many studies have shown different factors that promote the mobility of medical workers in general; some of the main reasons are economy-related, such as searching for employment or higher salaries, but also, in the younger population, factors include higher education and improvement . Pharmacists are considered the healthcare profession that is the most accessible, and the capacity of pharmacists is related to economic indicators, whereby the countries with weaker economic indicators have less workforce availability, which is directly correlated with inequalities faced by different socio-economic groups . However, pharmacist workforce shortages have been reported in all sectors. It is highly recommended to follow the trends of this indicator globally for the future capacity of pharmacists. . Our research shows that the lowest median value of the number of pharmacists per 100,000 inhabitants were found in Ukraine and Russia. Looking at the linear trend, most countries showed positive trends in the number of pharmacists, and prediction values to 2025 also follow these results, with the exception of three observed countries, most noticeable in Bulgaria and Albania. Epidemiological transitions have a large impact on the health systems of countries, creating difficult challenges for healthcare providers . The burden of disease is shifted through the transition (in earlier periods, infectious diseases dictated how much the state would spend on health; now this role is filled by chronic non-infectious diseases--diseases of well-being) and this is the reason why the health system must adapt and integrate new technologies . A report about universal health coverage from the WHO presented large investments of nearly 10% of GDP on health, whereby average per capita spending is about USD 1000. . The largest percentage of these costs were related to medicaments, treatment of inpatients and outpatients, tests, and scans, thus relegating the importance of prevention and preventive programs to the background . 5. Conclusions Knowledge of changing trends in medical staff and medical technology is of crucial importance in the better re-composition of health sector needs. Universal health coverage is a main aim in the health sector of each country worldwide, which is hardly likely to succeed even with the best organization. Medical professionals are integral parts of every health organization, and with an insufficient number of workers, these aims would be even more unreachable. Additionally, new medical technology must follow the increasing trends and demands of the people in need of it. Government investments must follow the need for a higher number of medical workers. According to our research, there is mostly a positive trend in the number of medical workers and medical technology in the countries of Balkan and South-Eastern Europe, with a few exceptions where this trend is one of slow decrease. Following these indicators, the government and health sectors can focus on and navigate the best investments to influence the options for better health coverage in each country, with careful specification of the level of each country's development. The importance of observing different economic-related indicators is useful for different countries, and their analysis can be a reflection of the successful application of preventative measures. Assessing these trends and comparisons between countries may give valuable information about the organization of different health systems, and countries with a specific problem can adapt their health system accordingly. Author Contributions Conceptualization, M.S. and N.R.; methodology, M.S. and N.R.; software, S.V.; validation, R.V., S.R. (Snezana Radovanovic) and S.R. (Svetlana Radevic); formal analysis, K.J.; investigation, M.S.; resources, N.R.; data curation, N.R., S.V. and M.S.; writing--original draft preparation, M.S., K.J. and R.V.; writing--review and editing, S.R. (Svetlana Radevic), S.V., S.R. (Snezana Radovanovic) and N.R.; visualization, M.S.; supervision, N.R.; project administration, M.S., S.V. and K.J.; funding acquisition, N.R. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data sets used and/or analyzed in the present study are available on (accessed on 21 November 2022). Conflicts of Interest The authors declare no conflict of interest. Figure 1 Median values of indicators: (a) general practitioners, (b) pharmacists, (c) physicians, (d) practicing dentists, per 100,000 inhabitants. Albania--ALB, Bosnia and Herzegovina--BIH, Bulgaria--BGR, Greece--GRC, Croatia--HRV, Montenegro--MNE, Northern Macedonia--MKD, Romania--ROU, Serbia--SRB, Slovenia--SVN, Turkey--TUR, Russia--RUS, Belarus--BLR, Lithuania--LTU, Latvia--LVA, Estonia--EST, Ukraine--UKR. Figure 2 Median values of indicators: (a) total number of computed tomography scanners and (b) magnetic resonance imaging units per 100,000 inhabitants. Albania--ALB, Bosnia and Herzegovina--BIH, Bulgaria--BGR, Greece--GRC, Croatia--HRV, Montenegro--MNE, Northern Macedonia--MKD, Romania--ROU, Serbia--SRB, Slovenia--SVN, Turkey--TUR, Russia--RUS, Belarus--BLR, Lithuania--LTU, Latvia--LVA, Estonia--EST, Ukraine--UKR. healthcare-11-00655-t001_Table 1 Table 1 Values of the number of general practitioners per 100,000 inhabitants--value of the first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (1990-2000) Last Year (2014-2016) Prediction Median IQR Regression Analysis Albania 52.9 55.86 60.63 53 3.94 y = -0.9346x + 56.908; R2 = 0.0911 Bulgaria 67.6 62.84 58.43 65 4.37 y = 2.7521x + 34.728; R2 = 0.283 Bosnia and Herzegovina 11.49 19.72 31.90 15 7.32 y = 1.4859x - 0.0295; R2 = 0.8872 Belarus 6.33 9.24 20.29 9 2.42 y = 0.6631x - 3.1129; R2 = 0.6046 Greece 14.31 39.15 52.88 18 6.91 y = 2.3669x - 5.6518; R2 = 0.8642 Croatia 55.02 57 62.33 53 4.65 y = 5.1864x - 20.139; R2 = 0.7321 Montenegro 30.48 39.18 46.01 33 7.68 y = 3.2036x - 3.3379; R2 = 0.746 Romania 65.82 56.95 51.34 65 9.16 y = 4.7354x - 12.363; R2 = 0.4253 Russia 38.7 32.09 49.38 43 14.62 y = 0.7576x + 37.779; R2 = 0.2111 Serbia 68.82 70.71 77.48 71 4.75 y = 4.8411x + 17.998; R2 = 0.5384 Slovenia 38.18 51.5 67.17 43 7.37 y = 4.338x - 5.5783; R2 = 0.8044 Turkey 48.26 53.47 64.72 51 8.19 y = 0.9193x + 43.067; R2 = 0.8606 Estonia 68.87 71.8 86.64 70 5.34 y = 1.8208x + 51.784; R2 = 0.6143 Lithuania 67.24 89.14 115.37 72 19.98 y = 2.4167x + 52.227; R2 = 0.95 Ukraine 31.78 36.11 46.84 33 7.12 y = 0.8446x + 25.892; R2 = 0.932 healthcare-11-00655-t002_Table 2 Table 2 Values of the number of pharmacists per 100,000 inhabitants--value of the first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (1990-1994) Last Year (2014-2016) Prediction Median IQR Regression Analysis Albania 38 84 72 39 6 y = 0.5234x + 21.161; R2 = 0.0276 Bulgaria 36 17 0 22 11 y = -1.5415x + 28.358; R2 = 0.7519 Bosnia and Herzegovina 18 12 11 10 1 y = 0.4002x + 2.293; R2 = 0.3079 Belarus 34 34 35 31 4 y = 0.049x + 30.474; R2 = 0.0163 Greece 86 105 129 96 13 y = 6.1128x - 32.852; R2 = 0.7909 Croatia 36 71 90 52 18 y = 1.6326x + 31.777; R2 = 0.985 North Macedonia 21 45 62 18 19 y = 0.7059x + 14.216; R2 = 0.1491 Montenegro 17 17 15 16 2 y = 0.9668x - 5.4213; R2 = 0.7147 Romania 29 73 114 46 31 y = 3.0312x - 7.7631; R2 = 0.6437 Russia 2 5 6 6 1 y = 0.1491x + 3.3187; R2 = 0.378 Serbia 25 33 42 30 6 y = 1.9579x - 9.5945; R2 = 0.8164 Slovenia 34 60 78 47 16 y = 2.99x - 4.5248; R2 = 0.8709 Turkey 29 35 38 34 2 y = 0.2371x + 30.43; R2 = 0.7305 Estonia 53 68 76 59 9 y = 1.5993x + 34.126; R2 = 0.4133 Latvia 56 78 100 63 12 y = 4.2935x - 21.52; R2 = 0.8292 Lithuania 52 66 87 59 3 y = -1.9902x + 49.605; R2 = 0.2204 Ukraine 3 3 5 3 1 y = 0.2082x - 0.6699; R2 = 0.8304 healthcare-11-00655-t003_Table 3 Table 3 Values of the number of healthcare workers per 100,000 inhabitants--value of the first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (1990-2000) Last Year (2014-2016) Prediction Median IQR Regression Analysis Albania 147 128 116 128 10 y = -3.0557x + 152.14; R2 = 0.2289 Bulgaria 298 400 426 353 24 y = 3.1217x + 316.19; R2 = 0.8513 Bosnia and Herzegovina 156 188 223 157 28 y = 6.9955x + 12.747; R2 = 0.3806 Belarus 288 407 446 327 45 y = 4.5933x + 276.18; R2 = 0.9225 Greece 363 625 815 466 219 y = 13.422x + 320.17; R2 = 0.9517 Croatia 194 313 357 241 41 y = 4.7335x + 186.48; R2 = 0.967 North Macedonia 234 280 315 232 41 y = -0.4363x + 235.11; R2 = 0.0034 Montenegro 193 219 241 204 13 y = 12.61x - 72.457; R2 = 0.7484 Romania 188 236 293 216 41 y = 10.824x - 0.7556; R2 = 0.5072 Russia 225 331 280 237 7 y = 3.7004x + 183.78; R2 = 0.2451 Serbia 275 307 355 300 28 y = 18.965x - 89.172; R2 = 0.7849 Slovenia 219 276 301 236 26 y = 13.403x - 0.2986; R2 = 0.7342 Turkey 97 175 218 140 49 y = 3.5474x + 94.603; R2 = 0.9923 Estonia 354 332 340 321 14 y = 0.1548x + 320.25; R2 = 0.012 Latvia 361 322 348 294 31 y = 0.8818x + 288.77; R2 = 0.0841 Lithuania 358 433 455 372 22 y = 6.1806x + 288.31; R2 = 0.2928 Ukraine 300 300 382 308 49 y = 19.561x - 45.216; R2 = 0.7598 healthcare-11-00655-t004_Table 4 Table 4 Values of the number of dentists working per 100,000 inhabitants--value of the first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (1990-1999) Last Year (2016) Prediction Median IQR Regression Analysis Albania 33.93 34.59 0 40 8.27 y = -2.5801x + 53.951 R2 = 0.9068 Bulgaria 67.95 100.38 109.97 82 19.01 y = 7.0214x + 71.396 R2 = 0.8403 Bosnia and Herzegovina 31.44 21.08 26.94 19 3.01 y = 1.8061x + 15.872 R2 = 0.7331 Belarus 31.72 54.89 69.26 44 15.53 y = 5.7146x + 36.692 R2 = 0.8768 Croatia 43.35 75.78 80.89 68 11.13 y = 2.9356x + 64.89 R2 = 0.8937 Montenegro 41.13 4.02 0 41 28.75 y = -24.34x + 80.441 R2 = 0.8498 Romania 31.65 67 98.34 49 22.15 y = 14.54x + 18.098 R2 = 0.9328 Russia 26.95 29.22 28.58 29 1.94 y = -0.2971x + 30.108 R2 = 0.7027 Slovenia 59.06 64.93 68.43 60 2.10 y = 2.5453x + 54.943 R2 = 0.9631 Estonia 51.75 89.68 100.75 79 22.56 y = 5.2017x + 73.115 R2 = 0.8348 Latvia 55.24 90.54 115.01 67 14.43 y = 11.234x + 51.215 R2 = 0.8855 Ukraine 45.43 68.37 100.43 46 20.32 y = 13.211x + 25.66 R2 = 0.8721 healthcare-11-00655-t005_Table 5 Table 5 Indicator values of total number of scanners for computed tomography per 100,000 inhabitants--value of first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (2005) Last Year (2016) Prediction Median IQR Regression Analysis Bulgaria 1.6 3.5 5.2 3.0 1.4 y = 0.1892x + 1.5121 R2 = 0.9188 Estonia 0.7 1.8 2.6 1.6 0.6 y = 0.1049x + 0.8015 R2 = 0.7725 Greece 2.5 3.7 4.5 3.3 0.5 y = 0.1x + 2.5333 R2 = 0.9429 Croatia 1.6 1.8 1.8 1.6 0.2 y = 0.0129x + 1.48 R2 = 0.0643 Lithuania 1.2 2.3 3.5 1.9 1.1 y = 0.1294x + 0.9424 R2 = 0.8095 Latvia 1.8 3.6 5.5 3.0 1.4 y = 0.1962x + 1.55 R2 = 0.9615 Romania 0.3 1.3 2.4 0.8 0.7 y = 0.1152x - 0.0636 R2 = 0.9945 Slovenia 1 1 0.8 1.1 0.2 y = -0.0112x + 1.1727 R2 = 0.1119 Serbia 1.3 1.4 1.6 1.3 0.1 y = 0.03x + 1 R2 = 0.45 Turkey 0.7 1.5 2.0 1.3 0.4 y = 0.0671x + 0.7636 R2 = 0.8951 healthcare-11-00655-t006_Table 6 Table 6 Values of total number of magnetic resonance units per 100,000 inhabitants--value of the first observed year, last observed year, predictive value, median value, inter-incremental difference and linear regression analysis. Countries First Year (2005) Last Year (2016) Prediction Median IQR Regression Analysis Bulgaria 0.3 0.8 1.3 0.5 0.4 y = 0.0524x + 0.1758 R2 = 0.9008 Estonia 0.2 1.4 2.1 0.9 0.5 y = 0.0941x + 0.247 R2 = 0.9377 Greece 1.3 2.7 3.4 2.2 0.5 y = 0.0976x + 1.4742 R2 = 0.8353 Croatia 0.3 0.4 0.5 0.3 0.1 y = 0.0123x + 0.2234 R2 = 0.5033 Lithuania 0.2 1.2 2.2 0.6 0.8 y = 0.101x + 0.0348 R2 = 0.9305 Latvia 0.3 1.4 2.3 0.9 0.7 y = 0.1021x + 0.1864 R2 = 0.9743 Romania 0.1 0.6 1.1 0.4 0.3 y = 0.0576x - 0.1018 R2 = 0.9733 Slovenia 0.6 1.1 1.4 0.8 0.2 y = 0.0445x + 0.4882 R2 = 0.9095 Serbia 0.3 0.3 0.3 0.3 0 / Turkey 0.3 1.1 1.6 1.0 0.4 y = 0.0643x + 0.4152 R2 = 0.7927 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000487 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050822 cells-12-00822 Article Fermented Soybean Paste Attenuates Biogenic Amine-Induced Liver Damage in Obese Mice Yang Ju-Hwan 1 Byeon Eun-Hye 1 Kang Dawon 1 Hong Seong-Geun 1 Yang Jinsung 2 Kim Deok-Ryong 2 Yun Seung-Pil 3 Park Sang-Won 3 Kim Hyun-Joon 4 Huh Jae-Won 5 Kim So-Yong 6 Kim Young-Wan 7 Lee Dong-Kun 1* Kalyuzhny Alexander E. Academic Editor 1 Department of Physiology and Convergence Medical Science, Institute of Health Sciences, Gyeongsang National University Medical School, Jinju 52727, Republic of Korea 2 Department of Biochemistry and Convergence Medical Science, Institute of Health Sciences, Gyeongsang National University Medical School, Jinju 52727, Republic of Korea 3 Department of Pharmacology and Convergence Medical Science, Institute of Health Sciences, Gyeongsang National University Medical School, Jinju 52727, Republic of Korea 4 Department of Anatomy and Convergence Medical Science, Institute of Health Sciences, Gyeongsang National University Medical School, Jinju 52727, Republic of Korea 5 National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju 28116, Republic of Korea 6 Fermented and Processed Food Science Division, National Institute of Agricultural Sciences, Wanju-Gun 55365, Republic of Korea 7 Department of Food Science and Biotechnology, Korea University, Sejong 30019, Republic of Korea * Correspondence: [email protected] 06 3 2023 3 2023 12 5 82216 11 2022 28 2 2023 04 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Biogenic amines are cellular components produced by the decarboxylation of amino acids; however, excessive biogenic amine production causes adverse health problems. The relationship between hepatic damage and biogenic amine levels in nonalcoholic fatty liver disease (NAFLD) remains unclear. In this study, mice were fed a high-fat diet (HFD) for 10 weeks to induce obesity, presenting early-stage of NAFLD. We administered histamine (20 mg/kg) + tyramine (100 mg/kg) via oral gavage for 6 days to mice with HFD-induced early-stage NAFLD. The results showed that combined histamine and tyramine administration increased cleaved PARP-1 and IL-1b in the liver, as well as MAO-A, total MAO, CRP, and AST/ALT levels. In contrast, the survival rate decreased in HFD-induced NAFLD mice. Treatment with manufactured or traditional fermented soybean paste decreased biogenically elevated hepatic cleaved PARP-1 and IL-1b expression and blood plasma MAO-A, CRP, and AST/ALT levels in HFD-induced NAFLD mice. Additionally, the biogenic amine-induced reduction in survival rate was alleviated by fermented soybean paste in HFD-induced NAFLD mice. These results show that biogenic amine-induced liver damage can be exacerbated by obesity and may adversely affect life conservation. However, fermented soybean paste can reduce biogenic amine-induced liver damage in NAFLD mice. These results suggest a beneficial effect of fermented soybean paste on biogenic amine-induced liver damage and provide a new research perspective on the relationship between biogenic amines and obesity. biogenic amine obesity liver NAFLD IL-1b MAO National Research Foundation of Korea2020R1I1A306867013 2021R1A4A302712212 Korea Research Institute of Bioscience and Biotechnology Research Initiative ProgramKGM4562222 Research Program for Agricultural Science & Technology Development and the National Institute of Agricultural SciencePJ013833 This study was supported by grants from the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (2020R1I1A306867013 and 2021R1A4A302712212); the Korea Research Institute of Bioscience and Biotechnology Research Initiative Program (KGM4562222); and the Research Program for Agricultural Science & Technology Development and the National Institute of Agricultural Sciences (PJ013833), Rural Development Administration, Republic of Korea. pmc1. Introduction Biogenic amines are biologically activated low-molecular-weight nitrogenous organic compounds that are primarily produced by spoilage microorganisms mediating the enzymatic decarboxylation of amino acids. Representative biogenic amines include the aliphatic compounds putrescine, cadaverine, agmatine, spermine, and spermidine; the aromatic compounds tyramine and 2-phenylethylamine; and the heterocyclic compounds histamine and tryptamine. Although the toxicity of small amounts of biogenic amines is negligible, consuming large amounts of aromatic and heterocyclic compounds in food can be hazardous and cause serious health problems . Unlike the fermentation process occurring under certain conditions and in certain environments, food decomposition results in the elevation of biogenic amine levels in foods. A high concentration of biogenic amines can adversely affect the nervous and vascular systems and may cause physiologically harmful reactions or intoxication . Furthermore, biogenic amines ingested in large quantities from foods can enter the systemic circulation and consequently cause migraine, elevation of blood sugar levels, high blood pressure, Parkinson's disease, schizophrenia, and depression . In particular, histamine, a representative biogenic amine present in most foods, can cause histamine and scombrid poisoning if consumed in large amounts. Additionally, tyramine is as common as histamine and is abundant in various foods, including strong/aged cheeses, aged/smoked meats, wine, and avocados . Similar to histamine, high levels of tyramine intake can have adverse health effects . Additionally, the association effect of histamine and tyramine shows synergistic cytotoxicity in intestinal cells . In general, small amounts of ingested biogenic amines from foods are physiologically metabolized and converted to less active forms via the detoxifying enzymes monoamine oxidase (MAO) and diamine oxidase (DAO) . The mitochondrial enzyme MAO has two isoforms (MAO-A and -B) that are widely expressed in various organs, including the brain, heart, lungs, kidney, intestine, and liver . MAO plays a physiologically important role in the metabolism of monoaminergic neurotransmitters in the central nervous system and biogenic amines in peripheral tissues . Tyramine is a well-known substrate for MAO-A and causes hypertension and even death when combined with MAO inhibitors . Furthermore, histamine is metabolized in the liver and eliminated from the blood after it becomes inactive . Because DAO is rarely expressed in the livers of most species, histamine N-methyltransferase, instead of DAO, converts histamine to N-methylhistamine in the liver and is then metabolized by MAO-B . In several studies, MAO activity has been used to estimate the levels of biogenic amines, especially histamine and tyramine . Therefore, MAO activity can be expected to be essential in reducing biogenic amines in vivo. However, there is insufficient evidence to establish a correlation between biogenic amines and hepatic MAO activity. Obesity, which has been increasing worldwide for decades, causes various health problems, such as metabolic disorders. Excessive fat accumulation induced by obesity causes metabolic diseases, such as type 2 diabetes mellitus (T2DM). Obesity contributes to the development of fatty liver, leading to nonalcoholic fatty liver disease (NAFLD) . Recent studies suggest that T2DM is a critical risk factor for NAFLD development . Several studies have also demonstrated that chronic and progressive fatty liver conditions caused by obesity can lead to advanced fibrosis, cirrhosis, hepatocellular carcinoma, and liver-related death . Additionally, the interleukin 1 (IL-1) family of cytokines plays a pivotal role in NAFLD development. For instance, IL-1a and -1b promote fatty liver disease processes, including liver steatosis, hepatic damage, liver fibrosis, and the recruitment of immune cells induced by inflammation through IL-1 receptor signaling . Although there is evidence for the deleterious effect of histamine and tyramine on the liver, the adverse risk of the relationship between NAFLD and biogenic amines has not been established. Recent studies have documented that soybean-derived foods such as fermented soybean paste contain various beneficial components. The long-term ingestion of fermented soybean paste prevents high-fat diet (HFD)-induced metabolic disorders, including NAFLD and insulin resistance. Consequently, it lowers the incidence of T2DM . Therefore, the aim of this study was to demonstrate increased hepatic damage caused by biogenic amines and the therapeutic role of fermented soybean paste after exposure to biogenic amines in HFD-induced NAFLD. 2. Materials and Methods 2.1. Animal Experiments All experimental and animal care protocols were approved by the Gyeongsang National University Institutional Animal Care and Use Committee (GNU IACUC, GNU-200820-M0053) and performed following the National Institute of Health (NIH) guidelines and a scientifically reviewed protocol (GLA-100917-M0093). C57BL/6 mice were used in these experiments. The mice were fed a high-fat (60%) diet (Research Diets, Inc., New Brunswick, NJ, USA) for 10 weeks after weaning to induce NAFLD. 2.2. Preparation of Fermented Soybean Paste Powder The fermented soybean paste powder used in the animal experiments was selected based on the National Health and Nutrition Survey of the Ministry of Health and Welfare of Korea. It was collected from 15 types of traditionally fermented soybean paste and two types of factory-made products. After grinding, the fermented soybean paste samples were quantified using a sterilized container. Then, 1000 g of each of 15 types of traditional fermented soybean paste were mixed to produce a standard sample of 15 kg. Two factory-made fermented soybean pastes (7.5 kg each) were mixed to make a standard sample of 15 kg. Each sample was freeze-dried for 5 days, then pulverized. The prepared soybean paste powder was stored at -20 degC. Residual biogenic amines were not removed from the samples. 2.3. Measurement of Body Weight, Food Intake and Survival Rate Mice were randomly assigned and fed either a normal chow diet (NCD) or an HFD containing 10% or 60% fat (Research Diets, Inc., New Brunswick, NJ, USA) for 10 weeks. Mouse body weights were measured daily during oral gavage administration. The food and water intake of the mice was measured at 12 h intervals during the last day of the experiment from 7 pm to 7 am and from 7 am to 7 pm. The survival/mortality of the mice was recorded after 6 days of oral gavage administration of drugs. 2.4. Drug Administration Drugs for oral gavage administration, including histamine (histamine dihydrochloride, TCI, Tokyo, Japan) and tyramine (Cayman Chemical, Ann Arbor, MI, USA), were dissolved in 0.5% carboxymethylcellulose (CMC, Sigma-Aldrich, St. Louis, MO, USA). The soybean paste powder was administered orally (75 or 750 mg/kg) with histamine and tyramine. A total volume of 0.5% CMC was treated to avoid exceeding the recommended dose for mice (10 mL/kg). 2.5. ELISA Assay Blood samples were collected from the hearts and stored in ethylene glycol tetra-acetic acid-coated tubes (Becton, Dickinson and Company, Franklin Lakes, NJ, USA). The blood samples were centrifuged at 3000 rpm for 10 min at 4 degC, and each sample's supernatant (blood plasma) was collected. This process was performed twice to obtain clear blood plasma samples. The collected blood plasma was immediately used for the ELISA assay to avoid degradation effects on the results. The total MAO, MAO-A, -B, bile acids, and C-reactive protein (CRP) levels in blood plasma were determined using OxiSelected MONOAMINE OXIDASE ASSAY KIT (Cell Biolabs, Inc., San Diego, CA, USA), Mouse Total Bile Acids Kit, and Mouse C-Reactive Protein ELISA Kit (Crystal Chem, Elk Grove Village, IL, USA) according to the manufacturers' instructions. The absorbance of the samples was measured using a Versamax microplate reader (Molecular Devices, LLC., San Jose, CA, USA). The blood concentration of each protein was calculated according to the manufacturer's instructions. 2.6. Plasma Biochemical Assays The blood samples were collected following the protocol described in the ELISA Assay section. Plasma aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were measured using dedicated kits (IVD Lab, Uiwang, Republic of Korea) and a spectrophotometer (Shimadzu UV-1800 spectrophotometer, Tokyo, Japan). 2.7. Western Immunoblotting Isolated liver samples were homogenized in RIPA buffer (Thermo Scientific, Rockford, IL, USA) on ice for 30 min and centrifuged twice at 13,000 rpm for 30 min at 4 degC. The concentrations of solubilized proteins in the supernatants were determined using a BCA protein assay (Thermo Scientific). Proteins in supernatants (10 mg) were separated using 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The separated proteins were transferred to a methanol-activated polyvinylidene difluoride membrane (Merck, Darmstadt, Germany). The membrane was blocked with a blocking buffer containing 5% skim milk in a mixture of Tris-buffered saline and 0.1% Tween-20 and washed three times for 10 min. Membranes were then probed with either a primary rabbit antiserum against IL-1b (1:1000, Abcam, Cambridge, MA, USA) or osteopontin (1:1000) (Abcam, Cambridge, MA, USA) or PARP-1 (1:1000, Cell Signaling Technology, Danvers, MA, USA) for 18 h at 4 degC, rewashed three times, and incubated with horseradish peroxidase-labeled goat anti-rabbit secondary antiserum (1:3000) (Thermo Fisher Scientific, Tewksbury, MA, USA) for 1 h at room temperature. Immunoreactive protein bands were detected using an iBright Western blot imaging system (Thermo Scientific, Tewksbury, MA, USA) with enhanced chemiluminescence reagents (Ab Frontier, Seoul, Republic of Korea; ratio of reagents A to B = 1:500). The same membrane was stripped and probed with mouse primary antiserum against b-actin (1:1000) (Sigma-Aldrich, St. Louis, MO, USA) to normalize the blots. Immunoreactive protein bands were semiquantified using a digital imaging camera and NIH Image 1.62 software. 2.8. IPGTT After 16 h of fasting, glucose solution (2 mg/kg, i.p.) was administered to the mice. Blood glucose levels were measured at 0, 30, 60, 90, and 120 min using a glucose meter (MEDISENSOR, Daegu, Republic of Korea). A blood sample was collected from the tail vein of the mouse, and the first drop of blood was discarded. The area under the curve from the IPGTT was calculated using the trapezoidal rule. 2.9. Statistics Statistical analyses were performed using one-way analysis of variance with Tukey's multiple comparison test (GraphPad Prism 9.3.1, GraphPad Software, La Jolla, CA, USA). Data were considered significantly different when the p-value was <0.05. All statistical results are presented as mean +- SEM. 3. Results 3.1. Changes in Survival Rate and Plasma CRP Levels after Repeated Exposure to Combined Biogenic Amines in Mice Fed an NCD The mice were administered combined biogenic amines once a day for 6 days by oral gavage to determine the adverse effects of biogenic amines, histamine, and tyramine under NCD-fed conditions . The combined biogenic amine administration was determined at three concentration levels--low (2 mg/kg histamine + 10 mg/kg tyramine, n = 12), medium (20 mg/kg histamine + 100 mg/kg tyramine, n = 12), and high concentration (200 mg/kg histamine + 1000 mg/kg tyramine, n = 12)--and 0.5% CMC without biogenic amines was used as a control (n = 12). Three concentration levels of combined biogenic amines were used--low (2 mg/kg histamine + 10 mg/kg tyramine, n = 12), medium (20 mg/kg histamine + 100 mg/kg tyramine, n = 12), and high concentration (200 mg/kg histamine + 1000 mg/kg tyramine, n = 12)--and CMC (0.5%) without biogenic amines was used as a control (n = 12). Body weight and food intake (but not water intake) were significantly reduced after treatment with high concentrations of biogenic amines . However, medium and low concentrations of combined biogenic amines did not affect body weight and food intake. The survival rate of mice was 100% (n = 26) in the CMC control group but decreased to 91.7% (1 death out of a total of 12 mice) in the low-concentration group, 84.6% (2 deaths out of a total of 13 mice) in the medium-concentration group, and 46.2% (7 deaths out of a total of 13 mice) in the high-concentration administration group. Subsequently, to determine the adverse effects of biogenic amines on liver damage, we tested changes in CRP levels in blood plasma, a marker protein produced by hepatocytes and associated with NAFLD and inflammation . Blood plasma CRP levels were significantly increased in the medium- (42.7 +- 7.9 ng/mL, n = 10) and high-concentration (52.3 +- 9.7 ng/mL, n = 13) groups but not in the group administered a low concentration (24.3 +- 0.9 ng/mL, n = 15) of biogenic amines compared with the control group (14.2 +- 2.1 ng/mL, n = 9) . Therefore, the optimal dose for combined biogenic amine administration was determined to be a medium concentration, which increased CRP levels without affecting feeding behavior and survival. When histamine and tyramine were administered alone, there was no change in the survival rate of the experimental animals; however, the blood plasma CRP level increased significantly after tyramine was administered alone . 3.2. Changes in Liver IL-1b Expression Levels after Repeated Exposure to Biogenic Amines in Mice Fed an NCD Recent studies demonstrate that IL-1b cytokine is closely associated with inflammation, hepatic injury, and obesity . Osteopontin is also a potential biomarker for numerous liver diseases . Therefore, we investigated whether biogenic amines affect the expression levels of IL-1b and osteopontin in the mouse liver. Administration of histamine or tyramine alone did not change the liver expression levels of IL-1b, but the levels were increased by combined biogenic amine administration in the liver (NCD + CMC: n = 6; NCD + histamine 20 mg/kg: n = 6, NCD + tyramine 100 mg/kg: n = 6; NCD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 6) . Osteopontin expression levels in the mouse liver also showed an increasing tendency with biogenic amine administration, but the difference was not statistically significant (NCD + CMC: n = 6; NCD + histamine 20 mg/kg: n = 6, NCD + tyramine 100 mg/kg: n = 5; NCD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 6) . Therefore, in subsequent experiments, we used IL-1b as a marker to evaluate the effects of biogenic amines and hepatic damage in HFD-induced obesity. The full-length whole Western blot images for Figure 2 are shown in Figure A1. 3.3. Establishment of HFD-Induced NAFLD to Elucidate Biogenic Amine-Induced Liver Damage in Obesity Leptin resistance is defined by a reduced sensitivity or a failure in brain response to leptin. Decreased tissue sensitivity to leptin leads to obesity and is closely linked to insulin insensitivity . Furthermore, leptin indicates a predisposition to metabolic disorders, including fatty liver diseases . Therefore, preliminary monitoring of leptin resistance is necessary to evaluate the effect of biogenic amines on obesity and NAFLD development. A previous study reported that C57BL/6 mice fed an HFD for 10 weeks showed symptoms of NAFLD . Therefore, all mice used in our experiment were fed an HFD for 10 weeks to establish NAFLD. Mice fed an HFD (n = 12) showed decreased glucose tolerance compared to the NCD-fed group (n = 11) . Additionally, fasting plasma glucose and plasma leptin levels were increased in HFD-fed mice for 10 weeks . These data demonstrate that HFD-induced obese mice developed leptin resistance. These results demonstrate that this method establishes a model suitable for evaluating liver damage caused by biogenic amines in NAFLD. 3.4. Changes in Survival Rate and Liver Damage Markers after Single or Combined Biogenic Amine Administration in HFD-Induced Developmental NAFLD To determine the effect of biogenic amines on the liver of HFD-induced obese mice, we tested the survival rate of experimental mice, IL-1b expression levels in the liver tissue, and blood CRP levels after oral gavage administration of biogenic amines. Survival rates were reduced after administration of both biogenic amine alone and a mixture of biogenic amines (CMC: 0 deaths out of 9, 100%; histamine 20 mg/kg: 1 death out of 13, 92%; tyramine 100 mg/kg: 2 deaths out of 12, 83%; histamine 20 mg/kg + tyramine 100 mg/kg: 7 deaths out of 33, 79%) . Consistent with this result, liver IL-1b levels increased after biogenic amine treatment (HFD + CMC: n = 6; HFD + histamine 20 mg/kg: n = 7; HFD + tyramine 100 mg/kg: n = 7; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 6) . Additionally, the survival rate was slightly lower in the HFD-fed group compared to the NCD-fed group (from 85% to 79%) . Blood CRP levels were significantly increased in both CMC (n = 8) and biogenic amine-administered groups (n = 11) after HFD was fed compared to the NCD-fed, CMC-treated group (n = 9) . As biogenic amines are degraded by the biogenic amine-detoxifying enzyme MAO , we determined whether biogenic amines alter liver MAO levels after HFD-induced NAFLD. Liver MAO-A and total MAO levels were significantly increased by repeated combined biogenic amine administration compared to the NCD control group, but MAO-B levels did not change (NCD + CMC: n = 6; HFD + CMC: n = 6; HFD + histamine 20 mg/kg: n = 6; HFD + tyramine 100 mg/kg: n = 7; HFD + histamine 20 mg/kg + tyramine 100 mg/ kg: n = 6) . Although bile acids are derived from hepatic cholesterol catabolism and are closely associated with NAFLD development , repeated administration of combined biogenic amines did not change the total bile acid levels in the blood plasma (NCD + CMC: n = 6; HFD + CMC: n = 10; HFD + histamine 20 mg/kg: n = 10; HFD + tyramine 100 mg/kg: n = 10; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 11) . These results demonstrate that even in the early stages of NAFLD, ingested biogenic amines may be associated with fatty liver conditions and induce severe risks linked to death via excessive response to MAO. The full-length whole Western blot images corresponding Figure 4B are shown in Figure A2. 3.5. Fermented Soybean Paste Affects Changes in Survival after Combined Biogenic Amine Administration in HFD-Induced Developmental NAFLD To determine the effect of fermented soybean pastes on biogenically induced liver damage in HFD-induced NAFLD, traditionally made fermented soybean paste (TSBP) and manufactured (factory-made) fermented soybean paste (MSBP) feeding were combined with biogenic amines. The decreased survival rate after combined biogenic amine administration was increased by both TSBP (HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 75 mg/kg: 1 death out of 9, 89%; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 750 mg/kg: 0 deaths out of 10, 100%) and MSBP (HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 75 mg/kg: 0 deaths out of 9, 100%; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 750 mg/kg: 0 deaths out of 9, 100%) in the early stage of NAFLD . We also evaluated blood aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels to determine liver damage by biogenic amines in developmental NAFLD. As shown in Figure 5C,D, combined biogenic amines induced increased levels of ALT (HFD + CMC: n = 4; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 75 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 750 mg/kg: n = 4; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 75 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 750 mg/kg: n = 6), and AST levels (HFD + CMC: n = 4; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 75 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 750 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 75 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 750 mg/kg: n = 5) were decreased by TBST and MSBP administration for 6 days. These data suggest that both TSBP and MSBP may be involved in reducing biogenic amine-induced toxic effects associated with developmental NAFLD. 3.6. Effects of Fermented Soybean Paste on Changes in Liver Damage Markers after Combined Biogenic Amine Administration in HFD-Induced Developmental NAFLD We evaluated changes in liver damage markers to determine whether fermented soybean paste reduces biogenic amine-induced liver damage in HFD-induced NAFLD. Combined biogenic amine-elevated hepatic IL-1b expression levels in developmental NAFLD were significantly decreased by both TSBP and MSBP . We also evaluated changes in cleaved PARP-1, known as a cellular stress sensor, in developmental NAFLD. As shown in Figure 6B, biogenic amine-induced cleaved PARP-1 expression levels were significantly decreased by both TSBP and MSBP (n = 6 per group). Additionally, blood CRP levels and biogenic amines upregulated by HFD were significantly downregulated by fermented soybean paste (NCD + CMC: n = 6; HFD + CMC: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 11; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 75 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 750 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/ kg + MSBP 75 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg + MSBP 750 mg/kg: n = 6) . In particular, HFD and biogenic amine-induced enhanced activity of MAO-A levels was reduced by the high dose of MSBP, while MAO-B and total MAO levels did not change in the liver (NCD + CMC: n = 6; HFD + CMC: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 75 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + TSBP 750 mg/kg: n = 6; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 75 mg/kg: n = 5; HFD + histamine 20 mg/kg + tyramine 100 mg/kg + MSBP 750 mg/kg: n = 6) . These results support the hypothesis that fermented soybean paste reduces biogenic amine-enhanced hepatic damage in developmental NAFLD. The full-length whole Western blot images corresponding to Figure 6A,B are shown in Figure A3 and Figure A4, respectively. 4. Discussion Although we are constantly exposed to the risk of biogenic amines by ingesting food with high protein or free amino acid contents, the relationship between biogenic amines and obesity-induced metabolic diseases remains elusive. Biogenic amines generated from fermentation decomposition by microorganisms or biochemical activity, including that histamine, tyramine, agmatine, putrescine, cadaverine, spermine, and spermidine, are not only toxic but also act as a measure of the freshness of food and spoilage . Aliphatic biogenic amines are commonly used as a decay indicator. Aromatic and heterocyclic compounds act as 'vasoactive amines', causing toxicity by stimulating the nervous and vascular systems when consumed in excess . The results of the present study show that ingesting large amounts of concomitant histamine and tyramine can induce life-threatening health problems. For instance, repeated exposure to combined biogenic amines decreased the food intake, survival rate, and body weight of NCD-fed mice. Additionally, repeated exposure to combined biogenic amines increased blood CRP levels in a dose-dependent manner. Immunoreactivity of the hepatic damage marker IL-1b, a well-known indicator of liver damage , was increased by the combined administration of biogenic amines. In particular, blood CRP levels increased only in HFD-induced NAFLD. Combined biogenic amine administration increased hepatic IL-1b levels in NAFLD. In contrast, survival rates were decreased by combined biogenic amine administration under normal conditions and showed a tendency to further reduce the survival rate in NAFLD mice. As IL-1b is closely associated with obesity and inflammatory fatty liver disease , HFD-induced NAFLD may be a factor in enhancing the risk of biogenic amines. IL-1b expression levels were increased, but developmental liver damage and the fibrogenesis marker osteopontin did not change. Therefore, these data suggest that the interaction between obesity-related NAFLD and unexpected ingestion of a large amount of biogenic amines may exacerbate hepatic function directly related to the maintenance of life. The main risk factors for developing NAFLD are obesity, T2DM, and other factors associated with metabolic syndrome . In general, NAFLD is induced by long-term HFD exposure, although a recent study reported that NAFLD symptoms appeared when after 10 weeks on an HFD . However, the relationship between obesity factors and biogenic amines in the early stages of fatty liver disease is unclear. We monitored glucose and leptin levels as indicators of obesity due to the provision of HFD for 10 weeks. Glucose and leptin levels in blood plasma were significantly increased by 10 weeks of HFD feeding compared to those in the NCD-fed group . Therefore, we used this as a model for developmental NAFLD because HFD-mediated metabolic processes involved in leptin resistance accelerate de novo lipogenesis, inflammation, and fibrogenesis in the liver and consequently cause NAFLD . Several studies have shown that IL-1b and CRP are strong predictors of NAFLD . Hepatic IL-1b expression and blood CRP concentration were increased in the HFD-induced NAFLD group after combined biogenic amine administration compared with HFD + CMC and NCD + CMC groups . Similarly, the survival rate of the combined biogenic amine-treated group was lower that of the control group. CRP is produced by hepatocytes and is involved in chronic liver disease. Recent studies have shown that high CRP levels have been observed in patients with liver dysfunction . In particular, patients with liver cancer or cirrhosis with high CRP levels show poor prognoses . Additionally, IL-1b plays a critical role in hepatic failure via NF-kB signaling and proinflammatory cytokine activation . These findings suggest that obesity may interact with repeated conjugated biogenic amine administration to cause liver damage via IL-1b and/or CRP upregulation. It has been documented that NAFLD is closely associated with the upregulated activity of MAO-A in the liver, which is associated with oxidative stress-mediated depressive symptoms . In addition, MAO inhibitors can potentially decrease the gene and protein expression of the proinflammatory cytokines IL-1b, IL-6, TNF-a, and INF-g . Consistent with these findings, we found that hepatic MAO-A, total MAO levels, and IL-1b expression increased after combined biogenic amine administration in HFD-fed NAFLD mice, while blood bile acid levels did not change significantly. Although the changes in MAO-B levels were not significant, they did show an increasing trend. Therefore, these findings suggest that hepatic MAO-A and IL-1b may act as more helpful markers than total bile acid when evaluating the risk of biogenic amine-induced liver damage in obese mice. In addition, recent studies demonstrated that cleavage of PARP-1, as a necrotic cell death marker, is closely associated with NAFLD and oxidated stress-induced liver damage . Interestingly, fermented soybean paste recovered the survival rate reduced by biogenic amines in NAFLD . Usually, hepatic steatosis due to NAFLD causes increased ALT and AST levels . Since plasma ALT and AST levels are known indicators of hepatocyte damage, they are used as general clinical biomarkers to evaluate liver function . As shown in Figure 5, it was confirmed that increased blood ALT and AST levels by combined biogenic amine treatment were decreased in the MSBP-treated groups of NAFLD mice. Biogenic amine-induced increased IL-1b, cleaved PARP-1 expression levels, and blood CRP were decreased by concomitant administration of fermented soybean paste in NAFLD . Additionally, fermented soybean paste reduced biogenic amine-enhanced hepatic MAO-A activity, but MAO-B and total MAO activities did not change . These findings suggest that fermented soybean paste may relieve hepatic damage by reducing MAO, IL-1b, and cleaved PARP-1 levels increased by biogenic amines in HFD-induced developmental NAFLD. Several studies have reported that fermented soybeans provide various benefits, including antioxidative, anti-inflammatory, fibrinolytic, anticancer, and immune-enhancing effects . These benefits are known to be caused by isoflavones or secondary metabolites produced by microorganisms involved in the fermentation process . Although decarboxylase-containing microorganisms produce biogenic amines during soybean paste fermentation, certain microorganisms, such as lactic acid bacteria and amine oxidase gene-containing bacteria, reduce biogenic amines . Among the microbes, Pediococcus acidilactici M28 and Staphylococcus carnosus M43, which are contained in Chinese soybean paste, can degrade biogenic amines, especially tyramine and histamine . Additionally, Staphylococcus is one a dominant microbe in fermented Korean soybean paste . Therefore, it is feasible that fermented soybean paste can reduce biogenic amine-mediated liver damage in NAFLD patients. However, the detoxification mechanism of biogenic amines by certain microorganisms remains unclear but may occur in a hepatic MAO-independent manner . Controlling spoilage microorganisms during fermentation is challenging because the production method varies from household to household and region to region. In contrast, systematically produced MSBP may have a constant amount or concentration of beneficial bacteria containing amine oxidase. Therefore, MSBP may be more effective in improving the liver damage caused by NAFLD biogenic amines. In this study, we did not investigate the effects of biogenic amines produced in soybean paste or the adverse effect of other biogenic amines except for histamine and tyramine. Nevertheless, recent studies demonstrate that the microbial community of soybean paste is involved in the degradation of other biogenic amines in addition to histamine and tyramine . Although the precise mechanism of the beneficial effect of fermented soybean pastes on biogenic amine-induced liver damage remains unclear, our data suggest that fermented soybean pastes may contribute to a reduction in biogenic amine-induced liver damage in NAFLD. 5. Conclusions We identified an increased risk of hepatic dysfunction by biogenic amine ingestion in obesity and confirmed that both blood and liver biomarkers, including CRP, MAO, IL-1b, and PARP-1, are helpful markers for evaluating hepatic function in biogenic amine-induced liver damage in obesity. Although there is insufficient documentation of the complementary benefits of soybean paste and the increased risk of biogenic amines in obesity, we propose that fermented soybean paste is a promising candidate to alleviate liver damage caused by biogenic amines in NAFLD. Acknowledgments We thank Na Hyeon Park and Eun A Kim for preparing and helping with the experimental procedures. Author Contributions Conceptualization, J.-H.Y., S.-Y.K., Y.-W.K. and D.-K.L.; methodology, D.K., S.-G.H. and J.Y.; validation, D.-R.K., S.-P.Y., S.-W.P. and H.-J.K.; formal analysis, J.-H.Y., E.-H.B. and D.-K.L.; investigation, J.-H.Y., E.-H.B. and D.-K.L.; resources, S.-Y.K.; writing--original draft preparation, J.-H.Y. and D.-K.L.; writing--review and editing, J.-H.Y. and D.-K.L.; supervision, D.-K.L.; project administration, S.-Y.K. and D.-K.L.; funding acquisition, S.-Y.K., Y.-W.K., J.-W.H., S.-P.Y. and D.-K.L. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All experimental and animal care protocols were approved by the Gyeongsang National University Institution Animal Care and Use Committee (GNU IACUC, GNU-200820-M0053) and performed in accordance with the National Institutes of Health (NIH) guidelines and with a scientifically reviewed protocol (GLA-100917-M0093). Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors report no conflict of interest. Appendix A Figure A1 The full-length and whole Western blot images corresponding to Figure 2. (A) IL-1b. (B) b-actin for IL-1b. (C) Osteopontin. (D) b-actin for osteopontin. The arrows indicate the appropriate molecular weight of each protein. Figure A2 The full-length Western blot images corresponding to Figure 4B. (A) IL-1b. (B) b-actin for IL-1b. The arrows indicate the appropriate molecular weight of each protein. Figure A3 The full-length Western blot images corresponding to Figure 6A. (A) IL-1b. (B) b-actin for IL-1b. The arrows indicate the appropriate molecular weight of each protein. Figure A4 The full-length Western blot images corresponding to Figure 6B. (A) PARP-1. (B) b-actin for PARP-1. The arrows indicate the appropriate molecular weight of each protein. Figure 1 Combined effect of biogenic amines administered by repeated oral gavage in mice fed a normal chow diet (NCD). (A) Timeline of repeated oral gavage administrations of biogenic amines. Changes in body weight (B), food intake (C), and water intake (D) after repeated oral gavage administrations of biogenic amines. (E) Changes in survival rate after repeated oral gavage administrations of biogenic amines by concentration. (F) Changes in plasma C-reactive protein (CRP) levels after repeated oral gavage administrations of biogenic amines by concentration. (G) Changes in survival rate following repeated oral gavage administration of histamine and tyramine. (H) Changes in plasma CRP levels after repeated oral gavage administrations of either histamine or tyramine. * p < 0.05, ** p < 0.01 vs. carboxymethylcellulose (CMC). Data are shown as mean +- SEM. BA, biogenic amine; His, histamine; Tyr, tyramine. Figure 2 Effect of administration of single biogenic amines or their mixture on liver damage markers in mice fed an NCD. (A) Changes in IL-1b expression levels after repeated oral gavage administrations of histamine, tyramine, and combined biogenic amines. (B) Osteopontin expression levels changed after oral gavage administrations of histamine, tyramine, and combined biogenic amines. * p < 0.05 vs. CMC. Data are shown as mean +- SEM. IL-1b, interleukin-1 beta. Figure 3 Establishing an HFD-induced NAFLD mice model by evaluating leptin resistance. (A) Intraperitoneal glucose tolerance test to evaluate leptin resistance after 10 weeks of feeding mice either an NCD or HFD. (B) The area under the curve corresponding to Figure 3A. (C) Fasting plasma glucose levels. (D) Plasma leptin levels. *** p < 0.001, **** p < 0.0001 vs. CMC. Data are shown as mean +- SEM. Figure 4 Effect of biogenic amines on liver damage in mice fed an HFD. (A) Changes in survival rate following single or repeated oral gavage administrations of biogenic amines after feeding an HFD. (B) Changes in IL-1b following single or repeated oral gavage administrations of biogenic amines after feeding an HFD. (C) Comparison of changes in survival rate between HFD-fed groups after repeated oral gavage administrations of biogenic amines. (D) Comparison of changes in blood CRP levels between NCD-fed, HFD-fed, and HFD-fed + biogenic amines administration groups. Changes in liver MAO-A (E), MAO-B (F), total MAO (G) levels, and total bile acid levels in the blood (H). * p < 0.05, *** p < 0.001, **** p < 0.0001 vs. NCD + CMC. Data are shown as mean +- SEM. MAO, monoamine oxidase. Figure 5 Reduction in biogenic amine-induced toxic effects by fermented soybean paste in obesity. (A) Effect of TSBP on survival rate changes caused by biogenic amine administrations and HFD-induced obesity. (B) Effect of MSBP on survival rate changes caused by biogenic amine administrations and HFD-induced obesity. (C) Changes in blood AST and (D) ALT levels caused by biogenic amines and fermented soybean paste in HFD-induced obesity. * p < 0.05, *** p < 0.001 vs. HFD + CMC; # p < 0.05, ## p < 0.01 vs. HFD + histamine 20 mg/kg + tyramine 100 mg/kg. Data are shown as mean +- SEM. TSBP, traditionally made fermented soybean paste; MSBP, manufactured fermented soybean paste. Figure 6 Reduction in biogenic amine-induced hepatic damage by fermented soybean paste in developmental NAFLD. (A) Changes in IL-1b expression levels by biogenic amines and fermented soybean paste in HFD-induced NAFLD liver tissue. (B) Changes in cleaved PARP-1 expression levels caused by biogenic amines and fermented soybean paste in HFD-induced NAFLD liver tissue. (C) Changes in blood CRP levels caused by biogenic amines and fermented soybean paste in HFD-induced NAFLD. Changes in MAO-A (D), MAO-B (E), and total MAO (F) levels caused by biogenic amines and fermented soybean paste in HFD-induced NAFLD liver tissue. * p < 0.05, **** p < 0.0001, vs. NCD + CMC; # p < 0.05, ## p < 0.01, ### p < 0.001, #### p < 0.0001, vs. HFD + histamine 20 mg/kg + tyramine 100 mg/kg. Data are shown as mean +- SEM. Figure 7 Putative role of fermented soybean paste extract in biogenic amine-induced hepatic damage in NAFLD. A large amount of combined biogenic amine ingestion may exacerbate hepatic function by increasing IL-1b expression, although activation of MAO degrades biogenic amines in NAFLD. In addition, biogenic amines enhance the cleavage of PARP-1, which may be upregulated by fatty liver disease. However, fermented soybean paste extracts are probably involved in the degradation of biogenic amines, reducing biogenic amine-induced hepatic damage in NAFLD. 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PMC10000488 | There is a great deal of controversy in the hematologic community regarding the classification of secondary myelodysplastic neoplasms (MDSs). Current classifications are based on the presence of genetic predisposition and MDS post-cytotoxic therapy (MDS-pCT) etiologies. However, since these risk factors are not exclusive for secondary MDSs and there are multiple overlapping scenarios, a comprehensive and definitive classification is yet to come. In addition, a sporadic MDS might arise after a primary tumor fulfills the diagnostic criteria of MDS-pCT without a causative cytotoxicity. In this review, we describe the triggering pieces of a secondary MDS jigsaw: previous cytotoxic therapy, germline predisposition and clonal hematopoiesis. Epidemiological and translational efforts are needed to put these pieces together and ascertain the real weight of each of these pieces in each MDS patient. Future classifications must contribute to understanding the role of secondary MDS jigsaw pieces in different concomitant or independent clinical scenarios associated with the primary tumor. myelodysplastic neoplasms (MDSs) secondary MDS genetic predisposition therapy-related myeloid neoplasm (TRMN) MDS post-cytotoxic therapy (MDS-pCT) MDS comorbidity clonal hematopoiesis of indeterminate potential (CHIP) Instituto de Salud Carlos III, Ministerio de Economia y CompetividadPI/17/0575 PI19/00374 PI 20/00531 PI22/00102 TRANSCANAECC AC 18/000002 ISCIII Generalitat de Catalunya2017 SGR288 (GRC) SGR00560 (GRC) This research was funded by the Instituto de Salud Carlos III, Ministerio de Economia y Competividad, grant numbers PI/17/0575, PI19/00374, PI 20/00531 and PI22/00102; TRANSCAN, grant numbers AECC AC 18/000002 and ISCIII; and Generalitat de Catalunya, grant numbers 2017 SGR288 (GRC) and SGR00560 (GRC). pmc1. Introduction Myelodysplastic syndromes or, as renamed in the latest World Health Organization (WHO) classification , myelodysplastic neoplasms (MDSs) are an age-associated malignant condition characterized by ineffective hematopoiesis, which entails a variety of prognostic biomarkers and heterogeneous outcomes due to their diverse etiology and the risk factors involved . However, the landscape of the risk factors driving different MDS etiologies is not fully understood. Previous studies reported both obesity and smoking as modifiable risk factors of MDSs . Furthermore, exposure to cytotoxic therapies , genetic predisposition or the presence of clonal hematopoiesis of indeterminate potential (CHIP) have been described as risk factors for this pathology. The development of a secondary myelodysplasia is benign and often reversible if the offending trigger is withdrawn . In Vienna, in 2006, the Myelodysplastic Neoplasm Working Group conference consolidated the two prerequisite criteria for the diagnosis of MDSs: the presence of cytopenia and the absence of other hematopoietic or nonhematopoietic disorders as the etiology of cytopenia . Further contributing to the confusion, the term secondary myelodysplasia was also being used to refer to MDS evolving secondarily from a previous myeloid neoplasm or to define diseases that progressed from another myeloid disease. However, in the last WHO classification, the transformation of a myeloproliferative neoplasm (MPN) to acute myeloid leukemia (AML) was retained under the MPN category, while the transformation of MDS to AML and MDS/MPN remains under AML-myelodysplasia-related (AML-MR), in the secondary myeloid neoplasm category . In very early reports, Jens Pedersen-Bjergaard first described secondary myeloid neoplasms in the study on "Acute Nonlymphocytic Leukemia, Preleukemia, and Acute Myeloproliferative Syndrome Secondary to Treatment of Other Malignant Diseases", in which among 31 patients, 21 "pre-leukemia" cases predominated. The term "secondary MDS" was first used in "Proposals for the classification of the myelodysplastic syndromes", in which the FAB group addressed the "Special features of Secondary MDS", describing a more frequent presence of fibrosis, hypocellularity, ringed sideroblasts, a higher proportion of blasts in the peripheral blood (PB) than would be expected from the percentage in the bone marrow (BM) and abnormal and immature megakaryocyte precursors often seen in PB and BM . Using sequential cytogenetics, Rowley and colleagues demonstrated in 1980 that the development of MDS after exposure to mutagens and carcinogens was related to chromosomal evolution towards complex karyotypes (-5/del(5q), -7, +8, +21) and cytological transition into acute leukemia . 2. The Pieces of the Jigsaw 2.1. MDS Post-Cytotoxic Therapy MDS post-cytotoxic therapy (MDS-pCT) cases are aggressive hematologic malignant neoplasms. The incidence of these neoplasms is rare (<0.5 per 100,000), but the mortality rates are higher compared to primary MDS, with a 5-year survival rate of 10% vs. 31% in primary MDS, and a median survival of around 8-10 months . The diagnosis of MDS-pCT requires fulfilment of the criteria for MDS in addition to a previous history of chemotherapy treatment or large-field radiation therapy for an unrelated neoplasm . Both incidental and therapeutic radiation have been associated with MDS-pCT. Indeed, a significant linear radiation dose-response for MDS has been described in atomic bomb survivors 40 to 60 years after radiation exposure . In the cancer setting, a study of patients receiving radiation therapy showed a higher risk of developing MDS than in those who did not . Nevertheless, the conclusions of studies in specific cancer series are not very uniform, with conflicting data in relation to breast cancer, Hodgkin lymphoma and radiation as part of myeloablative regimens before hematopoietic stem cell transplantation . It has been estimated that 10% of patients with non-Hodgkin lymphoma , 8.2% of patients with chronic lymphocytic leukemia and 3.4% of patients with multiple myeloma (MM) develop MDS-pCT . Cytogenetic abnormalities are detectable in almost 90% of MDS-pCT patients , while altered karyotypes are reported in 40-50% of patients with de novo MDS . Likewise, while high-risk forms with a poor prognosis are prevalent in the 46-70% of MDS-pCT patients , they are only reported in 30% of patients with de novo MDS . However, the same cytogenetic abnormalities are found in both groups of patients, who were undistinguishable at the karyotype level (Table 1). On the other hand, the latency period for the appearance of MDS-pCT after treatment substantially varies depending on the type of primary cancer and the treatment regimen . This is well known for drugs used for long periods in anticancer schedules. Treatment with alkylating agents has been associated with longer latency times, adverse cytogenetics with a high frequency of complex karyotypes and a poor prognosis . Regarding cytogenetics, the most common clonal abnormalities include the partial or total loss of chromosomes 5 and 7 and complex karyotypes after treatment with alkylating agents . The development of MDS-pCT after receiving anthracyclines and/or topoisomerase II inhibitors is associated with a median latency of 1 to 3 years and an MLL translocation at 11q23 or RUNX1/AML1 at 21q22 and a low frequency of complex karyotypes (Table 1). Exposure to PARP1 inhibitors is another criterion for the development of MN-pCT . Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are active in cells with impaired ability to repair DNA double-strand breaks, such as cancer cells with mutations in the tumor suppressors BRCA1 or BRCA2, and have been used in subsets of patients with ovarian, breast, prostate and pancreatic cancer . During the last 2 years, several reports have identified patients with MDS and AML following PARPi therapy . Common findings include a median latency of 2 years after the initiation of PARPi treatment, complex karyotypes, the presence of germline damage response gene variants and the acquisition of TP53 mutations . Interestingly, one of these studies reported how clonal hematopoiesis was more common in patients with ovarian cancer receiving PARPi maintenance therapy than in those not receiving this treatment, showing expansion in paired specimens post-therapy . On the other hand, immunomodulatory drugs were introduced for treating MM in the late 90s, leading to significantly improved overall survival. During the following decade, lenalidomide replaced thalidomide as the most used immunomodulatory drug for MM due to its higher efficacy and lower toxicity. Several clinical trials have found significantly higher rates of secondary myeloid neoplasms in lenalidomide-treated arms than in those without lenalidomide in relapsed/refractory, transplant-eligible and transplant ineligible MM patients . A definitive role for lenalidomide in the development of a secondary myeloid neoplasm after therapy for MM cannot be established in many cases since patients often receive high-dose chemotherapy during their initial treatment. However, a recent systematic analysis of 416 patients with MN-pCT and a detailed prior history of exposure found that TP53 mutations were significantly associated with previous treatment with thalidomide analogs, specifically lenalidomide. They also showed that lenalidomide treatment provides a selective advantage over TP53 (Trp53 in mice)-mutant murine hematopoietic stem and progenitor cells (HSPCs) in vitro and in vivo, and that the effect was specific to Trp53-mutant HSPCs and was not observed in HSPCs with other clonal hematopoiesis mutations . A recent systematic review and meta-analysis found that lenalidomide-induced later sporadic malignancies seem to occur exclusively in patients with MM, and no significant increase was described in chronic lymphocytic leukemia and MDS trials . Scarce information has been published regarding prognostic models or associations between MDS-pCT and concrete clinical outcomes and progression . In addition, there are no clinical management guidelines for the appropriate monitoring of these patients, since there are no accurate diagnostic criteria that consider all etiologic factors involved in the development of MDS-pCT, thereby hampering the exploration of targeted therapies. An important clue when identifying the different etiologies in secondary MDS relies on the fact that the somatic signatures in MDS-pCT are indistinguishable from those occurring in de novo MDS , which would hide the incidence of the treatment effect in MDS development . Only TP53 mutations were found to be enriched in MDS-pCT patients, while spliceosome mutations are more frequent in de novo MDS, which might partially explain the complex karyotype and unfavourable clinical outcomes of MDS-pCT patients . Likewise, mutations in the PPM1D gene, a negative regulator of the DNA damage response pathway, are also frequent in MDS-pCT patients, as they confer a competitive advantage under the selective pressure of chemotherapy . 2.2. Germline Predisposition Over the last decade, large-scale genomic studies have described the landscape of genomic variants in many of the most relevant types of cancer with the initial and fundamental objective of providing prognostic, diagnostic and pathogenic information based on the acquired alterations detected. However, the co-assessment of germ tissue in these series has transformed the understanding of how inherited variants influence cancer development . Within myeloid neoplasms, it was estimated that 5% to 10% of patients with AML carried germline variants predisposing them to myeloid neoplasia . In MDS, it has been estimated that germline mutations could explain at least 15% of adult and pediatric MDS cases . In specific contexts, such as adolescents with MDS and monosomy of chromosome 7, this percentage could reach up to 70% . The identification of clinical features and molecular biomarkers linked to this entity is important since its clinical management differs from sporadic MDS . To this end, several guidelines for myeloid neoplasms with a germline predisposition have been described to identify these patients . A growing number of inherited genetic loci that contribute to MDS has been identified . The SAMD9, SAMD9L, SRP72, TERC and TERT genes, together with other genes typically mutated in sporadic MDS, such as TP53, GATA2, DDX41, ANKRD26, ETV6, CEBPA, ASXL1 and RUNX1, have been associated with the germline development of the disease . Different correlations have been established among germline mutations, the age of onset and the severity of the myeloid neoplasm . Furthermore, several hereditary syndromes have also been associated with MDS development . These MDSs arise within the genetic landscape that predisposes patients to multiple tumors . Several diseases, such as Fanconi Anemia, Severe Congenital Neutropenia, Dyskeratosis Congenita or Blackfan-Diamond Anemia present with bone marrow failure triggering MDS . Although a particular karyotype has not been described in most germline-predisposed MDSs, in the context of inherited bone marrow failure (BMF) syndromes, recurrent chromosomal findings have been described, including duplications of chromosome regions 1q or 3q in Fanconi Anemia, isochromosome 7q in Shwachman-Diamond Syndrome, or isolated monosomy 7 common in GATA2 haploinsufficiency, among others (Table 1). 2.3. Clonal Hematopoiesis Finally, the presence of clonal hematopoiesis has been observed to increase with age and actively participates in the development of myeloid neoplasms . Clonal hematopoiesis of indeterminate potential (CHIP) is defined as the presence of clonal mutations in genes recurrently mutated in myeloid neoplasms in peripheral blood of healthy individuals at a low frequency . The incidence of CHIP has been associated with a higher risk of developing hematologic malignant neoplasms with adverse outcomes . Altered clones not only harbor genetic alterations but also numerical and structural chromosomal changes, including those found in hematopoietic malignancies, such as del(20q), del(13q), del(11q), trisomy 8 or less commonly, del(5q) or del(7q) (Table 1). CHIP has recently been described as a risk factor for developing secondary cardiovascular diseases . 2.4. Current Classifications and Secondary MDS In light of the different risk factors entailing different outcomes, the identification of risk factors must be concise for differential diagnosis and adequate clinical management . However, identification of different overlapping factors in relation with the development of MDS in a patient with a previous primary tumor is challenging. This hematologic condition is considered a secondary MDS, but an efficient consensus risk factor-based classification has yet to be established. The WHO first classified MDS occurring following cytotoxic therapy for a primary tumor as MDS-pCT independently of MDS associated with a germline predisposition . The latest update of the WHO classification (2022) proposes considering the entity of secondary myeloid neoplasms, which encompass the MDSs that arise from previous exposition to cytotoxic therapy or immune intervention (MDS-pCT), as well as MDS that occurs within the context of a syndromic germline . These separate subentities do not consider other risk factors or the overlapping of both conditions (MDS-pCT and germline predisposition). On the other hand, the recent International Consensus Classification (2022) maintains the therapy-related myeloid neoplasm (TRMN) category as an entity . Nevertheless, this update clarifies that TRMN should be subclassified according to its morphology and genetics, as risk factors, such as CHIP or clonal cytopenia, can occur after exposure to cytotoxic treatment. In addition, this proposal also suggests that the presence of an underlying germline condition must be explored, considering a possible relocation to germline mutation-associated disorders either as syndromes when the genetic origin is common between the two tumors or as having different molecular drivers. Both classifications are based on fitting, including two delimited etiologies for secondary MDS, based on therapy toxicity and genetic predisposition . However, this two independent etiology-based classification does not consider the genetic predisposition aside from syndromic MDSs, excluding multiple overlapping etiologies and scenarios that share the same clinical appearance. The relative contribution of risk factors, such as germline predisposition or the presence of CHIP, in the development of MDS-pCT have not yet been fully explored. Thus, genetic predisposition might increase the susceptibility to cytotoxic agents. The treatment of a primary tumor may affect bone marrow cells differently depending on the presence of mutations affecting the DNA damage repair system. In this sense, it has been described that between 16 and 21% of cancer survivors who developed MDS-pCT had a germline mutation associated with inherited cancer susceptibility genes . Several studies have reported germline mutations in BRCA1, BRCA2, PALB2, CHEK2 and TP53 and Fanconi Anemia genes in MDS-pCT patients . Similarly, recent studies showed that cancer therapy shapes the fitness landscape of clonal hematopoiesis by promoting the onset or the increment of cytopenia and clonal dysplasia, such as idiopathic cytopenia of undetermined significance (ICUS), clonal cytopenia of undetermined significance (CCUS), idiopathic dysplasia of unknown significance (IDUS) or CHIP . CHIP was higher than expected according to age in patients with MDS-pCT at the time of diagnosis of the primary tumor and before treatment . According to recent studies, it is estimated that 30% of patients with MDS-pCT have CHIP . CHIP was detected in 66% of MDS-pCT patients previously treated for gynecologic and breast cancers, including mutations in TP53 (31%), DNMT3A (19%), IDH1/2 (13%), NRAS (13%), TET2 (12%), NPM1 (10%), PPM1D (9%) and PTPN11 (9%) . Since CHIP is frequently observed in patients with MDS-pCT at the time of diagnosis of the primary tumor, it has been suggested as a predictive marker to identify patients at risk to preclude the administration of treatments that might trigger the development of MDS-pCT . In addition to these overlapping scenarios, both primary and secondary tumors might not be associated with any risk factor and do not occur concomitantly. Current therapeutic strategies have reduced the mortality among cancer patients, with an increase in survival rates entailing an increased frequency of age-dependent secondary pathologies with no relationship with the primary tumor. Thus, both tumors might arise independently or from different risk factors. The MDSs of these patients would have no relationship with the cytotoxic therapy of the primary tumor or a common genetic origin (syndrome), but they mimic the clinical definition of a secondary MDS. 3. Discussion: How to Put the Jigsaw Pieces Together With a few exceptions, the cytogenetic abnormalities and molecular similarities between secondary MDSs of different etiologies hamper adequate classification of differential diagnoses (Table 1). Furthermore, only a few studies with low number of patients have evaluated the proportion of altered karyotypes within the etiologies of CHIP and genetic risk factors within the context of secondary MDS (Table 1). Thus, the debate regarding the classification of secondary MDS is apparently going to continue during the coming years. The current classifications consider separate etiologies based on risk factors and cytotoxic therapy to describe either secondary MDS or TRMN . Nevertheless, recent studies regarding the germline landscape and CHIP condition in MDS-pCT patients support the contention that these different etiologies must be considered as overlapping . Thus, genetic predisposition must be considered beyond bone marrow syndromes . Likewise, CHIP may be initiated, expanded or triggered by cytotoxic therapy ; however, both CHIP and treatment for the primary tumor could also coexist with no association. In addition, different mutational burdens and their correlation with CHIP-related mutations are different for different hematological malignancies . Thus, different MDS subtypes may be expected in different combinations of cytotoxic effects together with an individual genetic landscape and CHIP mutations. We foresee future classifications of secondary MDSs assessing all risk factors and their interactions for a better assessment of the etiology of the cancer. Therefore, overlapping risk factors (CHIP and germline predisposition), together with the cytotoxic therapy effect, would result in the clinical definition of different concomitant scenarios, including a single or variety of responsible risk factors. Finally, clinical scenarios in which both tumors are independent or do not share risk factors must be considered as they mimic the clinical manifestation of secondary MDS but must be identified to prevent background noise. Therefore, we suggest the following scenarios . (a) Concomitant tumors are related to secondary MDS when it involves the etiology of the primary tumor: (a.1) MDS-pCT disease; the hematologic disease arises through exposure to a cytotoxic therapy when treating a primary tumor. Treatment might do the following:solely contribute to MDS without other known risk factors; trigger CHIP or drive an increase in CHIP; contribute depending on germline predisposition or susceptibility; contribute together with CHIP and the germline landscape. (a.2) Syndrome; secondary MDS arises from a common genetic origin together with the first tumor. (b) Independent tumors mimic the clinical appearance of the previous scenarios but do not share risk factors:Sporadic, correlative tumors with no shared risk factors; MDS-pCT-like, in which cytotoxic therapy does not participate in the development of a secondary myeloid tumor. Secondary MDS occurs with germline predisposition, in which a primary tumor might also have a genetic predisposition but is not common with that of the MDS. 4. Conclusions and Future Directions In summary, the role of risk factors in the different etiologies of MDS scenarios is still unclear. Furthermore, the classification of the etiologies of MDS becomes even more challenging when it occurs in a patient with a previous primary tumor. The first step to understand the molecular pathophysiology and the role of risk factors in different secondary MDSs is to have an adequate classification even with no prognostic biomarkers or molecular descriptions. Current classifications are based on etiologies related to well-delimited risk factors and cytotoxic therapy. However, the current knowledge regarding the biology of hematological malignancies supports the integration of genetic predisposition and CHIP into future MDS-pCT classifications to reflect the biological diversity and etiologies of MDS-pCT and their impact on outcomes. Thus, future classifications must consider the concomitance of single and overlapping risk factors, as well as independence regarding the relationship between primary and secondary tumors. Deciphering the contribution of risk factors in combination with cytotoxic treatments will allow for the differential diagnoses of patients at risk to aid in routine clinical decision-making at the translational level to provide adequate clinical management. In addition, understanding the pathologic mechanisms underlying different etiologies will improve the development of prognostic biomarkers and therapy-oriented guidance of primary tumors for patients at risk of developing secondary MDS and will also help in genetic counseling related to the suitability of hematopoietic progenitor cell transplants (HPTs) from a related donor. Author Contributions O.C., F.S., J.M. and A.J. wrote, reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Secondary myelodysplastic neoplasm (MDS) jigsaw pieces. (A) Current classifications based on delimited etiologies for secondary MDS arising from cytotoxic treatment or risk factors (genetic predisposition and clonal hematopoiesis of indeterminate potential, CHIP). MDS post-cytotoxic therapy (MDS-pCT) or therapy-related myeloid neoplasm (TRMN) were secondary MDSs arising from treatment effects with no overlap with other risk factors. (B) New classification approach. Both cytotoxic treatment and the presence of an underlying germline or CHIP conditions are overlapping etiologies and compose different susceptibility scenarios. The different contribution of several risk factors might participate in the development of MDS-pCT. Thus, treatment might promote or increase CHIP, while genetic predisposition might modulate the effect of cytotoxic therapy. Figure 2 Classification of secondary MDS. The risk factors involved in different etiologies are shown for the primary tumor and secondary MDS. Risk factors in white circles refer to mandatory conditions per the scenario described. Risk factors in grey circles refer to non-strictly necessary overlapping conditions co-occurring with the mandatory condition. The timeline shows the chronology of tumor events. The expected time of onset is shown for secondary MDS. Early onset is expected when MDS involves genetic predisposition. (A) Current classifications are based on well-delimited risk factors (genetic predisposition, CHIP or cytotoxic treatment). New classification approaches must consider the overlap between risk factors that compose different susceptibility scenarios of independent and concomitant tumors. (B) Independence: both tumors are independent when they do not share risk factors (sporadic) or even when the treatment of the first tumor is not related to the development of MDS (MDS-pCT-like). In addition, the primary tumor and secondary MDS might arise from a strong but not shared genetic predisposition. (C) Concomitancy is considered when secondary MDS arises in relation to the etiology of the first tumor. Typically, secondary MDS with germline predisposition within a syndromic scenario arises from genetic predisposition in common with that of the first tumor. MDS-pCT arises from exposure to a cytotoxic therapy for treating the primary tumor. The relative contribution of risk factors, such as germline predisposition or the presence of CHIP, might contribute to the development of MDS-pCT. Treatment might promote or increase CHIP, while genetic predisposition might modulate the cytotoxic effect. cancers-15-01483-t001_Table 1 Table 1 Chromosome alterations associated with MDS with different etiologies. Karyotype Genetic Risk Factors CHIP De Novo MDS MDS-pCT Altered karyotypes Not described 21% 40-60% 70-90% Complex karyotypes * Not described Not described 30% 46-70% Most frequent unique alterations dup(1q), 3q+, -7/del(7q), i(17)(q10), +8, +21, del(20q), del(11q) del(20q), del(13q), del(11q), +8, del(5q), del(17p) del(5q), -7/del(7q), +8, -Y Post-alkylating agents: -7, del(7q), del(5q), -5 Topoisomerase II inhibidors: t(11;21)(q23;q22), t(15;17), inv(16)(p13q22), t(17;19)(q22;q12) Most frequent complex karyotypes Not described Not described del(5q), -7/del(7q), -18/-18q (7%), +8, -20q. Other: +1/+1q, -5, +11, -13/13q-, -17/17p-, -21, +mar -5/del(5q), -7/del(7q) Other: der(21q), +8, der(12q), t(1;7), -12, der(17q), der(3q), der(3q), and -18 * Three or more cytogenetic alterations. MDS: myelodysplastic neoplasm; CHIP: clonal hematopoiesis of indeterminate potential; MDS-pCT: MDS post-cytotoxic therapy. 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PMC10000489 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13051004 diagnostics-13-01004 Review Clinical Characteristics and Current Status of Treatment for Recurrent Bladder Cancer after Surgeries on Upper Tract Urothelial Carcinoma Hu Xinfeng Xue Yufan Zhu Guodong * Rosser Charles Academic Editor Furuya Hideki Academic Editor Ku Ja Hyeon Academic Editor Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China; [email protected] (X.H.); [email protected] (Y.X.) * Correspondence: [email protected]; Tel.: +86-029-8532-3940 06 3 2023 3 2023 13 5 100419 1 2023 08 2 2023 02 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Upper tract urothelial carcinoma (UTUC) is a relatively rare, but highly malignant, disease with an estimated annual incidence of 2 cases per 100,000 people. The main surgical treatment modalities for UTUC are radical nephroureterectomy (RNU) with bladder cuff resection. After surgery, intravesical recurrence (IVR) can occur in up to 47% of patients, and 75% of them present with non-muscle invasive bladder cancer (NMIBC). However, there are few studies focused on the diagnosis and treatment of postoperatively recurrent bladder cancer for patients with previous UTUC history (UTUC-BC), and many of the influencing factors are still controversial. In this article, we performed a narrative review of the recent literature, mainly summarizing the factors influencing postoperative IVR in patients with UTUC and discussing the subsequent prevention, monitoring, and treatment tools for it. upper tract urothelial carcinoma intravesical recurrence non-muscle invasive bladder cancer risk factor treatment Fundamental Research Funds for the Central Universities of Chinaxjj2018zyts34 Research Funds on Social Development from the Department of Science and Technology of Shaanxi Province of China2020SF-119 The Fundamental Research Funds for the Central Universities of China (No. xjj2018zyts34) and the Research Funds on Social Development from the Department of Science and Technology of Shaanxi Province of China (No. 2020SF-119) to Guodong Zhu are acknowledged. pmc1. Clonogenic Correlation and Tumor Implantation Theory It remains controversial whether upper tract urothelial carcinoma (UTUC), and subsequently, urinary bladder cancer (BC) are of clonally related or separate origins. Several studies in recent years have supported a clonal origin with intratumoral implantation. According to Fadl et al., the presence of related clones with high karyotypic similarity in anatomically distinct tumors from the same bladder suggests that multifocal urothelial tumors have a monoclonal origin and arise by intraluminal inoculation of living cancer cells shed from the original tumor . There is a tendency for UTUC to recur around the cystostomy tube wall or within the bladder neck where the urethral duct is damaged, which further supports the hypothesis that cancer cells floating in the bladder may primarily adhere to the injured urethra and recur through intraluminal inoculation . Habuchi and colleagues found that upper urinary tract and bladder tumors from the same patient consistently exhibited the same distinct p53 mutation. Doeveren et al. systematically reviewed the available relevant literature on the possible clonal relationship between UTUC and BC, and they suggested that 94% of primary UTUC and intravesical recurrences (IVR) are clonally related . To further investigate the clonal relationship between the two entities, Audenet F et al. investigated the genes from UTUC and the specific recurrent BC tissue specimens from 29 patients by using somatic mutation data to study their clonal correlation. It was found that all the UTUC and BC pairs were considered to have similar clonal origins (p < 0.005) . Additionally, Doeveren et al. performed a targeted DNA sequencing technique on a panel including 41 genes, and the results showed that 73.3% of patients with paired UTUC and BC exhibited the same clonal relationship. Aside from that, the sample they took were from patients who had been diagnosed with primary urothelial carcinoma of the upper urinary tract, and subsequently diagnosed with urothelial carcinoma of the bladder, and this approach more accurately reflects the natural course of patients with UTUC after surgical treatment. This result supported the hypothesis that recurrent BC was primarily a clonally derived recurrence after the primary surgical resection of UTUC, rather than a separate entity. During the follow-up, three patients in their cohort developed multiple recurrent BCs, which were all associated with primary UTUC, and thus, provide further support for the possible mechanism of the tumor cells seeding theory . Based on the clonal origin, there was 80% concordance between the tumor grading of primary UTUC and recurrent BC in up to 90% of cases . However, in contrast to grading, the pathological stage of UTUC was poorly correlated with that of recurrent BC (UTUC-BC). In the study by Raman and colleagues, 92% of bladder recurrences in patients with superficial or invasive UTUC were of superficial bladder cancer , and almost all the UTUC-BCs tended to be superficial tumors independent of the stage of the primary UTUC tumors . 2. Comparison of the Characteristics of Recurrent and Primary BC Currently, the disease management of patients with IVR after radical nephroureterectomy (RNU) for UTUC (UTUC-BC) is based on the primary BC guidelines. For non-muscle invasive bladder cancer (NMIBC), the transurethral resection of bladder tumor (TUR-BT) remains the initial management option. However, according to a large population-based survey by Wu et al. , the baseline characteristics of the two patient's cohorts with recurrent BC after UTUC (UTUC-BC) and patients with primary BC were so different that the treatment guidelines for patients with primary BC were not fully applicable to the patients with UTUC-BC. For the UTUC-BC patients' cohort, the majority of the patients were white (88.0%), male (58.7%), with a lower proportion of females (41.3%) and those with an earlier TNM stage. The median age of the patients with IVR was 72.07 years old, and the median BC tumor size was 24.36 mm. Compared to UTUC-BC patients, primary BC patients were more likely to be male (76.7%), with a larger median tumor size (34.84 mm) and earlier TNM stages (p < 0.001). The primary sites of tumor location were significantly different between the UTUC-BC and primary BC patients (p < 0.001), with the most common sites for UTUC-BC being the lateral wall and bladder neck, mostly presenting as NMIBC , while the primary BC patients were more likely to have tumors in the trigone of the bladder. For primary UTUC lesions in patients with UTUC-BC, the highest proportion of patients had renal pelvic carcinoma (74.7%), grade III/IV (67.6%), and stage N0 (91.0%). The BC seems to be more difficult to treat than UTUC-BC does in terms of size and staging, but Miyake M et al. found that UTUC-BC had a worse prognosis with bacillus calmette-guerin (BCG) instillation in the bladder compared to that of primary BC, suggesting that these recurrent tumors inherently respond poorly to BCG . Meanwhile, Shigeta K et al. also observed that the fibroblast growth factor receptor 3 (FGFR3) level was significantly lower in primary MIBC patients than it was in UTUC-BC patients (including NMIBC and MIBC, p < 0.01). In contrast, MIBC specimens (including IVR and primary BC) showed a higher expression of P53 levels than those of IVR of NMIBC specimens (p = 0.03 and 0.04, respectively) . Increased expression of FGFR3 and P53 is frequently associated with tumor cell generation and progression, thus UTUC-BC might have characteristics such as being more aggressive in terms of growth and invasion. Interestingly, one study conducted by Wu et al., who investigated the prognosis of patients with BC, found that the cancer-specific survival (CSS) of UTUC-BC patients was not significantly different from the CSS of primary BC patients . However, the CSS of the former group (11.4%) was significantly higher than that of the latter group (0.7%). Due to the impact of UTUC, the overall prognosis of UTUC-BC patients was worse than that of primary BC patients. The median survival times for UTUC-BC patients and primary BC patients were 54 and 97 months, respectively (p < 0.001). For the type of NMIBC, the median survival rates were 67 and 112 months for UTUC-BC and primary BC patients, respectively (p < 0.001) . More importantly, the results demonstrated that neither radical cystectomy nor TUR-BT could provide a significant survival benefit for patients with UTUC-BC compared to that of the patients with primary BC who received the same surgical treatment. The study by Yates et al. indicated significant differences in the genetic and epigenetic background between the patients with UTUC-BC and primary BC , and these differences might be one of the factors that could result in the different treatment effects for the two patient cohorts with the same treatment strategy. Meanwhile, Makito et al. identified that patients with UTUC were more likely to develop IVR NMIBC after receiving intravesical BCG instillation compared with the likelihood of patients with primary NMIBC after matching UTUC-BC and primary NMIBC patients according to their propensity scores . This was consistent with other existing studies and suggested that while BCG was currently one of the most effective intravesical agents for preventing recurrence of NMIBC, its role in disease progression still remained controversial. 3. Risk Factors Affecting Recurrent BC The main surgical treatment modalities for UTUC are radical nephroureterectomy (RNU) with bladder cuff resection . Patients with UTUC have a higher risk of tumor recurrence after receiving surgery, such as recurrence in the bladder and local or distant metastasis, which can be as high as 47%, 18%, and 17%, respectively . Of the patients who experienced intravesical recurrence (IVR) during follow-up, 75% presented with non-muscle invasive bladder cancer (NMIBC), which was confined in the mucosa (Ta, CIS) or submucosa (T1) of the bladder wall . Therefore, exploring the risk factors affecting the postoperative IVR for patients with UTUC is essential for subsequent monitoring and treatment. However, not all patients with UTUC are suitable for the risk factor assessment. For example, some studies have shown that when UTUC tumors are first diagnosed, 60% of them are aggressive, and nearly 25% of them are regionally metastatic . Aggressive and late-staged tumors might indicate difficulties during the treatment with a poor prognosis, and they also represent a higher possibility for metastasis. For UTUC that is aggressive, the 5 year specific survival rate is <50% for patients with pT2/pT3 staging and <10% for those with pT4 staging . Therefore, when one is treating patients with aggressive or advanced UTUC, the goal of the treatment for physicians is to improve the life quality and prolong survival time for the patients, while monitoring or treating their metastases, but the management for the possible IVR is not a primary consideration. In the following part regarding risk factors that could affect the incidence of recurrent BC for UTUC patients, we only focus on patients with staging lower than pT2. As shown in Table 1, we can largely classify the factors that may influence the incidence of postoperative IVR for patients with UTUC after receiving RNU into four categories. 3.1. Patient-Specific Factors 3.1.1. Damaged eGFR Reduced eGFR may bring about electrolyte disturbances and imbalances of the internal environment within the patient. Kuroda K et al. retrospectively studied 187 UTUC patients with RNU and they found that a preoperative eGFR < 60 mL/min/1.73 m2 (HR = 2362, 95% CI = 1067-5592) is an independent factor for higher IVR in all UTUC patients . In addition, they believed that chronic kidney disease (CKD) or end-stage renal disease might be associated with the progression or invasiveness of UTUC . Similarly, Momota M et al. analyzed the clinical data of 1066 patients with UTUC, and the Cox analysis showed that there was a significant correlation between eGFR < 45 mL/min/1.73 m2 and IVR before RNU. These results might be due to the low eGFR, and some studies have found that the eGFR in UTUC patients could be decreased by 18% after RNU . Some studies demonstrated that CKD could lead to chronic inflammation, oxidative stress, metabolic disorders, and uremia-related immunodeficiency, which promote immune escape and the growth and metastasis of tumors . 3.1.2. Venerable Age Xylinas E et al. analyzed data from 1261 UTUC patients with RNU, and their multivariate Cox regression analysis showed that advanced age is associated with the postoperative IVR (p = 0.03) . Similarly, a study by Chromecki TF et al., who analyzed data from 1169 UTUC patients, they found that an age > 70 years old is an independent predictor for UTUC recurrence (p = 0.018), and they also found a 40.2% probability of recurrence in UTUC patients older than 80 years old in the third year after RNU . However, when these data were categorized by the physical performance status, the multivariate analysis found that age is not associated with disease recurrence (HR = 1.38, p = 0.101) . This observation suggested that UTUC recurrence might be more influenced by the physical health of the patient, but less related to the actual physical age. The study by Shariat SF et al. included 1453 patients with UTUC, and their multivariate analysis indicated that advanced age is not associated with recurrence of UTUC . However, they found that an older age is associated with history of previous ureteroscopy, a history of BC, an infiltrative tumor structure, and a poorer physical performance status in the investigated data. These above factors might contribute to the high recurrence rate of UTUC. Therefore, in actual clinical practice, the possibility of recurrence in patients of old age still needs to be considered in a focused manner. 3.1.3. Gender Difference UTUC is usually prevalent in men; however, Chien TM et al. analyzed data from 368 Chinese UTUC patients and they found a higher incidence of UTUC in women with advanced CKD. Multifactorial analysis showed that advanced CKD is an independent predictor for recurrent-free survival (RFS) in women with UTUC . In fact, in China, some women use traditional herbal medicines containing aristolochic acid during pregnancy or when they suffer from some diseases. It has been suggested that exposure to aristolochic acid is an important reason for the high incidence of UTUC in Chinese women , so it is also likely that the occurrence of IVR in some women with UTUC history is due to excessive aristolochic acid consumption. In one study by Xylinas E et al. and Ploussard G et al., they found that being male is associated with the occurrence of IVR for UTUC patients (p = 0.04 and 0.003, respectively) . Seisen T et al. conducted a meta-analysis including 18 studies with a total of 8275 UTUC patients, and after multifactorial analysis, they found that being male is a significant predictor of the postoperative IVR (HR = 1.37, p < 0.001) . Therefore, some researchers argued that adequate treatment and strict monitoring were necessary to reduce the tumor recurrence when one is dealing with male UTUC patients. 3.1.4. Smoking Smoking status or cumulative exposure has previously been shown to be associated with bladder recurrence after RNU . Xylinas E et al. performed a clinical trial including 519 UTUC patients after RNU. They classified the patients by current smoking status, cigarettes consumption per day, smoking duration, and time until they had quit. Using multivariate analysis, they found that current smoking duration (>=20 years) and heavy long-term smoking were associated with a higher risk of IVR (both p <= 0.04). In addition to this, patients who quit smoking ten years before receiving RNU had a lower risk of IVR than those who did not quit did . Similarly, Crivelli J.J. et al. performed a meta-analysis of three studies on smoking and showed that smoking is associated with IVR in two of the studies . In one study by Ehdaie B et al., who analyzed the disease characteristics of 288 UTUC patients, they found that smoking status is not associated with the risk of UTUC recurrence or death (p = 0.60). However, the risk of death is significantly higher in smokers than it is in non-smokers (HR = 3.64, 95% CI = 1.59-8.34) . Therefore, persuasive smoking cessation should be of great concern to surgeons, both in terms of the recurrence and prognosis for patients with UTUC. 3.1.5. Diabetes Mellitus with Poor Glycemic Control Poor glycemic control is most often seen in diabetic patients. Recent studies suggest that not all UTUC patients with diabetes will have a higher risk for IVR. Data from a study including 538 UTUC patients showed that diabetic patients with poor glycemic control (HbA1c >= 7.0%) exhibited a shorter RFS for recurrent bladder cancer compared with those of diabetic and non-diabetic patients with good glycemic control (both p < 0.001). In addition, in a multivariate analysis, poor glycemic control in diabetes independently predicted IVR (HR = 2.10, p < 0.018) . Similarly, a meta-analysis including 10 studies demonstrated that diabetes could increase the risk for IVR in patients with UTUC (HR = 1.26, 95% CI = 1.11-1.43, p = 0.0004) . It has been shown that hyperglycemia not only provided more nutrients to tumor cells, but also decreased the immunity, so that poor glycemic management in UTUC patients could contribute to tumorigenesis, apoptotic resistance, and resistance to chemotherapy . 3.1.6. Monocyte-to-Lymphocyte Ratio (MLR) The increasing numbers of studies have shown that inflammation might be associated with the survival and progression for malignant tumors . Therefore, it is feasible to examine cancer patients for inflammatory aspects to determine their specific prognosis. The monocyte-to-lymphocyte ratio (MLR) has been shown to correlate with the outcome of patients with UTUC . A multivariate analysis by Liu J et al., who analyzed data from 441 UTUC patients after receiving RNU, found that the preoperative MLR > 0.22 is significantly associated with IVR (HR = 4.085, p < 0.001). These results might suggest that MLR is an independent predictor for postoperative IVR in patients with UTUC . 3.1.7. Neutrophil-to-Lymphocyte Ratio (NLR) In addition to monocytes, the number of neutrophils is also used as an indicator for inflammation in the organism, and an increased neutrophil count often represents the development of inflammation . De Larco et al. showed that neutrophils in the tumor microenvironment could play a key role in angiogenesis and cancer progression . In addition to this, lymphocyte reduction may cause further immune escape for tumor cells. Therefore, an increased neutrophil-to-lymphocyte ratio (NLR) may suggest a higher chance of tumor invasion and metastasis and may cause IVR for UTUC patients after surgery. Vartolomei et al. analyzed nine studies including 4385 UTUC patients, and out of the six NLR-related studies, five demonstrated that elevated NLR is an independent predictor for tumor recurrence after patients receiving RNU (HR = 1.60, 95% CI = 1.16-2.19, p = 0.004) . Similarly, a study including 2477 UTUC patients demonstrated that patients with an NLR > 2.7 had a worse RFS than the patients with normal NLR did using an univariate analysis (p < 0.003), but no statistically significant difference was found in a multivariate analysis (p = 0.59) . Consequently, not all the studies demonstrated that an elevated NLR could independently predict postoperative recurrence in patients with UTUC, and their findings require further analysis. In actual clinical practice, when they are treating UTUC patients with an elevated NLR, physicians should proactively consider the possible elevated risk for tumor recurrence for their patients after receiving RNU. 3.2. Tumor-Specific Factors 3.2.1. Multifocality of Upper Urinary Tract Tumors Tumor multifocality refers to the presence of multiple tumor lesions in the unilateral urinary tract, which is often considered to have a worse prognosis than a single tumor does. In a retrospective review of 342 patients with UTUC, Milojevic B et al. found that tumor multimodality is associated with RFS (HR = 2.86, 95% CI = 2.06-3.99, p < 0.001) . In terms of IVR, Milojevic B's study showed the same results. Their multivariate analysis showed that tumor multiplicity is the only significant factor for predicting IVR (HR = 1.40, p = 0.037) . In clinical practice, tumor multiplicity of UTUC can be divided into multiple renal pelvic tumors, multiple ureteral tumors, and synchronous renal pelvic and ureteral tumors. Chen CS et al. retrospectively analyzed the data from 685 patients with UTUC diagnosed with multiple tumors, and they found that the synchronous renal pelvic and ureteral tumors group had a higher probability of IVR than the multiple renal pelvic tumor group did (p = 0.018) . This result suggested that UTUC patients with tumors in both the renal pelvis and ureter might require more stringent treatment and monitoring. The susceptibility to recurrence might be explained by the fact that multiple tumors tend to possess a more aggressive oncologic behavior and are more likely to be missed or delayed in the process of diagnosis and treatment . 3.2.2. Size of UTUC Tumor size is generally the main factor to describe the nature of tumors, and it has been previously demonstrated that a larger UTUC tumor might have a higher risk for IVR . In a multivariate analysis, Shibing Y et al. retrospectively analyzed data from 795 patients with UTUC, and showed that a tumor > 3.0 cm is an independent predictor for RFS (HR = 2193, p < 0.001) . The same conclusion was reached in the study by Espiritu PN et al. (HR = 1.97, p = 0.011), and they also found 5 year RFS rates were 46.9% and 25.8% for patients with tumor sizes < 3 cm and >=3 cm, respectively . This result might be explained by the fact that oversized UTUC tumors were not only more invasive, but also compressed or even obstructed the upper urethra resulting in high pressure in the upper urethra, where tumor cells might be more likely to be shed, invade, and implanted into the bladder. In contrast, a multifactorial analysis including 687 UTUC patients found that the effect of tumor size on IVR is not significant. However, the tumor size > 3 cm is significantly associated with IVR in a univariate analysis (p = 0.011) . Therefore, UTUC patients with a tumor size > 3 cm still need to be given more attention in clinical practice. 3.2.3. Distal Ureteral Position Tumors in UTUC are usually classified as tumors located in the ureter, renal pelvis, and multiple site tumors. It has been shown that tumors in the lower/middle ureter have a higher rate of local recurrence, but tumors in the renal pelvis have a higher prevalence of metastasis in distant organs such as the lungs . Therefore, it is likely that UTUC tumors in different locations have different effects on IVR. Xylinas E et al. analyzed 1839 patients with UTUC, and they found that a tumor located in the ureter is significantly associated with IVR (p = 0.03) . In addition to this, the same conclusion was reached by other two multivariate meta-analyses, the authors of which concluded that ureteral location is a significant predictor for IVR (both p < 0.001) . The reason for this result might be that ureteral tumors could cause ureteral obstruction even at earlier stages and grades , and that the higher pressure of the ureter and its closer proximity to the bladder result in a higher probability of seeding tumor cells. 3.2.4. Lymph Node Involvement Regional lymph nodes are the most common site of metastasis for UTUC patients , and tumor grading and lymph node involvement often represent increased malignancy and a higher probability of metastasis . Novara et al. demonstrated that lymph node involvement is an independent predictor for CSS, and they believed that UTUC patients with lymph node involvement had a three-fold increased risk of death compared to that of the patients with lymph node-negative disease . Therefore, the prevention of IVR in UTUC patients is not necessarily a primary consideration for patients with regional lymph node positive disease, and physicians should pay close attention to the complete removal of regional lymph nodes and tumor-containing tissues during the surgery and the possible local recurrence or distant metastasis when they follow up with the patients. For UTUC patients, lymph node involvement is likely to indicate that tumor cells are more likely to seed into the bladder. In a multivariable Cox regression analysis, Xylinas E found that lymph node involvement is independently associated with the occurrence of IVR for patients with UTUC (HR = 1.69, 95% CI = 1.19-2.40, p = 0.003) . Verhoest G et al. reached a similar conclusion that the proactive and appropriate lymph node dissection could improve the specific survival for UTUC patients . However, lymph node dissection may also have adverse effects on patients, leading to prolonged operative time and increased postoperative complications. Since the main site of lymph node metastasis depends on the location of the primary tumor , there is no exact standard for reginal lymph node dissections in different locations of UTUC, and therefore, individualized consideration for patients with lymph node involvement is needed. 3.2.5. Invasive pT Staging For UTUC patients, a large part of the occurrence of IVR may be due to excessive ureteral pressure caused by oversized tumors, which can seed cancer cells through the ureter into the bladder. In a multivariate analysis, Seisen T et al. retrospectively reviewed the data from 5041 patients with UTUC and found that the advanced stage (pT2, pT3, or pT4) is a significant predictor for IVR (HR 1.38, 95% CI 1.20-1.60; p < 0.001) . Additionally, Verhoest G et al. and Li Y et al. also found that factors such as locally aggressive budding tumors (i.e., aggressive pT staging) could increase the likelihood of cancer cells seeding into the bladder, and they were associated with the development of recurrent BC after the primary UTUC was completely resected . Therefore, UTUC at late stages not only have a higher malignancy, but also may cause excessive ureteral pressure or even obstruction, which may promote tumor cells implantation and lead to IVR. 3.2.6. Papillary Structure of Tumors Approximately two-thirds of UTUC patients have tumors with a papillary growth pattern and one-third have a sessile growth pattern. Different tumor structures are likely to possess different oncological behaviors. The study by Remzi M et al. included 1363 patients with UTUC after RNU, and they found the sessile tumor architecture is an independent factor for cancer recurrence (HR = 1.5, p = 0.002) and cancer-specific mortality (HR = 1.6, p = 0.001) . This was similar to the findings by Fritsche HM et al., who suggested that the sessile structure of the tumor is a predictor for IVR . Indeed, sessile carcinomas are more likely to suggest muscle-infiltrating disease, more aggressive behavior , a worse staging, and vicious oncological behavior. However, in recent years, a different opinion was presented by Ishioka J et al., who selected 754 UTUC patients for a multifactorial analysis, and they concluded that the papillary structure of the tumors is a predictor for IVR (HR = 1.676, 95% CI = 1087-2585, p = 0.019) . Therefore, a deeper investigation is needed regarding the effect of tumor structure for the occurrence of IVR. 3.2.7. Extensive Tumor Necrosis The meta-analysis by Seisen T, including 303 UTUC patients, showed that tumor necrosis is a significant predictor for IVR (HR = 2.17, 95% CI = 1.11-4.26, p = 0.02) . Several other studies with large samples showed that extensive tumor necrosis is independently associated with disease recurrence and survival . In the clinical setting, tumor necrosis has been shown to be associated with a poor outcome in many cancers , and it might indicate high malignancy and overgrowth of the tumor. Therefore, one possible explanation for the above results might be that the partially detached necrotic tumors are more likely to metastasize and implant due to the flow of urine in the renal pelvis and ureter. 3.2.8. Concomitant Carcinoma In Situ (CIS) CIS is a cytologic lesion which occurs in the uroepithelium and basement membrane and has the potential to infiltrate and invade into deep layer tissues. Concomitant CIS is defined as the presence of CIS associated with another pathological stage. In a multivariate analysis, Wheat JC et al. grouped 1387 patients with UTUC according to CIS, non-CIS, and concomitant CIS, and they found that concomitant CIS is a predictor for the development of IVR in patients with UTUC (HR = 1.25, p = 0.04) . Furthermore, in a retrospective study, the prevalence of combined CIS in patients with UTUC was 27-36% , and CIS has been long associated with aggressive diseases. It was shown that patients with CIS present at the time of the initial diagnosis were more likely to develop an aggressive disease if they were not treated promptly . The same conclusion was reached by Otto W et al., who performed a multivariate Cox regression analysis using data from 772 UTUC patients, and they found that concomitant CIS is an independent predictor for RFS (HR = 1.9, p = 0.007) and CSS (HR = 1.7, p = 0.048) . The above studies illustrated that concomitant CIS in UTUC patients not only cause tumor invasion and recurrence, but more importantly, if it is not promptly treated, it could also seriously affect the life expectancy of the patients. 3.3. Treatment-Specific Factors 3.3.1. Incomplete Excision The inadequate surgical treatment of UTUC is a clear predictor for ipsilateral ureteral stump or bladder tumor recurrence, such as incomplete resection, which increases the risk for IVR . Meanwhile, the study by Zou et al. and Chung JH et al. confirmed that incomplete resections in patients were significantly associated with their IVR . Seisen T et al. performed a meta-analysis using 18 retrospective studies including 8275 patients with UTUC, and the results demonstrated that an incomplete resection is a significant predictor for IVR (HR = 1.90, p = 0.004) . Indeed, due to surgical disruption, residual tumors were unstable; therefore, according to the implantation theory, their shed tumor cells might be more likely to implant through the ureter into the bladder, eventually causing IVR. 3.3.2. Immature Laparoscopic Technique Furthermore, different surgical choices contribute to variable recurrence rates. According to present studies, there was no evidence to confirm that the prognosis of patients treated with laparoscopic RNU (LRNU) was worse than that of those treated with open RNU (ORNU) . A meta-analysis including 10,730 patients with UTUC obtained the same conclusion; however, after multivariate analysis, Piszczek R et al. found that there was no significant difference between LRNU and ORNU in terms of IVR (HR = 1.08, 95% CI = 0.85-1.39, p = 0.52) . Nevertheless, there were some arguments against this, a meta-analysis conducted by Seisen T et al. showed that patients treated with LRNU had a significantly increased risk for IVR compared with that of those receiving ORNU (HR = 1.62, 95% CI = 1.18-2.22, p = 0.003) . Therefore, the impact of the surgical approach of RNU on IVR requires further study. For the existing medical technology, both LRNU and ORNU are relatively mature , and more often, the surgical approach is determined by the patient's tumor location and shape and the proficiency of the surgeons. Therefore, postoperative tumor metastasis or recurrence is more likely to be determined by the surgical technique. Shigeta K et al. selected 136 UTUC patients for comparison; half of them were treated with pure laparoscopic radical nephroureterectomy (p-LRNU) and the other half was treated with conventional LRNU. The clinical data demonstrated that the 3 year IVR-free survival rate in the p-LRNU group was 41.8%, which was significantly lower than those in the LRNU group (66.6%, p = 0.004). Multifactorial analysis showed that a history of p-LRNU is an independent risk factor for subsequent IVR. Thus, unskilled and imperfect laparoscopic technique usually leads to unstable postoperative prognostic outcomes. 3.3.3. Surgery Time In recent years, it has been found that not only the surgical approach affects the patient's IVR, but also, the duration of the surgical procedure might be associated with IVR. Shigeta K et al. found that with the longer duration of pneumoperitoneum created by an infusion of pressurized CO2 gas at a pressure of 10-12 mmHg during LRNU, the risk of IVR in UTUC patients was higher . Similarly, the Fisher's exact test analysis by Yanagi M et al. demonstrated that the prolonged duration of pneumoperitoneum at >=210 min with 8 mmHg CO2 gas pressure injected to create pneumoperitoneum during retroperitoneum LRNU was highly correlated with the risk for IVR (p = 0.0358). These results might be due to the extrusion of dislodged tumor cells by the high-pressure gas, resulting in the tumor cells implantation into the bladder cavity . Therefore, excessive surgery time might be another risk factor for IVR. 3.3.4. Early Ureteral Ligation Yamashita S et al. found that the IVR-free survival rates at years one and two for patients with renal pelvic cancer were 89% and 86% in the early ureteral ligation group and 74% and 64% in the control group (p = 0.025), respectively, so early ureteral ligation is an independent predictor for IVR in patients with UTUC located in the renal pelvis . Chen MK et al. selected 85 eligible cases, and they found that early ureteral ligation is an independent risk factor for subsequent bladder recurrence after UTUC (HR = 2.35, 95% CI = 1.53-3.48, p = 0.041). The IVR rate in patients with early ureteral ligation was significantly lower compared to that of the patients in the standard group (14.3% vs. 34.9%, p = 0.026) . During RNU, some surgical movements are very likely to touch or squeeze the tumor tissues, some of the detached tumor cells may then migrate down through the ureter into the bladder. So early ureteral ligation during the operation not only facilitates the operation, but also reduces the probability of IVR. 3.3.5. Ureteroscopy In addition, cancer cells could easily migrate to other locations within the urinary tract during ureteroscopy (URS). A multifactorial analysis conducted by Sung HH et al. showed that IVR rates were significantly higher in the preoperative ureteroscopic biopsy (URS-Bx) group (HR = 1558, 95% CI = 1204-2016, p = 0.001) and did not differ regardless of whether or not manipulations such as tumor biopsy and balloon dilation were performed (p = 0.658) . In the same way, Li YR et al. showed that preoperative ureter manipulation is an independent factor for IVR (p = 0.005) . Addtionally, Yoo S et al. found that URS us also an important risk factor for IVR in patients with UTUC , including the pre-RNU URS (URS with no tissue biopsy) and diagnostic URS (URS with tissue biopsy). Another recent study conducted by Loizzo et al. reached the same conclusion, and they found that the diagnostic accuracy of URS-Bx was only 72.4% for low-grade UTUC and 36% for in-staging accuracy in all grades for UTUC patients . The above four studies suggest that URS should be minimized or avoided if the diagnosis could be confirmed preoperatively by other examination methods; additionally, diagnostic URS should be used to make decisions based on different risk stratification and is more inappropriate for determining tumor staging for patients with UTUC. Nowadays, there are two types of ureteroscopes, including rigid and flexible ones, and the different ureteroscopes might also lead to different risks for IVR. A multivariate Cox regression analysis including 491 UTUC patients by Ha JS et al. showed that the flexible URS group was significantly more associated with an elevated IVR than the non-URS group was (HR = 1807, p = 0.0416). In contrast, the difference for IVR between the non-URS and rigid URS groups was not statistically significant (HR = 1301, p = 0.3388) . The study suggested that rigid URS might be safer, which could be explained by the fact that flexible URS required a more pressurized irrigation fluid to ensure the field of viewing during examination, thus exacerbating the shedding of tumor cells. 3.4. Molecular-Specific Factors 3.4.1. E-Calmodulin Calmodulins are a group of transmembrane proteins that are reliant on calcium (Ca2+) ions for their action and are essential for maintaining cell-to-cell contact and modulating the cytoskeletal complexes. In this group, E-calmodulin plays an important role in cell adhesion, whose loss of expression is a signature of epithelial-mesenchymal transition (EMT) and is related to an increased risk of cancer metastasis. At the same time, the expression of E-calmodulin was also shown to be associated with the overall survival (OS) of patients with bladder cancer, suggesting a probable survival benefit, which implies that E-calmodulin expression might be a prognostic factor for life expectancy in patients with bladder cancer . Inoue and colleagues investigated the expression of invasion-related genes in 55 UTUC patients who had undergone RNU and found that the expression of E-cadherin is associated with bladder-specific recurrence . Favaretto RL et al. evaluated 678 patients with UTUC treated with RNU and they found that reduced E-calmodulin expression is associated with a worse RFS using a univariate analysis (p < 0.001). 3.4.2. Forkhead Box O3A Forkhead box O3A (FOXO3A) belongs to the FOXO protein family and is located on human chromosome 6q21. It functions generally as an important transcriptional regulator involved in DNA damage repair, cell cycle regulation, apoptosis, and the cellular stress response . Zhang G et al. examined the expression level of FOXO3A in 107 UTUC patients and found that the RFS was significantly shorter in patients with UTUC with low FOXO3A expression compared to that of the high-expression group (HR = 2.385, p = 0.004) . Several studies have also demonstrated that downregulation of FOXO3A expression could promote occurrence, metastasis, and progression for UTUC patients . In addition, they found lower levels of FOXO3A expression in UTUC tissues than they did in normal tissues . Since FOXO3A is a recognized class of anti-cancer genes, its low expression might be related to the susceptibility of UTUC patients for recurrence and metastasis. 3.4.3. HER2 HER2 is a member of the epidermal growth factor receptor (EGFR) family and is involved in cell proliferation and differentiation. Its overexpression is frequently associated with tumor growth and metastasis, therefore, HER2 has been used as an antitumor therapeutic target in some cancer patients . A multicenter retrospective study by Soria F et al. including 732 patients with UTUC after RNU found that HER2 was overexpressed in 35.8% of patients. In another multivariate analysis, HER2 overexpression was also associated with IVR (p = 0.04) . 4. Current Treatment Measures for UTUC-BC Currently, not a lot is known about the natural course of bladder cancer recurrence after UTUC . It is not clear about the frequency and the specific time frame for which superficial bladder cancer may progress to an invasive disease; therefore, we recommend that the possible management strategy involves postoperative prevention, surveillance, and post-recurrence treatment should be taken in consideration . 4.1. Prevention 4.1.1. Surgical Techniques Regardless of the tumor location, ORNU with bladder cuff excision has consistently been the standardized surgery in the management of patients with high-risk UTUC, and we recommend dissecting the ipsilateral medial cord ligament and lowering the ipsilateral bladder to facilitate the dissection of the whole distal segment of the ureter. The majority of the published works suggested that a minimally invasive approach might bring a more favorable perioperative outcome . To lower the risk of tumor recurrence, oncological principles must be followed throughout the procedure, including the avoidance of access to the urinary tract, the avoidance of direct contact of instruments with the tumor, and using internal capsules to extract the specimens to prevent tumor seeding , the clamping of the ureter localized at the distal part of the UTUC tumor at an early stage to restrict the seeding of tumor cells into the bladder cavity in a downstream direction during renal and ureteral manipulation , and the resection of the upper urinary tract (kidney, ureter, and bladder cuff) intact . Avoiding incomplete resection and ensuring negative surgical margins might contribute to lowering the recurrence rate. In addition, the surgery duration should be reasonably controlled to avoid an excessive operative time, which might cause the possibility of intracavitary metastasis and seeding tumor cells . For tumors with pT > 2 stage, concomitant CIS, or extensive necrosis, surgeons should be more careful during the perioperative period . It was mentioned previously that the involvement of lymph nodes is a risk factor for IVR ; therefore, we recommend that lymph node dissection should routinely performed for UTUC patients with pT > 2 stage, especially for high-risk patients. Given that the ureter is divided into upper, middle, and lower segments, the possibilities for lymph node dissection are very variable and would depend on the patient's individual condition. Ureteroscopic biopsy and dialysis were mentioned earlier as independent risk factors for IVR , so minimizing the number of ureteroscopies and the number of dialysis preoperatively might also reduce IVR. 4.1.2. Intravesical Treatment Intravesical therapy refers to the local adjuvant therapy in which chemotherapeutic drugs are instilled into the bladder cavity through a catheter to inhibit the growth of cancer cells in the bladder. The goals of local instillation therapy in UTUC are to reduce the risk of tumor recurrence and progression and to treat CIS . The commonly used drugs are: mitomycin C (MMC), gemcitabine (GEM), pirarubicin (THP), etc. It has been shown that an immediate single bladder instillation of MMC prior to RNU or partial ureterectomy (within 3 h) could reduce the risk of bladder recurrence . Alternatively, intraoperative bladder instillation of MMC is feasible and is not associated with the risk of complication . Fang D et al. and Hwang EC et al. performed a meta-analysis including seven randomized controlled trials, and they found that early postoperative intravesical chemotherapy with MMC and THP could reduce the risk of bladder tumor recurrence within the first year after RNU . Ito et al. treated UTUC patients with a single bladder instillation with 30 mg THP within 48 h after RNU and showed fewer bladder recurrences in patients who received THP instillation compared to those of the patients in the control group . Due to existing studies, the timing of intravesical therapy also plays a differential role in the outcome. Noennig et al. compared intraoperative and postoperative bladder instillation by MMC, and they found that the one year bladder recurrence rate was significantly lower in the intraoperative group than it was in those patients who received postoperative MMC instillation . In the timing of postoperative titration, a single dose of MMC given within 24 h after RNU to prevent recurrence was demonstrated to be more effective than delayed intravesical titration is within 48 h or 2 weeks postoperatively . In addition to the timing of instillation, the frequency of instillation also affects the IVR of patients with UTUC. In a study by Huang Y et al., 270 patients were divided into three groups, which included multiple, single, and no instillation groups. These patients were instilled with epirubicin (30-50 mg per instillation, 125 patients), pirarubicin (30-50 mg per instillation, 89 patients), or mitomycin C (20-40 mg per instillation, 15 patients). The patients in both instillation groups were found to have a significantly lower recurrence rate compared to that of the no instillation group (13.1 vs. 25.4% vs. 41.5%, p = 0.001). Multiple instillation group had a higher bladder RFS rate than the single instillation group did . These findings might suggest that the use of early and multiple intravesical treatment in the perioperative period could effectively reduce the probability of IVR for patients with UTUC. The use of adjuvant intracavitary therapy has increased in recent years, with BCG being one of the first, and perhaps, the most studied adjuvant therapies. The use of BCG for the treatment of CIS is largely considered to be the standard of care in those who meet the criteria for intermediate or high-risk non-muscle invasive bladder cancer. Its use is supported by the American Urological Association (AUA) and European Association of Urology (EAU) guidelines. However, the efficacy of upper urinary tract remains uncertain and varies by dose variation, unique delivery mechanisms, and indication . The study conducted by Rastinehad et al. reported 50 patients who received BCG instillation for the treatment of UTUC at Ta/T1 stages. However, there did not have any statistical significance between UTUC patients who received and who did not receive adjuvant BCG therapy . The use of BCG might be more appropriate for CIS, as Carmignani et al. have shown that the induction process of BCG could convert a positive cytology to a negative one, with a mean recurrence rate of 32% at 19-57 months of follow-up. However, cytology negativity alone was not sufficient as a sign of remission . In addition to intravesical instillation, neoadjuvant chemotherapy (NAC) has become a treatment option that has been received a lot of attention in recent years. Wu Z et al. analyzed 24 studies and found that NAC had a higher survival rate and better pathological response compared to those of surgery, but there were no more significant advantages compared to those of surgery plus adjuvant chemotherapy . Therefore, the specific treatment modality and timing of NAC needs to be explored by more evidence-based research. Zennami K et al. studied a total of 184 UTUC patients grouped by whether or not they received NAC before RNU and found that high-risk UTUC patients who received NAC treatment had a significantly higher 5 year RFS than the controls did (80% vs. 61%, p = 0.001). A higher OS was also observed in patients with disease-staged <=cT2 who underwent the NAC treatment (p = 0.019) . Similarly, Shigeta K et al. studied 89 patients with UTUC who received NAC or conventional adjuvant chemotherapy and found that the NAC treatment before RNU could significantly improve RFS more than treatment with chemotherapy could (p = 0.039) . Due to the nephrotoxicity of platinum-containing drugs, preoperative NAC, such as chemotherapy with gemcitabine + carboplatin and immunotherapy with PD-1/PD-L1 immunosuppressants was encouraged to optimize the surgical outcomes , especially for UTUC patients with a poor renal function. So, if the patient has normal renal function, the implementation of regimens with cisplatin instead of carboplatin could bring about better therapeutic results . However, if the patient has poor renal function, then platinum-containing drugs should be avoided. Additionally, immunotherapy also plays a positive role in the prognosis of UTUC patients. Fradet Y et al. analyzed 542 UTUC patients treated with pembrolizumab or conventional chemotherapy, and they found that the one year OS rates and progression-free survival rates were higher in the UTUC patients group treated with pembrolizumab (44.2% and 12.4%, respectively) than they were in the chemotherapy group (29.8% and 3.0%, respectively), with a lower incidence of associated adverse events . 4.2. Monitoring during the Follow-Up Screening for smoking: Smoking is one of the risk factors for recurrence, as mentioned earlier. Crivelli JJ et al. analyzed six studies, estimating the effect of smoking for patients with UTUC after receiving RNU. Most of the studies were found a statistically significant relationship between smoking and IVR. The studies also found that smoking is associated with cancer-specific mortality for patients with UTUC-BC , so screening for smoking is also essential. Imaging: Computed tomography (CT) and intravenous urography of the bladder and ureter should be performed at least once a year. If necessary, MRI should also be added into the monitoring plan. Endoscopy: patients with UTUC must undergo endoscopic surveillance after RNU, and the surveillance program lasts for at least 5 years, with flexible cystoscopy recommended for the surveillance of male patients . Molecular biomarkers: Various molecular biomarkers can be used to help detect recurrent bladder cancer: e.g., tumor factors, UroVysion, and BTA tests. Using Kaplan-Meier analysis, Guan B et al. showed that UTUC patients with positive UroVysion results were more likely to develop IVR during the follow-up (p = 0.077). These data suggest that the urinary UroVysion test may be a powerful tool for predicting the risk of IVR in patients with UTUC . Walsh et al. performed a study to evaluate the effectiveness of the BTA test in patients with UTUC and found that the sensitivity of the BTA was 82% and the specificity was 89%, which were significantly better than those of the urinalysis in the same group of patients (11% and 54%, respectively) . However, the study conducted by Bialek L et al. found moderate diagnostic accuracy when they were detecting bladder cancer for patients with UTUC by BTA . Therefore, more evidence is needed for BTA to detect the occurrence of IVR in patients with UTUC. Tumor factors such as E-calmodulin and FGFR3 in molecular-specific factors have been shown to correlate with IVR, so these indicators can also be evaluated during the follow-up period. If a patient meets more of the above IVR risk factors, the frequency and length of follow-up should be increased to give appropriate consideration for the patient's specific situation. 4.3. Treatment Bladder cancer and UTUC, although they are similar, are not identical in terms of biological nature and prognosis. As only a little is known about the natural course and disease characteristics of UTUC-BC, the frequency and specific time frame for the possible progression of superficial bladder cancer to invasive disease cannot be estimated either . Therefore, even though some studies have investigated risk factors for the development of IVR in patients with UTUC, there have not been large-scale studies of the treatment strategies for patients with UTUC-BC . Consequently, the current management for patients with UTUC-BC is similar to the current guideline-based treatment strategies for patients with primary bladder cancer . For NMIBC patients with a history of UTUC (UTUC-NMIBC), transurethral resection of the bladder tumor (TUR-BT) remains the initial treatment option. For MIBC patients with a history of UTUC (UTUC-MIBC), radical cystectomy (RC) is commonly recommended . Since NMIBC and MIBC infiltrate different tissue layers, as shown in Figure 1, the treatment methods for them are also different, and we mainly focus on the treatment for patients with UTUC-NMIBC in this review article. 4.3.1. TUR-BT A study by Wu J et al. showed poorer outcomes among UTUC-NMIBC patients after receiving RC, with a one year overall survival (1 yr OS) of 81.8% and a three year overall survival (3 yr OS) of 56.1%, while the patients undergoing TUR-BT had relatively good outcomes (1 yr OS: 86.6%; 1 yr OS: 65.6%) . TUR-BT is both the first choice management option and an important diagnostic approach for patients with UTUC-NMIBC, contributing to a prolonged RFS for the patients. Mariappan et al. found that the lack of bladder detrusor in the specimen, as well as the presence of a residual tumor, was significantly associated with an increased risk of early recurrence in the bladder , which made the complete excision of tumors containing bladder detrusor particularly important. Two multifactorial analyses found that tumor concomitant CIS at the time of first IVR was an independent risk factor for UTUC-BC progression . Therefore, if a patient was found to have concomitant CIS during surgery, more attention should be paid to the complete resection of the tumor specimen and to restrictively follow oncologic principles during surgery. There was also a reduced recurrence rate when narrow band imaging (NBI) was used during TUR-BT . 4.3.2. En Bloc Resection of Bladder Tumor (ERBT) Tanaka N et al. investigated 241 patients with UTUC-BC after receiving RNU. Among them, the cumulative incidence rates of recurrent IVR at 1 and 5 years after treatment were 31.0% and 48.4%, respectively . For the treatment of patients with such a high recurrence rate, ERBT is gradually becoming an alternative treatment to conventional TUR-BT. ERBT can obtain a complete bladder tumor specimen, allowing the pathologist to make a more accurate diagnosis of the incision margin and depth of infiltration, with it being conducive to acquiring accurate pathological staging and achieving clinical significance for postoperative bladder perfusion protocols, prognosis, and individualized follow-up program . For patients with UTUC-NMIBC, ERBT was more feasible, safer, with fewer intraoperative complications than those of conventional TUR-BT, and it resulted in less remaining tumors and was unlikely to be replaced by TUR-BT . It is more likely that the secondary resection could be avoided by good en block resection and might gradually become the main therapeutic modality for patients with UTUC-NMIBC in the future. Additionally, with the development of medical laser technology, there are more wide-spread lasers being used in TUR-BT, and some studies argued that TUR-BT using lasers could achieve more satisfactory treatment effects with a better prognosis than traditional electric TUR-BT can. 4.3.3. Secondary Resection A considerable number of patients with UTUC-NMIBC will experience tumor recurrence after electrotomy due to factors such as tumor stage, size, numbers, and the surgical skill of the surgeon. Therefore, for those recurrent patients, we need to repeat TUR-BT (reTUR), which requires the resection of the basal part of the original tumor area (including the surrounding mucosal inflammatory edema area) and the suspected tumor site. It is necessary to resect into the deep muscular layer of the bladder. Meanwhile, it is advised to make multiple randomized biopsies from the bladder wall. A reTUR can increase the RFS, improve the outcomes after BCG treatment, and provide prognostic information . Because there are only a few surgical data about patients with UTUC-NMIBC, surgeons should decide when to perform reTUR based on the patient's individual characteristics (e.g., concomitant CIS, etc.). 4.3.4. Intravesical Chemotherapy There are surgical options for both types of UTUC-BC, yet there are only a few data showing improved survival in UTUC-BC patients treated with these therapies . Two multifactorial analyses have shown that the failure to perform intravesical therapy is an independent risk factor for disease progression for patients with UTUC-BC . Therefore, intravesical chemotherapy is essential in the treatment program. Intravesical instillation has been shown to be effective by destroying circulating tumor cells after TUR-BT by ablating tiny residual or neglected tumor cells at the resection site . It has been shown that tumors in patients with UTUC-BC respond more poorly to BCG than those in the patients with primary BC do . Therefore, instillation drugs with higher sensitivity should be selected for patients with UTUC-B, and normal saline with MMC, epirubicin, or pirarubicin showed beneficial effects . In a randomized controlled trial, the experimental group of normal saline combined with gemcitabine was superior to the placebo control (saline) group, with significantly lower toxicity . Gemcitabine has been shown to have a response rate no less than that of the existing standard MMC and has several other advantages, including lower toxicity and costs . 4.3.5. Photodynamic Diagnosis (PDD) and Radical Cystectomy (RC) To further improve surgical outcomes, some studies had shown that the introduction of photosensitizers for photodynamic diagnosis (PDD) during TUR-BT could improve the complete detection of tumors and reduce residual tumors more compared to that of white light cystoscopy (WLC), but it had no significant advantage over conventional WLC in terms of diagnostic accuracy . In addition to this, Wu J et al. found that patients with UTUC-MIBC who previously received radical cystectomy (RC) did not have significantly better survival compared to those who had tumor resection by TUR-BT . The above treatment modalities are roughly the same as those for primary BC. So, physicians can make an appropriate treatment strategy when they are treating patients with UTUC-BC according to the treatment guidelines for primary BC. 5. Conclusions UTUC is a rare, but highly malignant, disease, with a higher change of recurrence in the bladder and distant metastasis. In this review article, we summarized the possible mechanisms for the occurrence of IVR for patients with UTUC, including the tumor implantation theory and the correlation and characteristics of UTUC-BC and primary BC. Subsequently, we analyzed the possible factors influencing the occurrence of IVR through four aspects: the patient, tumor, treatment, and molecular specific factors. We introduced the current methods for prevention and monitoring, accordingly. In addition to this, if IVR occurs in UTUC patients, even though the current therapeutic tools are roughly the same as those used to treat primary BC, we described the advantages of these therapeutic tools and the points that need more attention when one is treating patients with UTUC-BC. Here, we recommend that urologists should develop their treatment strategies according to the risk stratification of UTUC, taking into account the specific clinical characteristics of individual patients and perform long-term, risk-adapted follow-up plans. However, due to the low incidence of UTUC, existing clinical studies are inevitably limited by their sample size, selection, and processing deviation, but there were still some inconsistent findings regarding surgical details, chemotherapeutic drug selection, and endoscopy modalities. In recent years, researchers have made continuous efforts in genomics, pathogenesis, imaging technology, and clinical practice and have achieved significant results in exploring the colonial origin and intracavitary seeding theory for UTUC-BC, improving the diagnoses and treatments for those patients. We are expecting to see there will be more available biomarkers to help urological surgeons to predict or identify possible postoperative recurrence, as well as to guide appropriate treatment options. In the future, better surgical techniques and more individualized drugs will greatly improve the survival and quality of life for patients with UTUC or recurrent BC. Author Contributions Conceptualization, G.Z.; original draft writing, X.H.; figures preparation and table making, Y.X.; manuscript review and editing, G.Z.; funding acquisition, G.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The colonial origin and intracavitary seeding theory of postoperatively recurrent bladder cancer for patients with upper tract urothelial carcinoma history (UTUC-BC). Figure 2 Current diagnosis and treatment strategy for patients with UTUC-BC. UTUC: upper tract urothelial carcinoma; RNU: radical nephroureterectomy; IVR: intravesical recurrence; TUR-BT: transurethral resection of bladder tumor; ReTUR: repeat TUR-BT; ERBT: en bloc resection of bladder tumor; RC: radical cystectomy; MMC: mitomycin C; THP: pirarubicin. diagnostics-13-01004-t001_Table 1 Table 1 Main risk factors affect recurrent BC for patients with UTUC. Categories Risk Factors Reference Patient specific factors Damaged eGFR Kuroda K et al. Xylinas E et al. Rasool M et al. Chowdhury R et al. Venerable age Xylinas E et al. Chromecki TF et al. Shariat SF et al. Gender difference Chien TM et al. Chen CH et al. Xylinas E et al. Ploussard G et al. Seisen T et al. Smoking Xylinas E et al. Xylinas E et al. Crivelli JJ et al. Ehdaie B et al. Diabetes mellitus with poor glycemic control Tai YS et al. Gao X et al. Duan W et al. Monocyte-to-lymphocyte ratio (MLR) Liu J et al. Zhang XK et al. Neutrophil-to-lymphocyte ratio (NLR) Mathieu R et al. De Larco JE et al. Vartolomei MD et al. Vartolomei MD et al. Tumor specific factors Multifocality of upper urinary tract tumors Milojevic B et al. Chen CS et al. Sheu ZL et al. Chromecki TF et al. Size of upper urinary tract tumor Kauffman EC et al. Shibing Y et al. Espiritu PN et al. Su X et al. Distal ureteral position Tanaka N et al. Xylinas E et al. Seisen T et al. Wu Y et al. Lymph node involvement Arancibia MF et al. Xylinas E et al. Roscigno M et al. Novara G et al. Verhoest G et al. Peyrottes A et al. Invasive pT staging Seisen T et al. Verhoest G et al. Li YR et al. papillary structure of tumors Remzi M et al. Fritsche HM et al. Ishioka J et al. Extensive tumor necrosis Seisen T et al. Zigeuner R et al. Simone G et al. Zhang L et al. Concomitant carcinoma in situ (CIS) Wheat JC et al. Roscigno M et al. Otto W et al. Treatment specific factors Incomplete excision Kauffman EC et al. Zou L et al. Chung JH et al. Seisen T et al. Immature laparoscopic technique Favaretto RL et al. Piszczek R et al. Seisen T et al. Shigeta K et al. Surgery time Yanagi M et al. Shigeta K et al. Early ureteral ligation Yamashita S et al. Chen MK et al. Ureteroscopy Sung HH et al. Li YR et al. Yoo S et al. Loizzo D et al. Ha JS et al. Molecular specific factors E-calmodulin K et al. FOXO3A Zhang G et al. Li J et al. HER2 Sasaki Y et al. Soria F et al. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. 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PMC10000490 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050918 foods-12-00918 Article Effect of Coagulant and Treatment Conditions on the Gelation and Textural Properties of Acidic Whey Tofu Guan Ziyu Writing - original draft 12 Zhang Jie Writing - review & editing 12* Zhang Shitong 12 He Yun Writing - review & editing 12 Li Yadi Writing - review & editing 12 Regenstein Joe M. 3 Xie Yuan Writing - review & editing 12 Zhou Peng Writing - review & editing 12 Alves Vitor D. Academic Editor 1 State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China 2 School of Food Science and Technology, Jiangnan University, Wuxi 214122, China 3 Department of Food Science, Cornell University, Ithaca, NY 14853-7201, USA * Correspondence: [email protected]; Tel./Fax: +86-510-85326012 21 2 2023 3 2023 12 5 91807 1 2023 06 2 2023 14 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). This study aimed to investigate the properties of acidic whey tofu gelatin generated from two acidic whey coagulants by pure fermentation of Lactiplantibacillus paracasei and L. plantarum, as well as the characteristics of acidic whey tofu. The optimal holding temperature and the amount of coagulants added were determined based on the pH, water-holding capacity, texture, microstructure, and rheological properties of tofu gelation. Then, the differences in quality between tofu produced by pure bacterial fermentation and by natural fermentation were investigated under optimal tofu gelatin preparation conditions. The tofu gelatin presented the best texture at 37 degC with a 10% addition of coagulants fermented by both L. paracasei and L. plantarum. Under these conditions, the coagulant produced by the fermentation of L. plantarum resulted in a shorter formation time and stronger tofu gelatin compared with that produced from L. paracasei. Tofu produced by the fermentation of L. paracasei had higher pH, less hardness, and a rougher network structure, whereas tofu produced by the fermentation of L. plantarum was closer to tofu produced by natural fermentation in terms of pH, texture, rheology, and microstructure. acidic whey coagulant Lactiplantibacillus paracasei Lactiplantibacillus plantarum rheological properties texture tofu gelation China Postdoctoral Science Foundation2022M721369 This study was partly supported by the fellowship of China Postdoctoral Science Foundation (2022M721369). pmc1. Introduction Tofu is a highly hydrated soybean protein gelatin, and the essence of its production process is the extraction and gelation of soybean protein . After screening and cleaning, impurity-free soybeans are obtained, which are fully soaked in water and then ground to obtain raw soybean milk. After soybean milk is boiled, the coagulant of appropriate concentration is added. The product is pressed into shape, and the excess liquid is discharged, which is soybean whey . In traditional Chinese tofu production, acidic whey, which is produced by the natural fermentation of soybean whey, was often used as the coagulant to make acidic whey tofu . When coagulant is added to cooked soybean milk, the lactic acid bacteria in it use the carbohydrates in soybean milk to produce large amounts of lactic acid, causing the pH of the solution to drop and move toward the isoelectric point of the soybean protein . In this acidic solution, the decreasing protein surface electrical charge further reduces the electrostatic repulsion on the protein surface, destroying the colloidal stability and forming soybean protein gelatin by protein cross-linking under the action of hydrogen bonding and hydrophobicity . However, the production of acidic whey tofu is mostly home-based. The judgment of the fermentation ending point of coagulant is mostly based on manual experience and lacks scientific guidance. In addition, coagulant is generally obtained by the natural fermentation of soybean whey placed outdoors, which may contain harmful microorganisms. Moreover, in actual production, the coagulant is easily affected by the environment and season, and the quality of the coagulant varies greatly from batch to batch . Therefore, the variation in the quality of coagulant leads to the unstable quality of acidic whey tofu, seriously restricting the development of tofu. As people have become more health conscious in recent years, tofu has become a new trend as a new lactic acid bacteria carrier. Chen et al. used Weisseria greekii D1501 in combination with transglutaminase to produce a new type of lactic acid bacteria tofu that was creamy, smooth, soft, and elastic, which was effective in inhibiting contamination by other bacteria and extending the shelf life of tofu. Riciputi et al. and Serrazanetti et al. used L. casei and L. acidophilus to ferment soybean milk and salt brine as tofu coagulants and found that L. acidophilus could produce enough substances such as acetic acid, limonene, and benzyl alcohol to inhibit the growth of spoilage bacteria while promoting the synthesis of bioactive substances in tofu. Wang et al. used L. plantarum fermented plum juice as an acidic coagulant for tofu and produced tofu with plum juice that was close to the quality of lactic tofu and could be stored for 1 week at 4 degC. This study aimed to determine the properties of tofu gelatin and tofu produced from two acidic whey coagulants by pure fermentation of L. paracasei and L. plantarum. Our study provided theoretical guidance for producing stable and good-quality acidic whey tofu, which was conducive to the industrial production of local specialty curd. 2. Materials and Methods 2.1. Materials Soybeans were purchased from Anhui Huaibei Jinyuan Soybeans Wholesale Co., Ltd. (Huaibei, Anhui, China). Acidic whey was collected from a local tofu manufacturing market and stored in -20 degC for future use. L. plantarum Lb-p1 and L. paracasei were obtained from acidic whey collected from Chuxiong, Yunnan, China. The processing procedure for the manufacture of acidic whey tofu is shown in Figure S1. High-quality soybeans with whole kernels were selected and soaked at room temperature for 10-12 h at a soybean:water ratio of 1:3.5. The soybeans were then drained and pulverized in a hot-wall cooker for 1 min at a soybean:water ratio of 1:8 (water added = dry soybean mass x 9--soaked soybean mass). The soybean milk was filtered through 120-mesh gauze. The soybean milk was heated in a boiling water bath and cooled in an ice water bath after the heating was completed. 2.2. Preparation of Acidic Whey Tofu Gelatin and Acidic Whey Tofu The acidic whey coagulant was obtained by inoculating Lb-p1 (6 log CFU mL-1) or L. paracasei in sterile 0.85% NaCl into sterile soybean milk with a volume percentage of 3% and then cultivating at 37 degC for 12 h. For optimizing the temperature, this coagulant was added to soybean milk at the ratio of 1:10 (v/v) and incubated at 27, 37, 47, 57, and 67 degC for 6 h using the water bath. For optimizing the ratio, the coagulant was mixed with soybean milk with the percentage of 4%, 7%, 10%, 13%, and 16% and incubated at 37 degC for 6 h using the water bath. The obtained acidic whey tofu gelatin was cooled down using ice water to 4 degC for analysis. Soybean milk (500 mL) was taken, and 50 mL of pure-bacterial-fermented coagulant and naturally fermented coagulant were added separately and kept warm for 6 h. The mixture was poured into a tofu mold (8 x 8 x 6 cm3) and pressed with a force of 25 g/cm2 for 90 min to obtain different acidic whey tofu, which was stored in a refrigerator at 4 degC for backup. 2.3. Determination of the pH Value of Acidic Whey Tofu Gelatin and Acidic Whey Tofu Acidic whey tofu gelatin (10 g) was weighed and pounded, and its pH was measured directly with a pH meter (Mettler Toledo, Columbus, OH, USA). After adding deionized water (20 mL) to the acidic tofu (5 g), it was homogenized with a disperser for 1 min and then stirred at room temperature for 30 min. The pH of the sample was measured directly using the pH meter. 2.4. Determination of the Water-Holding Capacity of Acidic Whey Tofu Gelatin and Acidic Whey Tofu After the soybean milk was mixed with the acidic whey, it was placed in a 50 mL centrifuge tube, kept in a water bath for 6 h, and left overnight at 4 degC. After reaching room temperature, the sample was centrifuged at 20 degC for 10 min at 4000x g. The water left on the bottom of the tube was poured out, and the tube was placed upside down on filter paper to absorb the water flow. The water-holding capacity of the acidic whey tofu gelatin was defined as the ratio of the mass of the sample after centrifugation to the mass of the sample before centrifugation. For acidic whey tofu, its water-holding capacity was determined using the same method. 2.5. Determination of Texture Profile Analysis of Acidic Whey Tofu Gelatin and Acidic Whey Tofu Acidic whey tofu gelatin stored overnight at 4 degC was removed and equilibrated at room temperature for 1 h. The hardness of gelation was determined using TA-XT Plus (Stable Micro Systems, Ltd., Godalming, UK). The measurement conditions were as follows: a P/0.5 R probe was selected, the pre-test speed, mid-test speed, and post-test speed were 0.8 mm/s, the trigger force was 1 g, and the measurement distance was 6 mm. The probe was centered on the sample, and the hardness of gelatin was expressed as the maximum induced force (g) obtained during the determination. Acidic whey tofu stored overnight at 4 degC was cut into blocks of 2 x 2 x 2 cm3 and equilibrated at room temperature for 1 h. Texture profile analysis (TPA) was determined using TA-XT Plus. The measurement conditions were as follows: P50 probe was selected, and the premeasurement velocity, mid-measurement velocity, and post-measurement velocity were 1.5 mm/s, 1 mm/s, and 1 mm/s, respectively; the trigger force was 2 g; and the measurement distance was 5 mm. The probe was centered on the sample, and the tofu gelation hardness was expressed as the maximum induction force (g) obtained during the measurement . 2.6. Determination of the Rheological Properties of Acidic Whey Tofu Gelatin and Acidic Whey Tofu Rheological properties were measured with a HAAKE MARSIII rheometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). For acidic whey tofu gelatin, temperature scanning was applied using a 50-mm parallel-plate probe with a gap setting of 1 mm. A strain of 1% (within the linear range) and a frequency of 1 Hz were selected. Soybean milk (10 mL) was mixed with an appropriate coagulant, and the sample was quickly added to the sample stage. The rheometer probe was lowered, and the excess sample around the probe was aspirated. The sample was then sealed with silicone oil and solvent cap to avoid water evaporation during the measurement. The experimental procedures for temperature scanning were as follows: the warming program scan was 25-37 degC at the rate of 2 degC/min, the constant-temperature program scan was 37 degC for 360 min, and the cooling program scan was 37-25 degC at the rate of 2 degC/min. The trends of the storage modulus (G') and lost modulus (G'') with time during the temperature scan were recorded. After the temperature scan, acidic whey tofu gelatin was subjected to a frequency scan at 25 degC with an angular frequency scan range of 1 rad/s to 100 rad/s and a strain of 1%. The trends of G' and G'' with the angular frequency scan range during the temperature scan were recorded . Acidic whey tofu was determined using both strain creep response and creep-recovery response. For strain creep response, the sample was cut into thin slices of about 2 mm, and the strain was gradually increased from 1% to 200% at 25 degC using a 25 mm parallel-plate probe with a gap setting of 2 mm and a frequency of 1 Hz. For creep-recovery response, Shear stress (8 Pa) was applied to the sample at 25 degC, and the change in strain with time was recorded for 5 min. Then, the stress was removed, and the change in strain with time was continuously recorded for 5 min . 2.7. Analysis of Microstructure of Acidic Whey Tofu Gelatin and Acidic Whey Tofu Acidic whey tofu gelatin and tofu was cut into thin slices of approximately 1.5 mm thickness and placed in 2.5% glutaraldehyde solution (0.1 M, pH 7.4, in phosphate buffer configuration) for 36 h. The samples were rinsed 3 times with phosphate buffer for 10 min each time. The samples were further dehydrated with an ethanol gradient (30%, 50%, 60%, 70%, 80%, and 90%) for 20 min each time and then dehydrated twice with anhydrous ethanol for 30 min each time. The dehydrated samples were replaced twice with tert-butanol for 30 min each. Finally, the samples were frozen with liquid nitrogen (-196 degC) and then vacuum freeze-dried. The dried samples were broken off and subjected to ion-sputtering gold spraying. The cross-sectional structure was observed using scanning electron microscopy (SEM) . 2.8. Determination of the Organic Acids in Acidic Whey Tofu After adding 20 mL of deionized water into the acidic whey tofu (5 g), the mixture was homogenized with a disperser for 1 min and stirred at room temperature for 30 min. The sample was centrifuged at 10,000x g for 10 min, following which the supernatant was collected and filtered through a 0.22 m membrane. The collected liquid was analyzed using high-performance liquid chromatography (Agilent 1200, Agilent Technologies, Inc., Santa Clara, CA, USA) with a Diamonsil C18 column (4.6 mm x 250 mm, 5 mm, Dikma Technologies Inc., Lake Forest, CA, USA). The mobile phase was methanol: water: phosphoric acid (5:95:0.05, volume ratio), and the flow rate was 0.6 mL/min at 30 degC. 2.9. Statistical Analysis All data were analyzed using the Statistical Package for the Social Sciences, SPSS 20 (IBM Corp., Chicago, IL, USA). The results are given as mean +- standard deviation (SD), significant differences in mean values were determined using Duncan's multiple range tests, p values of <0.05 were considered to be significant, and p < 0.01 were very significant. 3. Results and Discussion 3.1. Characterization of pH and Organic Acids during the Fermentation of Soybean Whey by Lactic Acid Bacteria The changes in the pH value during the fermentation of soybean whey by L. paracasei and L. plantarum were compared to obtain lactic acid bacteria that could use soybean whey with high acid production capacity. The results are shown in Figure 1A. The pH value of soybean whey decreased gradually as the fermentation process proceeded. The pH value decreased rapidly during the first 8 h of fermentation and then changed slowly. Compared with L. paracasei, the pH value of L. plantarum changed faster during the fermentation of soybean whey. The pH value was as low as 3.85 at the end of fermentation, indicating that L. plantarum produced acid faster and had a stronger acid production ability than L. paracasei. The changes in five organic acids, namely formic acid, lactic acid, acetic acid, citric acid, and succinic acid, during the fermentation of soybean whey by L. paracasei and L. plantarum are shown in Figure 1B,C, respectively. After soybean whey was fermented by L. paracasei and L. plantarum for 24 h, the total amount of the 5 organic acids increased substantially, which was consistent with the gradual decrease in pH value in soybean whey during the fermentation process. As shown in Figure 1B, the total amount of the 5 organic acids increased from 7.55 g/L to 14.61 g/L after 24 h of fermentation of soybean whey by L. paracasei, among which the lactic acid content increased from 0 g/L at the beginning to 7.45 g/L, accounting for 50.99% of the total acid content. However, the content of citric acid decreased, probably due to the consumption of bacteria, especially when L. paracasei was used. After the 24 h fermentation of soybean whey by L. plantarum, the total amount of the 5 organic acids increased from 7.55 g/L to 16.59 g/L, among which the lactic acid content increased from 0 g/L at the beginning to 8.02 g/L, accounting for 48.34% of the total acid content. In general, lactic acid and acetic acid were mainly produced during the fermentation of soybean whey by L. paracasei and L. plantarum. After 24 h of fermentation, the total amount of organic acids in soybean whey fermented by L. plantarum was higher than that of L. paracasei. 3.2. Acidic Whey Tofu Gelatin 3.2.1. Effect of Holding Temperature on the Gelation Condition, pH, Hardness, Water-Holding Capacity, and Microstructure of Gelatin The acidic whey prepared by the fermentation of L. paracasei and L. plantarum was used as a coagulant for tofu manufacture and held at 27 degC, 37 degC, 47 degC, 57 degC, and 67 degC for 6 h. The solidification of soybean milk is shown in Figure S2. Using acidic whey formed by L. paracasei fermentation, the acidic whey tofu gelation was formed only at 37 degC and 47 degC, while soybean milk remained in the liquid state at 27 degC, 57 degC, and 67degC. In contrast, using the acidic whey formed by L. plantarum fermentation, the tofu gelation was formed at all five holding temperatures. The properties of tofu gelatin prepared from coagulant fermented from L. paracasei or L. plantarum were determined. The results are shown in Table 1. Using coagulant fermented by L. paracasei and L. plantarum, the pH of tofu gelatin showed a tendency to decrease and then increase with the increasing holding temperature when the amount of coagulant added was 10%. At the same temperature (except 67 degC), the pH of tofu gelatin made with the coagulant fermented with L. plantarum was lower than that of tofu gelatin made with the coagulant fermented with L. paracasei. When the holding temperature was 37 degC, the pH value of tofu gelatin made with coagulants fermented with L. paracasei and L. plantarum reached the lowest value of 5.64 and 4.50, respectively. As the holding temperature increased, the water-holding capacity of tofu gelatin was the lowest at the holding temperature of 37 degC with the coagulant fermented with L. plantarum. At different holding temperatures, the hardness of tofu gelatin showed a trend of increasing and then decreasing with the coagulant fermented with L. plantarum. The hardness of tofu gelatin reached its maximum at the holding temperature of 37 degC, and the hardness of tofu gelatin made from L. plantarum was 2.5 times higher than that made from L. paracasei. The microstructure of tofu gelatin using coagulant fermented with both bacteria at different holding temperatures was observed by SEM . The pores of tofu gelatin formed by L. paracasei at 37 degC were uniform and dense. The tofu gelatin formed at a holding temperature of 47 degC had larger pores and a heterogeneous structure. However, tofu gelatin made from L. plantarum had a more uniform and orderly network structure than L. paracasei. The pores of tofu gelatin were smaller and more uniformly dense at the holding temperature of 37 degC than other temperatures. The tofu gelatin with a low pH value, high hardness, and a uniform and dense structure was obtained at the holding temperature of 37 degC using both L. L. plantarum-fermented coagulants. It might be because both L. paracasei and L. plantarum were able to grow and multiply better at 37 degC and facilitate acid production, thus promoting the slow binding of soy protein, achieving the best coagulation rate, and having the ability to encapsulate water, fat, and small-molecule proteins into the protein network structure to form a more orderly network structure. When the holding temperature was higher than 37 degC, the growth and reproduction of lactic acid bacteria were affected. Furthermore, the thermal movement between protein molecules was too fast, and the chances of mutual collision and binding were higher. The protein solidification rate is accelerated, resulting in a tofu gelatin network structure with larger holes and reduced hardness. When the holding temperature was lower than 37 degC, the growth of lactic acid bacteria and the protein movement were slower. Therefore, the gelation process might occur throughout the holding process, but the protein coagulation was slower, resulting in a weaker gelatin structure. 3.2.2. Effect of Coagulant on the Gelation Condition, pH, Hardness, Water-Holding Capacity, and Microstructure of Gelatin The properties of tofu gelatin produced by different coagulant additions are shown in Table 2. The solidification of soybean milk is shown in Figure S3. The pH of tofu gelatin decreased with the increase in the addition of a coagulant after 6 h of incubation. The pH of tofu gelatin started to approach 4.5 when the addition of the coagulant fermented with L. plantarum was higher than 10%. Using the coagulant fermented with L. paracasei, the pH of tofu gelatin was still above 5.5 when the coagulant was added at 16%. The water-holding capacity of tofu gelatin showed an overall decreasing trend with the addition of the coagulant, using coagulants fermented with both L. paracasei and L. plantarum. The hardness of tofu gelatin made from L. plantarum reached a maximum with a value of 57.22 g after a 10% addition of coagulant. The microstructure of tofu gelatin with different additions of coagulant fermented with L. paracasei and L. plantarum was observed by SEM . After adding 10% coagulant fermented with L. paracasei, the reticulation structure of tofu gelatin was clearly observed with small, dense, and evenly distributed pores. With the increase in the addition of coagulant, the structure was denser. The structure of tofu gelatin was uneven, and the pores formed were large when the concentration of coagulant fermented with L. plantarum was 4% and 7%. When the concentration of this coagulant was 10%, the pores of the tofu gelatin were small and evenly distributed. When the addition of coagulant was further increased, the pores of the tofu gelation were still relatively uniform and dense. The concentration of coagulant is an important factor affecting the quality of tofu gelatin. When the coagulant concentration is extremely low, the pH of soybean milk is much higher than the soybean protein isoelectric point, with the electrostatic repulsion in soybean protein dominating. Therefore, most proteins cannot cross-link to form a gelation network. When the coagulant concentration increases, the electrostatic repulsion between protein molecules weakens, and the gravitational force increases. Although the proteins can combine to form a gelatin network, the structure of the network is coarse and uneven, and the strength of gelatin is low, which makes it difficult to bind the small molecules. When the coagulant concentration continues to increase, the pH was lower than the protein isoelectric point . The gravitational force and the repulsive force between protein molecules reach an equilibrium, forming a uniform and orderly network structure. Other substances, such as small molecules of protein and water, are evenly distributed in the network structure, and the strength of gelation is higher. When the coagulant concentration increases further, the balance between the gravitational and repulsive forces among protein molecules is broken, and H+ makes the proteins positively charged, leading to electrostatic repulsion again. This results in the contraction of the gelatin network. The ability of the network to bind proteins and water, as well as the gelatin strength, decreases. When the tofu gelatin network is uniform and dense, it can better bind water, lipids, and other substances in the network structure. Additionally, the tofu gelatin formed is hard, and the yield of tofu is high . 3.2.3. Study of the Rheological Properties of Acidic Whey Tofu Gelatin The acidic whey fermented by L. paracasei and L. plantarum were used as the coagulants to understand the differences in the rheological properties of tofu gelatin. The variations in storage modulus (G') and loss modulus (G'') with time were measured for tofu gelatin at 37 degC with a 10% addition of coagulant . Initially, G' was smaller than G''. As time increased, G' increased rapidly, intersected with G'', and continued to rise; the intersection point was called the gelation point . Using coagulants fermented by L. paracasei and L. plantarum, G' was equal to G'' in 182.4 min and 132.9 min, respectively, and soybean milk started to gelatinize. Compared to L. paracasei, the coagulant fermented by L. plantarum required a shorter gelation time. The transformation of tofu gelatin from a liquid dispersion into a solid gelatin structure was completed during the holding process. During the cooling process, G' and G'' continued to rise, indicating that the structure of gelatin was gradually enhanced during the cooling process, probably because the cooling process facilitated the formation of hydrogen and ionic bonds, thus increasing the binding interaction between the proteins . It was also observed that the storage modulus G' was greater with coagulant fermented by L. plantarum, indicating greater gelatin strength , which was consistent with the data of gelatin hardness (Table 2). Frequency scans were performed on tofu gelatin samples to investigate further the viscoelasticity and force of coagulant-induced soy protein gelatin. As shown in Table S1, the magnitude of n reflected the nature of the forces in gelatin. When n was close to 0, it indicated that gelatin was chemical in nature and consisted of strong covalent bonds. When n was greater than 0, it indicated that the gelation was physical in nature, and the main forces were weak noncovalent bonds . The model fit results (shown in Table S1) with R2 greater than 0.99 indicated a good fit. Using coagulants fermented by L. paracasei and L. plantarum, the n value of tofu gelatin was 0.1156 and 0.1220, respectively, which was greater than 0, indicating that the tofu gelatin had weak physical gelatin. In addition, a correlation existed between the n value and gelatin strength. The larger the n value, the stronger its gelatin strength, which was consistent with the value of gelation endpoint G'. In summary, using coagulants fermented by L. paracasei and L. plantarum and comparing the pH value, water-holding capacity, hardness, and microstructure of tofu gelatin, a better quality of tofu gelatin was obtained when the amount of coagulant added was 10% and the holding temperature was 37 degC. 3.3. Evaluation of the Quality of Acidic Whey Tofu 3.3.1. Effect of pH, Water-Holding Capacity, Texture, and Structure of Acidic Whey Tofu Fermented Using Different Strains of Bacteria The acidic whey tofu production process requires pressure drainage to drain water from the tofu gelatin and reconstruct the texture. Pressurized water drainage can facilitate the binding of dispersed protein gelatin inside tofu, resulting in a more compact tofu structure. Naturally fermented tofu was added as a control to evaluate the difference in the quality of acidic whey tofu produced using coagulants fermented by L. paracasei and L. plantarum and naturally fermented acidic whey. The pH and water-holding capacity of tofu produced from the L. paracasei group, the L. plantarum group, and the naturally fermented acidic whey group are shown in Table 3. The pH value of tofu in the L. plantarum group was 4.64, and that in the naturally fermented group was 4.23, which were close to each other, while the pH value of tofu in the L. paracasei group was much higher at 5.62. The water-holding capacity was higher in the L. plantarum group, followed by the L. paracasei group, and the lowest in the naturally fermented group, indicating that the tofu of the L. plantarum group had a higher ability to bind free water. Table 3 provides the values of hardness, elasticity, cohesiveness, and chewiness parameters corresponding to the whole mass composition. As shown in Table 3, the elasticity of tofu in the L. paracasei group, the L. plantarum group, and the naturally fermented group was similar, which was 0.93, 0.92, and 0.93, respectively. The cohesiveness of tofu in the L. paracasei group was greater than that of tofu in the L. plantarum group and tofu in the naturally fermented acidic whey group. The hardness of tofu in the L. plantarum group and the naturally fermented group was similar, which was higher than the hardness of tofu in the L. paracasei group. Chewiness positively correlated with hardness, and the trend of chewiness variation and hardness variation in the three types of tofu was consistent. The hardness, elasticity, chewiness, and cohesiveness of tofu in the L. plantarum group were comparable to those in the naturally fermented group, indicating that the two types of tofu had similar structural properties. Figure 5 showed the appearance and microstructure of tofu manufactured from coagulants fermented by L. paracasei, L. plantarum, and natural bacteria. From the appearance, the tofu gelatin in the L. paracasei group adhered as a whole after pressing, with water overflowing from the surface of the tofu and having a smooth cut surface. The tofu in the L. plantarum group and the tofu in the naturally fermented group adhered during the pressing process, but gaps were created during the pressing process. The internal microstructure of the three groups of tofu was observed using SEM. The tofu in the L. paracasei group was relatively rough and porous, having holes of different sizes and an uneven structure. The tofu in the L. plantarum group and the tofu in the naturally fermented group had a more similar microstructure with a uniform and dense structure. The reason for the differences in the microstructure of the three types of tofu was probably that the tofu in the L. plantarum group and the tofu in the naturally fermented group could better promote soy protein gelatin and form a denser cross-linked structure, which also well-explained the differences in hardness and rheological properties of tofu. Thus, coagulants fermented by L. plantarum could be used as a new source of lactic acid bacteria tofu. 3.3.2. Comparison of the Rheological Properties of Acidic Whey Tofu As shown in Figure 6, the shear stress of 8 Pa was applied to tofu, and a transient strain was generated in the initial stage due to the purely elastic nature of the sample. Then, the strain increased rapidly due to the viscous nature of the sample, causing relaxation elasticity. Subsequently, the strain was reduced. When the stress was withdrawn, some of the deformations could be recovered. However, still, some deformation remained, indicating the viscoelastic nature of the sample . The fits for all 3 samples had R2 greater than 0.99, indicating good fits. As shown in Table 3, tofu in the L. plantarum group and the naturally fermented group had a larger G0 than tofu in the L. paracasei group, indicating that the former two had greater stiffness, which was consistent with the results of the texture measurements. The tofu in the L. plantarum group had the largest G1 and m0, while the tofu in the L. paracasei group had the smallest G1 and m0, which might be related to the internal forces during gelatinization. As shown in Figure 6, the strain scans for L. paracasei tofu, L. plantarum tofu, and naturally fermented tofu showed that the shear stress increased slowly in the beginning, then increased sharply, and finally decreased rapidly as the shear strain increased. The storage and loss moduli of the three species remained essentially unchanged at low strains, indicating that the three tofu species were not damaged in this strain range and could maintain their structural stability. The tofu in the L. plantarum and naturally fermented groups had greater yield stress than the tofu in the L. paracasei group, indicating that the former two had greater gelation strength. The tofu in the L. paracasei group fractured at 56% of strain, while the tofu in the L. plantarum and naturally fermented groups fractured at about 10% of strain, indicating that the tofu from the L. paracasei group was more deformable. The order of fracture stress for the three types of tofu was naturally fermented group tofu > L. plantarum group tofu > L. paracasei group tofu. The order of yield strain was L. paracasei group tofu > L. plantarum group tofu > naturally fermented group tofu. Thus, although the gelation strength was higher in the tofu in the L. plantarum and naturally fermented groups, the gelatin became more brittle as a result. 3.3.3. Comparison of the Organic Acid Content in the Acidic Whey Tofu The contents of organic acids in the three kinds of tofu were measured. The results are shown in Table 4. Seven organic acids were detected in the three acidic tofu, namely formic acid, malic acid, lactic acid, acetic acid, citric acid, succinic acid, and propionic acid, among which contents of lactic acid, acetic acid, and propionic acid were relatively high. The total amount of organic acids in L. paracasei tofu, L. plantarum tofu, and naturally fermented tofu was 12.87 g/L, 15.81 g/L, and 15.39 g/L, respectively. The total amount of organic acids in L. plantarum tofu and naturally fermented tofu was similar and higher than that in L. paracasei tofu. 4. Conclusions In this present study, acidic whey tofu was prepared using coagulants fermented by either L. paracasei or L. plantarum as the coagulant. Based on the pH, water-holding capacity, hardness, and microstructure of tofu gelatin, good-quality tofu gelatin was obtained when the ratio of coagulant was 10%, and the holding temperature was 37 degC. The quality of tofu produced by pure bacterial fermentation was compared with that produced by natural fermentation under optimal gelatin preparation conditions. It was found that the tofu produced by L. paracasei-fermented coagulant had higher pH, less hardness, and a rougher network structure, while the tofu produced by L. plantarum-fermented coagulant was closer to the tofu produced by natural fermentation in terms of pH, texture, rheology, and microstructure. Supplementary Materials The following supporting information can be downloaded at: Figure S1: The processing procedure for the manufacture of acidic whey tofu; Figure S2: Effect of different temperatures on tofu gelatin induced by coagulant fermented using L. paracasei (A) and L. plantarum (B); Figure S3: Effect of amount of coagulant fermented using L. paracasei (A) and L. plantarum (B) on tofu gelatin; Table S1: Parameters of rheological properties for tofu gelatin induced by coagulant fermented using L. paracasei and L. plantarum. Click here for additional data file. Author Contributions Z.G.: Investigation, Methodology, Writing--original draft; J.Z.: Methodology, Writing--review and editing; S.Z.: Methodology, Writing--review and editing; Y.H.: Methodology, Writing--review and editing; Y.L.: Methodology, Writing--review and editing; J.M.R.: Methodology, Writing--review and editing; Y.X.: Methodology, Writing--review and editing; P.Z.: Methodology, Writing--review and editing. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Data is contained within the article or Supplementary Materials. Conflicts of Interest The authors confirm that they have no conflict of interest with respect to the work described in this manuscript. Figure 1 Changes of pH during the fermentation of acidic whey using L. paracasei and L. plantarum (A). Changes of organic acids in acidic whey during the fermentation using L. paracasei (B) and L. plantarum (C). Note: Different letters of the same column filling mean significant differences (p < 0.05). Figure 2 SEM images of tofu gelatin induced by coagulant fermented using L. paracasei (A) and L. plantarum (B) at different temperatures. Figure 3 SEM images of tofu gelatin induced by different percentage of L. paracasei (A) and L. plantarum (B) fermented coagulant. Figure 4 Time sweep G' and G'' of tofu gelatin induced by coagulants fermented by L. paracasei (A) and L. plantarum (B). Frequency sweep G' and G'' of tofu gelatin induced by coagulants fermented by L. paracasei (C) and L. plantarum (D). Figure 5 Pictures of tofu manufactured from coagulants fermented by L. paracasei (A1), L. plantarum (B1), and natural bacteria (C1). SEM images of tofu manufactured from coagulants fermented by L. paracasei (A2), L. plantarum (B2), and natural bacteria (C2). Figure 6 Creep-recovery curve (A), strain creep curves (B), and changes in G' and G'' as a function of strain (C) of tofu manufactured from coagulant fermented by L. paracasei (A), L. plantarum (B), and natural bacteria (C). foods-12-00918-t001_Table 1 Table 1 Effect of different temperatures on properties of tofu gelatin induced by coagulants fermented using L. paracasei and L. plantarum. Temperature/degC pH Water-Holding Capacity (%) Hardness (g) L. paracasei L. plantarum L. paracasei L. plantarum L. paracasei L. plantarum 27 6.34 +- 0.03 c 5.51 +- 0.04 c - 76.6 +- 1.7 bc - 23 +- 1 b 37 5.64 +- 0.02 a 4.50 +- 0.02 a 79 +- 4 70.2 +- 0.4 a 20.2 +- 0.6 57 +- 2 c 47 5.70 +- 0.03 b 5.26 +- 0.01 b 84 +- 2 75.4 +- 2.8 ab 14.7 +- 2.2 41 +- 4 d 57 6.39 +- 0.01 d 6.18 +- 0.02 d - 80.2 +- 2.8 bc - 17 +- 2 a 67 6.28 +- 0.02 c 6.27 +- 0.02 d - 81.6 +- 1.6 c - 13 +- 4 a Note: '-' indicates unmeasured; means followed by different letters as superscripts in a column are significantly different (p < 0.05). foods-12-00918-t002_Table 2 Table 2 Effect of different percentages of L. paracasei--and L. plantarum--fermented coagulant on the properties of tofu gelatin. Percentage (%) pH Water-Holding Capacity (%) Hardness (g) L. paracasei L. plantarum L. paracasei L. paracasei L. plantarum L. paracasei 4 6.36 +- 0.01 d 5.55 +- 0.01 d - 75.5 +- 0.3 a - 46 +- 2 a 7 6.09 +- 0.02 c 5.17 +- 0.02 c - 72.0 +- 1.4 a - 49 +- 3 ab 10 5.64 +- 0.03 b 4.50 +- 0.02 b 79 +- 3 a 70.2 +- 0.4 a 20.2 +- 0.6 a 57 +- 2 ab 13 5.59 +- 0.03 b 4.42 +- 0.01 a 77 +- 1 a 72.2 +- 2.8 a 21.5 +- 0.5 a 48 +- 5 ab 16 5.51 +- 0.01 a 4.35 +- 0.03 a 76 +- 2 a 70.5 +- 7.1 a 21.5 +- 0.2 a 54 +- 5 b Note: '-' indicates unmeasured; means followed by different letters as superscripts in a column are significantly different (p < 0.05). foods-12-00918-t003_Table 3 Table 3 pH, water-holding capacity, TPA parameters, and parameters of Burger's model for the creep behavior of tofu manufactured from coagulants fermented by L. paracasei, L. plantarum, and natural bacteria. Index L. paracasei L. plantarum Natural Bacteria pH 5.62 +- 0.03 c 4.64 +- 0.04 b 4.23 +- 0.03 a Water-holding capacity (%) 89.8 +- 1.4 a 92.1 +- 0.8 b 88.6 +- 0.8 a Hardness (g) 212 +- 5 a 338 +- 38 b 337 +- 21 b Springiness 0.93 +- 0.02 a 0.92 +- 0.01 a 0.93 +- 0.03 a Cohesiveness 0.83 +- 0.01 b 0.79 +- 0.01 a 0.79 +- 0.01 a Chewingness (g) 164 +- 1 a 246 +- 26 b 247 +- 9 b G0/x103 Pa 0.81 +- 0.01 a 6.49 +- 0.07 b 7.76 +- 0.13 c G1/x103 Pa 0.85 +- 0.01 a 9.12 +- 0.14 c 6.93 +- 0.11 b l/s 36.8 +- 1.3 b 27.7 +- 0.9 a 38.3 +- 1.5 b m0/x105 Pa 3.23 +- 0.08 a 36.34 +- 0.66 c 9.43 +- 0.09 b Note: Means followed by different letters as superscripts in the same arrow are significantly different (p < 0.05). G0 indicated the hardness of tofu. G1 indicated the cohesion of tofu. l indicated the time required to reach the maximum deformation. m0 indicated the viscosity of tofu. foods-12-00918-t004_Table 4 Table 4 Organic acids in tofu manufactured from coagulant fermented by L. paracasei and L. plantarum and natural bacteria. Organic Acids/g/L L. paracasei L. plantarum Natural Bacteria Formic acid 0.07 +- 0.01 a 0.12 +- 0.01 b 0.15 +- 0.01 c Malic acid 0.24 +- 0.01 c 0.18 +- 0.00 b 0.11 +- 0.02 a Lactic acid 3.60 +- 0.09 a 6.37 +- 0.01 b 3.72 +- 0.03 a Acetic acid 1.70 +- 0.02 a 1.98 +- 0.02 b 2.43 +- 0.02 c Citric acid 0.19 +- 0.01 a 0.24 +- 0.03 b 0.19 +- 0.01 a Succinic acid 0.21 +- 0.00 a 0.23 +- 0.01 b 0.73 +- 0.00 c Propionic acid 6.86 +- 0.01 a 6.70 +- 0.01 a 8.06 +- 0.77 a Total contents 12.87 +- 0.01 a 15.81 +- 0.01 b 15.39 +- 0.75 b Note: Means followed by different letters as superscripts in the same arrow are significantly different (p < 0.05). 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PMC10000491 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051101 foods-12-01101 Article Ethanol Extract of Mao Jian Green Tea Attenuates Gastrointestinal Symptoms in a Rat Model of Irritable Bowel Syndrome with Constipation via the 5-hydroxytryptamine Signaling Pathway Wu Lei Methodology Software Investigation Writing - original draft 12 Gao Liming Investigation 2 Jin Xiang Investigation 1 Chen Zhikang Investigation 2 Qiao Xutong Investigation 2 Cui Xiting Investigation 2 Gao Jianhua Writing - review & editing Supervision Project administration Funding acquisition 2* Zhang Liwei Methodology Funding acquisition 1* Eduardo-Figueira Maria Academic Editor Direito Rosa Academic Editor 1 Institute of Molecular Science, Shanxi University, Taiyuan 030006, China 2 Shanxi Key Laboratory of Minor Crops Germplasm Innovation and Molecular Breeding, College of Life Sciences, Shanxi Agricultural University, Taigu, Jinzhong 030801, China * Correspondence: [email protected] (J.G.); [email protected] (L.Z.) 04 3 2023 3 2023 12 5 110117 1 2023 17 2 2023 27 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). In a previous study, we demonstrated that the hydro extract of Mao Jian Green Tea (MJGT) promotes gastrointestinal motility. In this study, the effect of MJGT ethanol extract (MJGT_EE) in treating irritable bowel syndrome with constipation (IBS-C) in a rat model constructed via maternal separation combined with an ice water stimulation was investigated. First, a successful model construction was confirmed through the determination of the fecal water content (FWC) and the smallest colorectal distension (CRD) volume. Then, the overall regulatory effects of MJGT_EE on the gastrointestinal tract were preliminarily evaluated through gastric emptying and small intestinal propulsion tests. Our findings indicated that MJGT_EE significantly increased FWC (p < 0.01) and the smallest CRD volume (p < 0.05) and promoted gastric emptying and small intestinal propulsion (p < 0.01). Furthermore, mechanistically, MJGT_EE reduced intestinal sensitivity by regulating the expression of proteins related to the serotonin (5-hydroxytryptamine; 5-HT) pathway. More specifically, it decreased tryptophan hydroxylase (TPH) expression (p < 0.05) and increased serotonin transporter (SERT) expression (p < 0.05), thereby decreasing 5-HT secretion (p < 0.01), activating the calmodulin (CaM)/myosin light chain kinase (MLCK) pathway, and increasing 5-HT4 receptor (5-HT4R) expression (p < 0.05). Moreover, MJGT_EE enhanced the diversity of gut microbiota, increased the proportion of beneficial bacteria, and regulated the number of 5-HT-related bacteria. Flavonoids may play the role of being active ingredients in MJGT_EE. These findings suggest that MJGT_EE could serve as a potential therapeutic pathway for IBS-C. Mao Jian Green Tea ethanol extract gastrointestinal motility 5-hydroxytryptamine gut microbiota flavonoids Shanxi Agricultural University Youth Science and Technology Innovation Fund2016020 Shanxi Key Laboratory of Minor Crops Germplasm Innovation and Molecular Breeding, Shanxi Agricultural University202105D121010 This research was funded by Shanxi Agricultural University Youth Science and Technology Innovation Fund, grant number 2016020 and Shanxi Key Laboratory of Minor Crops Germplasm Innovation and Molecular Breeding, Shanxi Agricultural University, grant number 202105D121010. pmc1. Introduction Irritable bowel syndrome (IBS) is a common gastrointestinal disease associated with changes in gastrointestinal motility, secretion, and visceral sensation. It manifests clinically mainly as abdominal pain accompanied by intermittent or persistent irregular bowel movements, as well as abnormalities in stool texture and shape . Several basic and clinical studies have investigated the etiology of IBS from different perspectives, including the effects of genetic factors, low-grade mucosal inflammation and immune activation following severe gastrointestinal infection, increased intestinal mucosal permeability, changes in gut microbiota, abnormalities in bile salt metabolism, allergies to certain dietary components, abnormalities in neurotransmitter pathways, and changes in brain function . Although the pathogenesis of IBS has not yet been fully elucidated, researchers speculate that hypersensitivity and alteration in visceral perception as well as gastrointestinal dysmotility form the main pathophysiological basis of the disorder . IBS can be divided into four subtypes according to the Rome IV criteria: IBS with constipation (IBS-C), IBS with predominant diarrhea (IBS-D), IBS with mixed bowel habits (IBS-M), and IBS unclassified (IBS-U) . Approximately one third of all IBS cases are of the IBS-C subtype . Medical treatments for IBS often yield unsatisfactory results, thereby imposing a heavy disease burden on patients . For IBS-D, most clinicians recommend the use of serotonin type 3 receptor (5-HT3R) antagonists to block the excessive action of 5-HT on 5HT3R and reduce intestinal motility. Common medications used for IBS-C treatment include the serotonin type 4 receptor (5-HT4R) agonists, prucalopride and tegaserod , the type 2 chloride channel activator, lubiprostone , and the guanylate cyclase C agonists, linaclotide and plecanatide , which can promote intestinal peristalsis. In effect, tegaserod has already been approved for use by the U.S. Food and Drug Administration for the treatment of IBS-C. However, there are age-related limitations and contraindications to the use of lubiprostone and tegaserod, with the latter only being approved for use in a limited IBS-C patient population (women aged < 65 years without cardiovascular disease risk-related contraindications) . Only a few studies have investigated the effects of lubiprostone in Asian patients; therefore, its use in the treatment of IBS-C has not been recommended in South Korea and Japan . Given the scarcity of IBS-specific drugs, the treatment of the disease often requires the introduction of other adjuvant strategies, such as good lifestyle habits (eating regular meals and increasing dietary fiber intake), traditional Chinese medications or acupuncture , or acupoint catgut embedding that contribute to improving the condition of the patient. During history, herbal medicines have also been developed by several countries and regions with specialties to deal with various diseases. Some of them can treat or relieve gastrointestinal disorders. For example, the herbal therapy STW-5 (Iberogast(r)) including angelica roots (Angelicae radix), chamomile flowers (Matricariae flos), caraway fruit (Carvi fructus), St. Mary's thistle fruit (Cardui mariae fructus), balsam leaves (Melissae folium), peppermint leaves (Menthae x piperitae), greater celandine (Chelidonii herba), and licorice root (Liquiritiae radix) has been in clinical use in German-speaking countries for decades and is sold as an over-the-counter medicine in Europe. It acts on 5-HT4, 5-HT3, muscarinic M3, and opioid receptors to relieve intestinal spasm and reduce gastric acid secretion . There is much evidence that peppermint oil reduces visceral pain and modulates gastrointestinal motility via TRPM8 and/or TRPA1 receptors . Curcumin, contained in turmeric (Curcuma longa), treats abdominal pain as well as other gastrointestinal symptoms present in IBS . Atractylodes lanceolata oil was able to ameliorate the rat IBS-D by inhibiting the SCF/c-kit pathway, thereby reducing inflammation and protecting the intestinal barrier from damage via the MLCK/MLC2 pathway . Dracocephalum rupestre Hance, called Mao Jian Cao (MJC) in Chinese, is a perennial herb of the Dracocephalum genus and the Lamiaceae family that is native to the Northern Shanxi Province of China. MJC is a traditional Chinese medicine, with the effect of relieving headaches, soothing sore throats, subsiding coughs and preventing icterohepatitis . MJC is rich in flavonoids, among which dihydroflavonoids and their corresponding glycosides such as luteolin, luteolin-7-O-b-D glucoside, eriodictyol, and eriodictyol-7-O-b-D glucoside, and terpenoids such as b-sitosterol, betulinol, and betulinic acid, are representative components . Interestingly, the herbal tea made from its leaves as a daily drink to aid digestion is a more popular way. This is because people in these regions often consume the slower-digesting coarse grains. From June ending to September each year, fresh MJC leaves are harvested by locals for making Mao Jian tea (MJT), including MJGT (green tee) or MJBT (black tea). The making method could lead to the production of different metabolites . For example, 130, 136, and 95 compounds were detected in the MJC, MJGT, and MJBT, respectively. There were 28 differential metabolites in MJGT compared to MJC; MJBT had 29. The MJGT-making method led to the significant intensity of some flavonoids such as apigenin, eriodictyol, luteolin, and naringenin, whereas the corresponding glycosides of eriodictyol and luteolin decreased. Interestingly, a similar trend was observed in MJBT, except that the content of some flavonoid glycosides decreased sharply, including the 7-O-glucoside of the four flavonoids mentioned above. Common green tea is made from the steamed and dried leaves of the Camella sinesis plant. The main active ingredients include tea polyphenols and tea polysaccharides, which have anticancer, antioxidant, neuroprotective, and hypoglycemic pharmacological activities . Green tea contains caffeine (~3%) , which enhances the autonomic activity of the vagus nerve, releases acetylcholine, and promotes gastrointestinal motility , but such ingredients can also cause euphoria and insomnia after consumption. The caffeine content of MJC is very low at 0.495%, so it does not affect sleep after consumption . In addition, caffeine is one of the main components that form the bitter taste of the tea ; therefore, MJC has a lighter taste compared to other common green teas. Flavonoids have multiple effects on the gastrointestinal tract, including (1) protecting the intestinal epithelium from drug damage and food toxins; (2) regulating the activity of enzymes involved in lipid and carbohydrate absorption; (3) maintaining the intestines of the intestinal barrier; (4) regulating the secretion of intestinal hormones; (5) modulating the gastrointestinal immune system; (6) exerting potential anti-colorectal cancer activity; and (7) shaping the composition of the bacterial flora . For example, quercetin inhibits gastrointestinal toxicity induced by diclofenac and aggravated by ranitidine, improves gastrointestinal bleeding, intestinal permeability, and restores intraluminal pH in rats . The ability of polyphenols in oranges and apples to alter the microbiota of systemic lupus erythematosus (SLE) patients, with their flavonoids increasing the levels of lactobacilli and dihydroflavonols increasing the levels of bifidobacteria, suggests the possibility of correcting the ecological dysbiosis associated with SLE by altering the flavonoid diet . Apigenin showed a dose-dependent relaxation effect on acetylcholine (ACh)-induced muscle strips in the concentration range of 0.1 to 100 mmol/L. Luteolin and quercetin showed a similar performance to apigenin with the exception that, at low doses (0.001-0.1 mmol/L), they were able to further increase the induction effect of ACh . Previously, we demonstrated that MJGT promotes small intestinal propulsion and gastric emptying in normal rats and improves gastrointestinal motility by increasing the abundance of beneficial bacteria . Flavonoids constituted the main active ingredients in MJGT. Considering the easier concentration and higher efficiency for the extraction of flavonoids without the concerns of impacts on toxicity and biodegradability , we chose ethanol as the extraction solvent in the present study. A rat model of IBS-C was treated with the ethanolic extract of MJGT (MJGT_EE), and the response of the key enzymes and downstream targets of the serotonin (5-hydroxytryptamine; 5-HT) biosynthesis pathway, which is an essential signaling pathway in the gastrointestinal tract, was investigated. 2. Materials and Methods 2.1. Sample Collection MJGT was purchased from Jiufeng Cooperative (Ningwu County, Shanxi Province, China) in December 2018, and samples were conserved at the Chinese Medicine Resources and Sciences Laboratory of Shanxi Agricultural University (JF18001-2). 2.2. Preparation of MJGT_EE MJGT (200 g) was subjected to heat reflux extraction in 4 L of 70% ethanol for 60 min at 70 degC followed by vacuum concentration for ethanol recovery; then, the ethanol extract obtained was dried and stored at 4 degC until use. 2.3. Animal Grouping, Construction of the IBS-C Model, and Sample Collection Six pregnant specific-pathogen-free (SPF) rats were purchased from Si Pei Fu Biotechnology Co., Ltd. (Beijing, China). The rats were provided clean water, fed daily, and reared under a 12-h light-dark cycle. At 7 days of age, 24 offspring rats were randomly selected and subjected to 3 h of maternal separation from 9 am to 12 noon daily for 14 days. Subsequently, the rats were assigned to three groups: the model (MG), positive drug (MSP) (1 mg/kg of mosapride), and 70% MJGT ethanol extract (MJGT_EE) (17 mg/mL, determined based on the daily dose for humans, with 0.1% dimethyl sulfoxide added in each group for solubilization) groups. Eight rats that were not subjected to maternal separation were assigned to the negative control (NC) group (saline). With the exception of animals in the NC group, animals in all the other groups were administered ice water at 0-4 degC (1.5 mL/rat) via gavage for 14 days. A fecal water content (FWC) measurement and intestinal sensitivity testing were performed to confirm successful IBS-C modeling. Subsequently, drug administration was performed in the different groups for 30 days via gavage. Next, rats were selected from each group and sacrificed. Then, two 5 x 5-mm proximal colonic tissue specimens were collected from each sacrificed rat and washed thrice with saline for intestinal content removal. One specimen was fixed in 4% paraformaldehyde for immunohistochemical analysis, and the other was stored at -80 degC for western blot analysis. In addition, the cecal contents of the sacrificed rats were collected in 1 mL sterile centrifuge tubes and immediately stored at -80 degC. All specimens were transported on dry ice prior to testing. All animal experiments were approved by the laboratory animal ethics committee of Shanxi Agricultural University (Taigu, China) (Approval No.: SXAU-EAW-2018R.0406001) and performed in accordance with the regulations and guidance of this committee. 2.4. Measurement of FWC On days 14 and 28 of the IBS-C model construction and drug administration periods, respectively, the rats were separated with each rat reared individually, and the amount of feces passed out within 24 h by the rats in each group was recorded for FWC calculation. Then, the wet weight of the feces was measured using an electronic balance; next, the feces was dried at 105 degC to a constant weight and the dry weight of the feces was recorded. FWC was calculated using Equation (1). water content% = [wet weight of feces (g) - dried weight of feces (g)]/wet weight of feces (g) x 100% (1) 2.5. Measurement of Intestinal Sensitivity The smallest threshold colorectal distention (CRD) volume was also measured on days 14 and 28 of the IBS-C model construction and drug administration periods, respectively. Each rat was anesthetized using a small amount of diethyl ether and placed in a rat holder. Then, a glycerol-lubricated urinary catheter with an attached balloon was inserted into the colorectum of each rat and taped to the base of the tail, with the end of the balloon positioned approximately 1 cm away from the anus. When the rats regained consciousness and were fully acclimatized to the environment for 30 min, normal saline at 26-28 degC was injected into the balloon, and the smallest injection volume that induced CRD in the rats was recorded. This process was repeated thrice at 15-min intervals, and the smallest threshold volume was calculated by taking the average of the three volumes. 2.6. Effects of MJGT_EE on Gastric Emptying and Small Intestinal Propulsion After continuous gavage for 29 days, the rats were starved for 24 h but allowed access to water. A semi-solid paste was prepared following a slightly modified version of the method described by ; first, 10 g of sodium carboxymethyl cellulose was dissolved in 250 mL of distilled water. Then, 16 g of milk powder, 8 g of glucose, 8 g of starch, and 2 g of activated charcoal powder were added to this solution, and the resulting mixture was uniformly mixed to obtain 300 mL of a black semi-solid paste. This paste was stored in a refrigerator and warmed to a temperature of 20 degC before use. At the end of the drug administration period (day 30), 2 mL of the semi-solid paste was measured (Mp: mass of paste) and administered to each rat by gavage. Forty minutes following administration, the animals were anesthetized using pentobarbital sodium (40 mg/kg) and sacrificed. Then, the total mass of the stomach (Mfs), the net mass of the stomach (Mns), the total distance from the pylorus to the ileocecal junction (Lt), and the distance from the pylorus to the front edge of the black semi-solid paste (Lc) were measured. The gastric emptying and small intestinal propulsion rates were calculated using Equations (2) and (3), respectively, as represented below:Gastric emptying rate (%) = [1 - (Mfs - Mns)/Mp] x 100%(2) Small intestinal propulsion rate (%) = (Lc/Lt) x 100%(3) 2.7. Hematoxylin and Eosin (H&E) Staining and Immunohistochemistry For H&E staining, colonic tissues were fixed in 10% neutral buffered formalin solution, sectioned, deparaffinized at 65 degC, rehydrated, and stained using an H&E staining kit (Solarbio, G1121). For immunohistochemical analyses, colonic tissue specimens were sectioned, deparaffinized, and rehydrated. High-temperature antigen retrieval was performed on the tissue specimens using trisodium citrate, and endogenous peroxidase activity and non-specific binding sites in the specimens were blocked with H2O2 and goat serum, respectively (Zhongshan Jinqiao ZLI-9022). Anti-5-HT antibodies (primary antibodies; 1:1000) were added to the tissue sections and incubated at 4 degC for 12 h. Next, goat anti-rabbit IgGs (secondary antibodies; 1:100) and the peroxidase-antiperoxidase complex (PAP; 1:100) were successively added to the samples and incubated for 1 h at 37 degC each time; staining was performed using diaminobenzidine (DAB)/H2O2. The sections were adequately rinsed with 0.01 mol/L PBS (Na2HPO4 8 mM, NaCl 136 mM, KH2PO4 2 mM, KCL 2.6 mM, pH: 7.4) in between the steps described above. After staining, the sections were mounted onto gel-coated slides, dehydrated using graded alcohol, cleared in xylene, mounted, and observed under an optical microscope (Olympus BX-51 biological microscope, white light, Japan, Olympus). Five high-power (200x) fields of view were randomly selected for the calculation of the average optical density (AOD, IOD/Area) using Image-Pro Plus 6.0 (Media Cybernetics, Silver Spring, MD, USA). 2.8. Western Blot Analysis For each rat, 50 mg of colonic tissue was precisely weighed and placed in an Eppendorf tube. First, an appropriate amount of protease inhibitor-containing cell lysis buffer was added to the tissue and the mixture was homogenized using an electric homogenizer. Next, the sample loading buffer was added to the homogenate, and the mixture was boiled for 5 min; then, the resulting mixture was subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Separated proteins were transferred onto a polyvinylidene fluoride (PVDF) membrane and blocked with 5% skimmed milk powder. Second, primary antibodies against 5-hydroxytryptamine receptor 3 (5-HT3R; bs-2126R), 5-hydroxytryptamine 4 receptor (5-HT4R; bs-12054R), the serotonin transporter (SERT, bs-1893R), tryptophan hydroxylase 1 (TPH1; bs-1215R), tryptophan hydroxylase 2 (TPH2; bs-8729R), calmodulin (CaM; bs-3666R), or myosin light chain kinase (MLCK) (Bioss Biotechnology Co., Ltd., Beijing, China) were added (1:1000) to the membrane and incubated at 4 degC for 12 h. Next, the membrane was washed thrice with TBST buffer (T1081, Solarbio Science & Technology Co., Ltd., Beijing, China); then, secondary antibodies (HRP-conjugated Affinipure Goat Anti-Mouse IgG (H+L) or HRP-conjugated Affinipure Goat Anti-Rabbit IgGs (H+L); 1:5000) were added to the membrane and incubated at room temperature for 1 h. Finally, at the end of the incubation, the membrane was again washed thrice with the TBST buffer, developed, exposed in a dark room, and imaged using a ChemiDoc MP Imaging System (Bio-Rad Laboratories Inc., Hercules, CA, USA). GAPDH or a-tubulin was used as the housekeeping protein. 2.9. 16S rDNA Sequencing DNA extraction: Total microbiota DNA was extracted from rat fecal samples using the E.Z.N.A.(r) soil DNA kit (Omega Bio-Tek, Norcross, GA, USA) following the instructions of the manufacturer. The quality of the extracted DNA was evaluated via 1% agarose gel electrophoresis, and DNA concentration and purity were measured using the NanoDrop2000 (Thermo Fisher Scientific, Waltham, MA, USA) device. 16S rRNA gene amplification and sequencing through the polymerase chain reaction (PCR): The V3-V4 variable regions of the 16S rRNA gene were subjected to PCR (ABI GeneAmp(r) 9700, ABI, Los Angeles, CA, USA) using the 338F (5'-ACTCCTACGGGAGGCAGCAG-3') and 806R (5'GGACTACHVGGGTWTCTAAT-3') primer sequences under the following cycling conditions: initial denaturation at 95 degC for 3 min, 27 cycles of denaturation at 95 degC for 30 s, annealing at 55 degC for 30 s, extension at 72 degC for 30 s, stable extension at 72 degC for 10 min, and storage at 4 degC. The PCR reaction system was constituted of 4 mL of 5xTransStart FastPfu buffer, 2 mL of 2.5 mM dNTPs, 0.8 mL of forward primer (5 mM), 0.8 mL of reverse primer (5 mM), 0.4 mL of TransStart FastPfu DNA polymerase, 10 ng of template DNA, and ddH2O to make up a final volume of 20 mL. PCR was performed in triplicate for each sample. Illumina Miseq sequencing: DNA fragments were recovered from a 2% agarose gel after mixing, purified using the AxyPrep DNA Gel Extraction Kit (Axygen, San Francisco, CA, USA), detected using 2% agarose gel electrophoresis, and quantified using a QuantusTM Fluorometer (Promega, Madison, WI, USA). Sequencing libraries were constructed using the NEXTFLEX Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA) according to the following steps: (1) adaptor ligation; (2) magnetic bead screening for the removal of self-ligated adaptors; (3) library template enrichment via PCR amplification; (4) magnetic bead recovery of PCR products to obtain the final sequencing libraries. Sequencing was ultimately performed on the Illumina MiSeq PE300 platform (Majorbio Bio-Pharm Technology Co., Ltd., Shanghai, China), and raw sequencing data were uploaded to the NCBI Sequence Read Archive (SRA) (Accession No.: PRJNA906308). Data processing: Reads were filtered by removing bases with tail quality values of less than 20 using a 50-bp window. If the average quality value within the window was less than 20, bases were trimmed from the back end starting from the window. Reads with lengths < 50 bp after quality control were filtered and those containing N bases were removed. Based on the extent of overlap between the paired-end reads, read pairs were merged into a sequence with a minimum overlap length of 10 bp. Sequences that exceeded the maximum overlap region mismatch ratio allowed (0.2) were removed. Samples were distinguished based on the barcodes at the head and tail ends of sequences and primers, and sequence directions were adjusted based on the number of permitted mismatches (allowable barcode mismatches: 0; maximum allowable primer mismatches: 2). Using the UPARSE software version 7.1, accessed on 20 June 2021) package, operational taxonomic unit (OTU) clustering was performed based on a 97% similarity threshold, and chimeric sequences were removed. Each sequence was subjected to species classification and annotation using the RDP classifier and compared against the SILVA 16S rRNA database (version 138), with the confidence threshold set at 70%. 2.10. Identification of the Four Chemical Component Types in MJGT_EE with HPLC Chromatographic conditions: Chromatographic system: Agilent Technologies; chromatographic column: Agilent 5 TC-C18(2), 250 mm x 4.6 mm, 5 mm; flow rate: 1 mL/min; column temperature: 25 degC; injection volume: 10 mL; mobile phase: 0.3% acetic acid (A)-methanol (B) (0-22 min: 32% B, 22-23 min: 32-37% B, 23-36 min: 37% B, 36-37 min: 37-45% B, 37-46 min: 45% B, 46-47 min: 45-60% B, 47-60 min: 60-80% B); UV absorption of eriodictyol and eriodicty-7-O-glucoside was monitored at 284 nm, while monitoring of luteolin and luteolin-7-O-glucoside was at 350 nm.. Preparation of mixed control solution (S1): A mixed solution containing eriodictyol-7-O-glucoside (0.348 mg/mL), eriodictyol (0.200 mg/mL), luteolin-7-O glucoside (0.270 mg/mL), and luteolin (0.156 mg/mL) in methanol was prepared as the control. Preparation of test solution (S2): Dried MJGT was pulverized and passed through a 40-mesh sieve. A total of 1.7 g of MJGT was precisely weighed and placed in a 250-mL distillation flask. Then, 70% ethanol was added to the flask, which was securely stoppered and weighed. The contents of the flask were subjected to heat reflux extraction for 60 min and cooled to room temperature. Then, 70% ethanol was added to the flask to make up for the lost weight, and the contents of the flask were filtered through a 0.22-mm organic filtration membrane to obtain the test solution. 2.11. Statistical Analysis All data are expressed as the mean +- standard error of the mean (SEM). SPSS version 26.0 (SPSS, Inc., Chicago, IL, USA) was used for statistical comparison of data via one-way analysis of variance (ANOVA). Differences were considered statistically significant when p was less than 0.05. Lowercase and uppercase letters were used to denote the results of comparisons at significance levels of 0.05 and 0.01, respectively. All graphs were plotted using GraphPad Prism version 7.0 (GraphPad software, Inc., La Jolla, CA, USA). 3. Results 3.1. Evaluation of the IBS-C Model Figure 1A shows the process flow diagram for model construction and administration. There was a significant decrease in FWC in the MG group . However, rats administered MJGT_EE or MSP exhibited a significant recovery in FWC, with the recovered FWC in the MSP group being similar to that in the NC group (after administration). Visceral sensitivity changes constitute some of the most important pathophysiological characteristics of IBS patients. In this study, the smallest threshold CRD volume was adopted as a measure of visceral sensitivity in the different groups. A significant decrease in the smallest threshold CRD volume in the MG group was observed , indicating a significant increase in rat visceral sensitivity. After drug administration, the smallest threshold CRD volume was restored to normal levels in the MJGT_EE and MSP groups as compared to the MG group . 3.2. Effects of MJGT_EE on Gastric Emptying and Small Intestinal Propulsion in IBS-C Rats Previous studies have demonstrated that IBS-C patients exhibit delayed gastric emptying and small intestinal transit . Therefore, these two indicators were selected and evaluated in our in vivo experiments. As compared to rats in the NC group, those in the MG group exhibited a significant decrease in gastric emptying and small intestinal propulsion rates (p < 0.01). MJGT_EE administration restored both gastric emptying and small intestinal propulsion rates to levels similar to those in the NC group (p < 0.01); the treatment effects of MJGT_EE were in line with those of MSP . 3.3. Effect of MJGT_EE on the Colonic Tissue Morphology Rat colonic tissues were subjected to H&E staining for morphological evaluation. Clear structures were observed in the various colonic tissue layers. Mucosal epithelial cells exhibited a simple columnar structure, with cells and glands arranged in an orderly manner; in addition, normal colonic crypts were present. No significant inflammatory cell infiltration or pathological damage, interstitial hyperemia or edema, ulcerations, or organic lesions were observed. These findings indicated that the method used for model construction did not induce organic lesion development , and that both the MJGT_EE and MSP treatments had no effects on rat tissue morphology. 3.4. Evaluation of the Accumulation of 5-HT in the Colonic Tissue Impacted by MJGT_EE To determine whether MJGT_EE affects 5-HT expression, 5-HT accumulation in rat colonic tissues was evaluated with the immunohistochemical method. As shown in Figure 4, 5-HT was mainly distributed in the submucosal and muscular layers of the colon. Calculated AOD values indicated that colonic 5-HT secretion significantly increased in the MG group as compared to the NC group , suggesting that the model construction method induced an increase in colonic 5-HT levels. After MJGT_EE or MSP intervention, colonic 5-HT secretion significantly decreased in these groups as compared to the MG group . Therefore, MJGT_EE and MSP exhibited similar regulatory effects on 5-HT, and this is consistent with the results described above . 3.5. Evaluation of the Expression of TPH1 and TPH2 in the Colonic Tissue Impacted by MJGT_EE To further evaluate the cause of the decrease in 5-HT synthesis observed, western blotting was performed to quantitatively determine changes in the levels of tryptophan hydroxylases (TPHs), which are key enzymes of the 5-HT metabolic pathway. A significant increase in the expression levels of TPH1 and TPH2 in the colons of IBS-C rats was identified (MG group) (p < 0.01), suggesting that changes in 5-HT expression levels in the model were significantly associated with TPH synthesis . Following treatment with MJGT_EE, the expression levels of both TPH1 and TPH2 decreased , and its effects were similar to those of the positive drug, MSP. Treatment with both MSP and MJGT_EE restored TPH expression to levels similar to those of the NC group . 3.6. Effect of MJGT_EE on SERT Expression in the Colon 5-HT synthesized in the intestines can be transported by the SERT from the interstitial spaces of the lamina propria to the mucosal epithelial cells and presynaptic neurons. This process is known as 5-HT reuptake . Thus, the SERT content is also a major factor that affects 5-HT expression. IBS-C negatively affected colonic SERT expression in rats in the MG group as compared to rats in the NC group (p < 0.01). Following drug administration (MJGT_EE and MSP), SERT expression levels were restored to levels similar to those observed in rats in the NC group at the 0.01 level . 3.7. Effect of MJGT_EE on the Expression of 5-HT3R and 5-HT4R in the Colon Among the seven confirmed 5-HT receptor subtypes, 5-HT3R and 5-HT4R are significantly related to gastrointestinal motility and pain sensitivity. Therefore, these two indicators were evaluated to determine the effects of the drug. As compared to rats in the NC group, those in the MG group exhibited a significant decrease in 5-HT3R and 5-HT4R expression (p < 0.01). Both MSP and MJGT_EE restored 5-HT4R expression levels , with the expression levels in rats in the MSP group being higher than those in rats in the NC group (p < 0.01). However, a similar trend was not observed with 5-HT3R expression. 3.8. Effect of MJGT_EE on CaM-MLCK Signaling Pathway The CaM-MLCK pathway is a classical downstream pathway of 5-HT4R that regulates smooth muscle contraction. As compared to rats in the NC group, those in the MG group exhibited significantly lower CaM (p < 0.05) and MLCK (p < 0.01) expression levels. Following treatment with MJGT_EE and MSP, both CaM and MLCK expression levels were restored to levels similar to those in rats in the NC group . 3.9. Effects of MJGT_EE on IBS-C Rat Gut Microbiota IBS-related pathophysiological changes involve alterations in gut microbiota composition or microbiota dysbiosis . Therefore, 16S rDNAs of the gut microbiota in rats in the different treatment groups were analyzed. b diversity analysis revealed the existence of significant differences in the microbiota between rats in the MG and NC groups . The number of OTUs decreased from 882 (NC) to 834 (MG) following model construction but increased following drug administration (MJGT_EE and MSP). Notably, the number of OTUs was highest following treatment with MJGT_EE (926) . The ACE, Chao, Sobs, and Shannon a diversity indices also showed that the diversity of the gut microbiota in rats with IBS-C was lower than that in rats in the NC group; however, this diversity was restored following treatment with MJGT_EE or MSP (p > 0.05) . At the phylum level, bacteria of the phyla Firmicutes and Bacteroidota accounted for the greatest proportion of microbes, with their proportions in the NC, MG, MJGT_EE, and MSP groups being 68.95% and 13.49%, 78.57% and 7.94%, 76.59% and 11.00%, and 74.27% and 15.00%, respectively . The Bacteroidetes/Firmicutes ratio in the MG group (0.10) decreased onefold as compared to that in the NC group (0.20). This is consistent with the previously reported significant increase in Firmicutes bacterial strain counts and the decrease in the Bacteroidetes/Firmicutes ratio in IBS-C patients . Following drug administration, the Bacteroidetes/Firmicutes ratio increased in the MJGT_EE group (0.14) but was still lower than that in the MSP group (0.20). At the family level, changes in the abundance of bacteria of the Prevotellaceae family in the different groups (0.80% and 0.43% in the NG and MG groups, respectively) followed a similar trend to those of bacteria of the Bacteroidota phylum, i.e., the restoration of bacterial abundance was more significant in the MSP group (1.75%) than in the MJGT_EE group (0.69%). The proportion of Clostridia_UCG-014 strains in the MG group (1.59%) decreased by 58.6% as compared to that in the NC group (3.75%); following drug administration, in the MJGT_EE group, this proportion (7.08%) was 4.45 and 2.79 times that in the MG and MSP groups, respectively. Linear discriminant effect size analysis (LFEse) revealed Clostridia_UCG-014 to be the only characteristic bacterium enriched in the MJGT_EE group . There was an increase in the abundance of some bacterial families in IBS-C rats. For instance, the abundance of bacteria of the Lachnospiraceae family in the MG group (28.94%) was 1.64 times that in the NC group (17.61%); however, this increase was reversed following treatment with MJGT_EE (14.94%) and MSP (14.37%). The abundance of bacteria of the Corynebacteriaceae family ranged from 1.68% in the NC group to 2.16% in the MG group, but decreased to 0.92% following treatment with MJGT_EE. The proportions of some bacteria remained unchanged before and after model construction, but changed following drug treatment. For instance, bacteria of the Ruminococcaceae family accounted for 4.54% and 4.68% of the microbiota in rats in the NC and MG groups, respectively. Their abundance increased to 6.67% following treatment with MJGT_EE but decreased to 3.86% following treatment with MSP . At the genus level, the proportion of Lactobacillus sp. decreased by approximately 76.08% in the MG group (1.11%) as compared to the NC group (4.64%). Their abundance was restored following the administration of MJGT_EE (6.19%) and MSP (4.04%), with MJGT_EE inducing a 0.33-fold increase in their abundance as compared to that in the NC group . 3.10. Identification of the Four Chemical Component Types in MJGT_EE MJGT_EE was analyzed using high-performance liquid chromatography (HPLC). Mixed control (S1) and test (S2) solutions were prepared as described in Section 2.10 and analyzed under appropriate chromatographic conditions. Through a comparative analysis of retention time and ultraviolet (UV) spectra, four main chromatographic peaks, which represented luteolin-7-O-glucoside ), luteolin ), eriodictyol-7-O-glucoside ), and eriodictyol ), were identified in MJGT_EE. 4. Discussion In IBS patients, gastrointestinal motility disorders are often accompanied by visceral hypersensitivity responses, which are exaggerated sensational responses to environmental stimuli, possibly induced by alterations in the processing of afferent signals from visceral neurons . The IBS-C rat model can be constructed via water limitation, ice water stimulation, and the maternal separation plus ice water stimulation. The first two methods ignore the psychological factors in the pathogenesis of IBS-C, so the last one that is more closely related to the patient's pathogenesis was chosen in the study. The chronic stress in newborn rats was applicated using maternal separation to induce stable changes in the central nervous system through the hypothalamic-pituitary-adrenal axis (HPA), as well as cognitive and emotional functions. This led to the gradual development of a disease state characterized by increased visceral sensitivity at the level of the large intestines after the maturation of the animals. Subsequently, to establish the IBS-C model, ice water at 4 degC was administered daily via gavage to the rats to induce symptoms of constipation. A comparison of the FWC and smallest threshold CRD volume between the MG and drug administration groups showed that drug administration not only reversed the significant decrease in FWC, but also decreased intestinal sensitivity in rats in the MG group. Therefore, MJGT_EE is able to reverse the decrease in FWC, as well as the increase in intestinal sensitivity, exhibited by IBS-C rats. Another characteristic symptom of IBS is the chronic disruption of normal gastrointestinal peristaltic activity , which mainly manifests as delayed gastric emptying and small intestinal transport . Our experimental results showed that rats in the MG group exhibited delayed gastric emptying and decreased small intestinal propulsion functions, and these were significantly improved via treatment with MJGT_EE. This provides preliminary evidence of the effects of MJGT_EE in promoting gastrointestinal motility in IBS-C patients. Notably, this method used to construct IBS-C in the present study can only represent one of the psychological factors that cause the onset of IBS. Studies on the gastrointestinal motility-promoting mechanism of MJGT_EE have shown that it elicits this effect by inhibiting the secretion of 5-HT, which is a typical indicator of alterations in IBS patients. In addition, 5-HT plays a key role in the regulation of gastrointestinal motility, secretion, and sensation . In this study, colonic tissue H&E staining revealed no inflammatory exudates nor pathomorphological changes. This is consistent with the findings of previous studies, which reported that IBS patients typically do not manifest organic lesions and that IBS-C rarely induces inflammatory responses. To further evaluate the causes of alterations in the 5-HT signaling system, we investigated rate-limiting enzymes that directly affect 5-HT synthesis, i.e., TPH (TPH1 and TPH2) , as tryptophan (Trp) is a precursor of 5-HT that is first converted to 5-hydroxytryptophan (5-HTP) under the action of TPH and is subsequently converted to 5-HT under the action of 5-HTP decarboxylase (5-HTPDC). TPH plays a vital role in the conversion of Trp to 5-HTP and directly affects 5-HT secretion. Synthesized 5-HT, which is stored in enterochromaffin (EC) cells, is released into the lamina propria in response to luminal pressure, as well as chemical or mechanical stimuli, where it interacts with nerve endings and immune cells . As with 5-HT release, its deactivation is of equal importance in maintaining dynamic equilibrium. The SERT plays an indispensable role in 5-HT deactivation as it transports 5-HT from the interstitial spaces of the lamina propria to the intestinal mucosal cells and presynaptic neurons and is subsequently involved in 5-HT degradation. Insufficient SERT synthesis leads to 5-HT accumulation . This induces high contractility in the digestive tract smooth muscles, as well as high gland sensitivity and increased endocrine secretion, which result in diarrhea and pain. A significant increase in 5-HT levels in the MG group was observed as compared to the NC groups, and this was the possible cause of the abnormalities in gastrointestinal motility; however, treatment with MJGT_EE exerted a significant downregulatory effect on 5-HT levels. These findings are consistent with the trend observed in the changes in TPH expression in the different groups, demonstrating that MJGT_EE reduced 5-HT secretion by decreasing TPH synthesis. The decrease in SERT expression was identified in the MG group; however, this expression was upregulated following treatment with MJGT_EE, indicating that drug administration inhibited excessive 5-HT accumulation. Therefore, MJGT_EE evidently restores abnormally increased 5-HT levels by regulating TPH and SERT expression. MJGT_EE regulates gastrointestinal responses by regulating 5HT4R. 5-HT released from EC cells can regulate gastrointestinal motility by effectively activating 5-HT3R and 5-HT4R at the vagal afferent nerve endings of the intestinal mucosa. Consequently, the activation of these receptors enhances gastrointestinal transport . Our findings indicated that the expression levels of both 5-HT3R and 5-HT4R were downregulated in IBS-C rats, and that their expression levels were negatively correlated with visceral sensitivity, and this is consistent with findings reported in the literature . Interestingly, in a similar way as MSP, a selective 5-HT4R agonist, MJGT_EE only exerted restorative effects on 5-HT4R expression but did not affect 5-HT3R expression. This phenomenon could be explained by the fact that 5-HT released by EC cells can mediate digestive functions through the activation of endogenous or exogenous sensory nerve endings at high concentrations and activate 5-HT4 or 5-HT1P receptors at a low concentrations, thereby regulating gastrointestinal motility . MJGT_EE reduced 5-HT synthesis, inducing lower 5-HT luminal concentrations in the colon; this may explain the lack of effect of MJGT_EE on 5-HT3R secretion. The CaM-MLCK pathway is a core pathway through which 5-HT4R regulates downstream smooth muscle contraction. Following the activation of Ca2+ ion channels, free Ca2+ concentrations within cells rapidly increase, leading to the formation of Ca2+-CaM complexes. Consequently, MLCK is activated and induces the phosphorylation of the 19th serine residue on myosin light chain 20 (MLc20). This in turn activates myosin ATPase, which hydrolyzes ATP and coverts the chemical energy it contains to mechanical energy that enables myosin to slide past actin filaments and achieve smooth muscle contraction, ultimately resulting in the acceleration of intestinal peristalsis . The findings of our study also indicate that changes in CaM and MLCK expression in the MG group before and after drug administration were positively correlated with 5-HT4R expression, further corroborating the effects of MJGT_EE. Intestinal microbes would also be involved in the gastrointestinal motility impacted by MJGT_EE. Several clinical studies indicated the variation of gut microbiota composition in IBS patients , and this might be a possible etiology for the disorder. In this study, we found that treatment with MJGT_EE led to the following. (1) Increase in gut microbiota diversity. The gut microbiota in IBS patients is significantly different from that in healthy individuals and is characterized by lower bacterial diversity . We found that the number of OTUs in rats with IBS-C was 5.4% lower than that in normal rats (NC group), however, increased by 11% and 4.8% following treatment with MJGT_EE and MSP, respectively. This indicates that not only was MJGT_EE beneficial in increasing microbiota diversity, but it also elicited effects superior to those of MSP. (2) Increase in the number of bacteria with known benefit. MJGT_EE increased the counts of some beneficial bacteria such as those belonging to the Lactobacillus genus and the Prevotellaceae and Ruminococcaceae families. Lactobacillus sp. strains alleviate gastrointestinal diseases , reduce allergic symptoms , and are considered as potential antimicrobial probiotic strains against human pathogens through various mechanisms. Bacteria of the Ruminococcaceae family can generate short-chain fatty acids (SCFA) , which are generally believed to elicit beneficial effects in the human body, such as improving intestinal health and protecting the intestinal mucosal barrier . This increase in beneficial bacterial counts may be related to the MJGT_EE-induced decrease in 5-HT secretion, as 5-HT directly inhibits the growth of beneficial bacteria . (3) Regulation of gut microbes involved in 5-HT synthesis. Studies have shown that Corynebacterium sp. strains promote 5-HT synthesis in tissues ; we observed an increase in the proportion of Corynebacterium sp. strains in rats in the MG group as compared with that in the rats in the NC group; in the MG group, this proportion decreased to approximately half the initial level following treatment with MJGT_EE. The proportions of bacteria of the Lachnospiraceae family, which induce 5-HT biosynthesis and release by EC cells , were also restored to levels similar to those in rats in the NC group following treatment with MJGT_EE and MSP. Notably, Clostridia_UCG-014 strains, which are beneficial bacteria associated with tryptophan metabolism and that regulate intestinal homeostasis, were only enriched in rats in the MJGT_EE treatment group . Similar effects were observed for MSP, persuading us to speculate that Clostridia_UCG-014 strains may be key bacterial species that affected gastrointestinal motility in rats in the MJGT_EE group. Generally, an organism has a core native microbiota that remains relatively stable during adulthood. However, each individual has a unique gut flora profile due to a variety of factors such as gut type, body mass index (BMI) level, frequency of exercise, lifestyle, culture, and diet. Therefore, there is no one best gut microbiota composition . For example, gut microbiota are not only able to respond to the various physiological activities of flavonoids, but also to metabolize them and produce new active products . Through an HPLC analysis, four major MJBT_EE components were identified: eriodictyol-7-O-glucoside, luteolin-7-O-glucoside, eriodictyol, and luteolin. In the previous trial, we found that these four components are the active ingredients in hydro extracts of MJGT that affect gastrointestinal motility . The regulation effect of luteolin and other flavonoids, such as apigenin and quercetin, on muscle tissue contraction in cows were also identified . Thus, we believe that they should also be important components of MJBT_EE to alleviate the symptoms of IBS-C. Notably, whether there are other active ingredients needs to be further investigated. 5. Conclusions MJGT_EE promoted gastrointestinal motility and reduced intestinal sensitivity in IBS-C model rats established via maternal separation. These effects were mainly related to a decrease in 5-HT secretion and an upregulation in 5-HT4R expression and were not related to 5-HT3R expression. The possible mechanism underlying the effects of MJGT_EE on 5-HT secretion may involve the decrease and increase in TPH and SERT secretion, respectively, while underlying that its effects on 5-HT4R expression involve the upregulation of the CaM-MLCK pathway. MJGT_EE also increased microbiota diversity and beneficial bacterial counts, while restoring gut microbiota composition disturbed by IBS-C. Since the flavonoids are important active ingredients in MJGT_EE, the final observations would result from the complicated interactions among flavonoids and gut microbiota bioactivity and a wide range of their metabolites, which are worthy of further investigation. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Changes of intestinal flora diversity in rats of MJGT_EE group. (n = 4 for each group). Figure S2: Linear discriminant effect size (LEfSe) analyses comparing differentially abundant taxa in each group (A); the LDA effect size taxonomic cladogram comparing four groups. Different colors indicate species with significant differences between groups, and the logarithmic LDA score is set to 4 (B). (n = 4 for each group). Figure S3 The chromatogram of the MJGT_EE. (A) The mixed control solution of luteolin-7-O-glucoside (1) and luteolin (2) detected at 350 nm; (B) The test solution detected at 350 nm; (C) The mixed control solution of eriodictyol-7-O-glucoside (3) and eriodictyol (4) detected at 284 nm; (D) The test solution detected at 284 nm. Click here for additional data file. Author Contributions L.W.: conceptualization, writing--original draft preparation, investigation, methodology, software; L.G.: investigation; X.J.: investigation; Z.C.: investigation; X.Q.: investigation; X.C.: investigation; J.G.: writing--review and editing, supervision, project administration, funding acquisition; L.Z.: conceptualization, methodology, supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animal experiments were approved by the laboratory animal ethics committee of Shanxi Agricultural University (Taigu, China) (Approval No.: SXAU-EAW-2018R.0406001) and performed in accordance with the regulations and guidance of this committee. Data Availability Statement Data is contained within the article or Supplementary Material. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The timeline from rat model establishment, administration to sampling (A). Comparison of fecal water content (B) and pressure threshold (C) in rats of different groups. Capital and lowercase letters above the bar indicate the difference significance at the 0.01 or 0.05 levels, respectively. (n = 8 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group. Figure 2 Effect of MJGT_EE on gastric emptying rate (A) and intestinal propulsive rate (B) in vivo. Capital letters above the bar indicate the difference significance at the 0.01 level. (n = 8 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group. Figure 3 H&E staining to observe the effect of MJGT_EE on the colonic tissues of IBS-C rats (200x). (A) The colonic tissues from normal rats; (B) the colonic tissues from rats with IBS-C; (C) the colonic tissues of IBS-C rats after 30 days of MJGT_EE treatment; (D) the colonic tissues of IBS-C rats after 30 days of MSP treatment. (n = 8 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group. Figure 4 Immunohistochemical staining analysis to observe the effect of MJGT_EE on the colonic tissues of IBS-C rats. (A) The colonic tissues from normal rats; (B) the colonic tissues from rats with IBS-C; (C) the colonic tissues of IBS-C rats after 30 days of MJGT_EE treatment; (D) the colonic tissues of IBS-C rats after 30 days of MSP treatment; (E) the relative expression of 5-HT. Capital letters above the bar indicate the difference significance at the 0.01 level. (n = 8 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group; 5-HT: 5-hydroxytryptamine. Figure 5 Western blotting analysis of TPH1 (A), TPH2 (B), SERT (C), 5-HT3 receptors (D), 5-HT4 receptors (E), CaM (F), and MLCK (G) in colonic tissues of each group. Capital and lowercase letters above the bar indicate the difference significance at the 0.01 or 0.05 levels, respectively. (n = 8 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group; 5-HT: 5-hydroxytryptamine; TPH1: tryptophan hydroxylase 1; TPH2: tryptophan hydroxylase 2; SERT: serotonin transporter; CAM: calmodulin; MLCK: myosin light chain kinase; 5-HT3R: 5-HT3 receptor; 5-HT4R: 5-HT4 receptor. Figure 6 PCoA analysis of the OTU level of intestinal flora in different groups rats (A); venn diagram of the distribution of OTUs in the four groups (B). (n = 4 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group. Figure 7 The variations in intestinal flora composition are displayed the phylum (A) and family (B) and genus level (C), respectively. (n = 4 for each group). NC: negative control group; MG: model group, MSP: mosapride group, MJGT_EE: Mao Jian Green Tea ethanol extract group. 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PMC10000492 | Our study discussed the role of Zfp90 in ovarian cancer (OC) cell lines' sensitivity to cisplatin. We used two OC cell lines, SK-OV-3 and ES-2, to evaluate their role in cisplatin sensitization. The protein levels of p-Akt, ERK, caspase 3, Bcl-2, Bax, E-cadherin, MMP-2, MMP-9 and other drug resistance-related molecules, including Nrf2/HO-1, were discovered in the SK-OV-3 and ES-2 cells. We also used a human ovarian surface epithelial cell to compare the effect of Zfp90. Our outcomes indicated that cisplatin treatment generates reactive oxygen species (ROS) that modulate apoptotic protein expression. The anti-oxidative signal was also stimulated, which could hinder cell migration. The intervention of Zfp90 could greatly improve the apoptosis pathway and block the migrative pathway to regulate the cisplatin sensitivity in the OC cells. This study implies that the loss of function of Zfp90 might promote cisplatin sensitization in OC cells via regulating the Nrf2/HO-1 pathway to enhance cell apoptosis and inhibit the migrative effect in both SK-OV-3 and ES-2 cells. zinc finger protein 90 ovarian cancer cisplatin sensitivity apoptosis nuclear factor E2-related factor 2 Ministry of Science and Technology, TaiwanMOST 110-2314-B-037- Medical University Chung-Ho Memorial HospitalKMUH109-M910 KMUH110-0M43 KMUH110-0M45 Kaohsiung Medical University Research CenterKMU-TC108A04-0 This research was funded by the Ministry of Science and Technology, Taiwan (MOST 110-2314-B-037-040-), the Kaohsiung Medical University Chung-Ho Memorial Hospital (KMUH109-M910, KMUH110-0M43 and KMUH110-0M45) and partially supported by Kaohsiung Medical University Research Center Grant (KMU-TC108A04-0). pmc1. Introduction Ovarian cancer (OC) is one of the most malignant gynecological tumors . According to the Taiwan Ministry of Health and Welfare data, OC became eighth place in the occurrence of cancer in Taiwan in 2018. Its five year death rate of between 60 and 70% renders it one of the highest in all gynecologic cancers . In addition, the ovary is found in the abdominal cavity's depths, which is more inconducive for direct sampling pathological slices and presently lacks effective screening for the early detection of OC. Overall, 70% of OC patients have been detected with stage III or stage IV in recent years . Debulking surgery followed by postoperative chemotherapy and radiotherapy is the standard golden treatment for OC. Cisplatin-based therapy is the first-line treatment for OC patients . However, drug resistance has become a big concern for OC treatment . Drug resistance and toxicities are often the main problems for OC chemotherapy . The mechanisms implicated in anti-cancer drug resistance are often complex. However, some anti-oxidant cascade-induced chemoresistance have been frequently discussed . Studies about inhibiting such resistance to cancer medication could offer more beneficial information about improving chemotherapy . Prior studies have depicted that the anti-cancer effect influenced by cisplatin is through generating reactive oxygen species (ROS) or DNA double-strand breaks (DSBs) . Thus, some studies have revealed that the mechanism of chemo-resistance from cancer cells influences the NF-E2-related factor 2 (Nrf2)/anti-oxidant response elements (ARE) pathway . Some literature has demonstrated that the activation of the Nrf2/ARE pathway could protect cancer cells from cisplatin damage . Thus, some research has also sought to inhibit this pathway to modulate the chemo-resistance effect . To enhance the treatment rate of OC, there has been numerous research to develop a proper way to deal with cisplatin chemoresistance . Some of these studies have aimed at realizing the pathobiology to expand the currently available treatments and develop tailored therapies. Some studies used genome-wide association studies (GWAS) to determine the possible genetic polymorphisms as predictors of OC clinical outcome . There are more than 30 variants found by GWAS linked to OC susceptibility , such as BRCA1 and BRCA2, which are the most well-known pathogenic variants. Pathogenic variations in the BRCA1 and BRCA2 responsible for most OC syndromes have been reported in numerous ethnic groups . Prior studies have also illustrated that women with harmful BRCA1 (39-44%) or BRCA2 (11-17%) variants will develop OC easily at 70-80 years old . To further discover more possible candidate pathogenic variants, many studies have performed post-GWAS analysis . Among them, numerous GWAS studies have highlighted that p-value < 5 x 10-8 acted as a significant index for identifying whether the variant has an impact or not. However, Chen et al., 2021 indicated that studies with sample sizes over 20,000 to 120,000 could relax the p-value threshold to 5 x 10-7 and increase the discovery of potential candidates , such as TREM2 variant rs75932628 in Alzheimer's disease. The analysis of participants indicated a strong, highly substantial association with Alzheimer's disease (p = 1.4 x 10-7; OR = 4.59; CI = 2.49-8.46) . Other studies also further confirmed the feasibility of the strategies . We therefore assessed the GWAS data and discovered Zinc finger protein 90 (Zfp90) (rs137866923) (p = 3 x 10 -7; OR = 3.82; CI = 2.29-6.36) as a potential target. Zinc finger proteins (Zfp) are a broad family of proteins characterized by the coordination of one or more zinc ions to regulate the fold. It performs various biological functions, including the development and differentiation of several tissues. A prior study demonstrated that Zfp90 regulated cardiac development . In addition, some studies have also disclosed that Zfp90 played a critical role in initiating colitis-associated colorectal cancer through modulating the nuclear factor of stimulated T-cells and the cytoplasmic 2 (NFATC-2)/bone morphogenic protein-4 (BMP-4) pathway . The team also expressed that Zfp90 facilitated the development of colitis-associated colorectal cancer via a microbiota-dependent strategy . However, the role of Zfp90 in OC remains largely equivocal. Due to the data expressed in the GWAS, our study sought to evaluate the role of Zfp90 in OC and the impact of Zfp90 on cisplatin sensitization. We assessed Nrf-2-related molecules, including p-Nrf2 and HO-1; the SOD activity; the apoptotic pathway, including p-P38, p-Akt, p-ERK, Bcl-2, Bax and active caspase-3; and the migration pathway, including MMP-2 and MMP-9 to assert its role in OC treatment. 2. Materials and Methods 2.1. Cell Maintenance The SK-OV-3 cell line was acquired from the American Type Culture Collection (No. HTB-77TM). SK-OV-3 and ES-2 were maintained with McCoy's 5A medium (No. CC120-0500, GeneDireX Inc., Zhunan Township, Taiwan) (5% CO2; 37 degC). The cell numbers for each assay were presented as follows: cell viability assay: 2 x 103/well for 96-well microplates; 2 x 105/dish in a 6 cm culture dish containing coverslips (24 x 24 mm) for the transferase dUTP nick end labeling (TUNEL) staining and wound healing assay; 1 x 106/dish in a 10 cm culture dish for the Western blot analysis, SOD activity and Enzyme-linked immunosorbent assay (ELISA). The ES-2 cell line was obtained from the Bioresource Collection and Research Center (No. 60067). The cells were maintained with McCoy's 5A medium (No. CC120-0500, GeneDireX Inc, Taiwan) (5% CO2; 37 degC). The cell numbers for each assay were presented as follows: cell viability assay: 2 x 103/well for 96-well microplates; 2 x 105/dish in a 6 cm culture dish for the TUNEL staining (with coverslips (24 x 24 mm)) and wound healing assay (without coverslips); 1 x 106/dish in a 10 cm culture dish for the Western blot analysis, SOD activity and ELISA. The normal cell line used in this study was human ovarian surface epithelial cells (HOSE), which were purchased from the ScienCell Research Laboratories (No. 7310, San Diego, CA, USA). The HOSE was maintained in an ovarian epithelial cell medium (OEpiCM) (No. 7311, San Diego, CA, USA). 2 x 104/well for 96-well microplates 2.2. Knockdown of Zfp90 with siRNA Transfection The cells were seeded in 10 cm dishes for the transfection of Zfp90 siRNA. The SK-OV-3 cells and ES-2 cells were transfected with Zfp90 siRNA (SASI_Hs01_0036-3148/ZFP90, SASI_Hs01_0017-3518/ZFP90, SASI_Hs01_0036-3519, Sigma, St. Louis, MO, USA), The normal control group were treated with the siRNA negative control (No. SIC001, Sigma, MI, USA). The transfections of siRNAs and the negative control were executed with DharmaFECT 1 Transfection Reagent (No. T-2001-03, Horizon Discovery, Cambridge, UK). The cultured cells were washed once with phosphor buffer saline (PBS) and replaced with normal McCoy's 5A medium after transfection for 48 h. 2.3. Cell Viability Assay The cultured cells (si-Ctrl or si-Zfp90) were seeded in 96-well microplates and treated with 1, 10, 15 or 20 mM cisplatin (No. 15663-27-1, Sigma, MI, USA) for 24 or 48 h. Then, 10 mL alamarBlueTM (No. DAL1025, Invitrogen, Carlsbad, CA, USA) in each well was included and calculated by the ELISA reader (595 nM). The cell viability was calculated as 100 x [(optical density (OD) of treated cells - OD of blank-treated cells)/(OD of control cells - OD of blank-treated cells)]. 2.4. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) Stain The cells (si-Ctrl or si-Zfp90) in 6 cm dishes with coverslips were treated with 20 mM cisplatin for 24 h. The cells were washed with PBS and also fixed with 4% paraformaldehyde. Then, 3% H2O2 in methanol was used to inhibit and was stained with a TUNEL reaction mixture (No. 11684795910, Roche Diagnostics, Mannheim, Germany) for 1 h. The cells on the coverslips were washed by ddH2O and mounted by the mounting medium with DAPI (No. ab104139, abcam, Cambridge, UK). The apoptotic signal was detected by fluorescence microscopy (IX51, Olympus, Tokyo, Japan). 2.5. Western Blotting The lysed cell extracts were controlled to an adequate concentration with a lysis buffer. Then, the mixture of sample buffer and cell extracts was loaded in a 10% SDS-polyacrylamide gel and the electrophoresis was run for 90 min at 100 volts. Then, a PVDF membrane was employed in the following transfer at 125 mA for overnight at 4 degC. Next, 5% non-fat milk in TTBS was blocked for 40 min at room temperature (RT), corresponding to the primary antibody for 24 h at 4 degC. After washing thrice in TTBS, the membrane was incubated with a secondary antibody for one hour at RT. Images were collected using the UVP BioChemi Imaging System, and the LabWorks 4.0 software (UVP) was employed to quantify the relative densitometry. The primary antibodies used in this study are listed as followed: ZFP90 (zinc finger protein 90; dilution 1:1000) (No. 26120-1-AP, Thermofisher, Waltham, MA, USA); b-actin (loading control; dilution1:1000) (No. A5441, Sigma, MI, USA); p-ERK (extracellular signal-related kinases; dilution 1:1500) (No. 9190, Cell Signaling Technology, Danvers, MA, USA); ERK (extracellular signal-related kinases; dilution 1:1000) (No. 9102, Cell Signaling Technology, USA); p-AKT (dilution 1:1000) (No. 9271, Cell Signaling Technology, USA); AKT (dilution 1:1000) (No. 4685, Cell Signaling Technology, USA); p-P38 (dilution 1:1000) (No. 9211, Cell Signaling Technology, USA); P38 (dilution 1:1000) (No. 9212, Cell Signaling Technology, USA); active caspase-3 (dilution 1:1000) (No. MA5-32015, Invitrogen, USA); Bcl-2 (dilution 1:2000) (No. ab59348, abcam, UK); Bax (dilution 1:2000) (No. ab32503, abcam, UK); MMP-2 (dilution 1:1000) (No. ab13132, abcam, UK); MMP-9 (dilution 1:1000) (No. AB19016, Sigma, MI, USA); E-cadherin (dilution 1:1000) (No. GTX100443, GeneTex, CA, USA); p-Nrf2 (dilution 1:1000) (No. PA5-67520, Invitrogen, USA); HO-1 (dilution 1:1000) (No. ab13248, abcam, UK) 2.6. Wound Healing Assay The SK-OV-3 cells (2 x 105/dish) or ES-2 cells (2 x 105/dish) were seeded in 6 cm dishes for 24 hr. We then utilized a 200mL pipette tip to inscribe a scratch wound. The cells (si-Ctrl or si-Zfp90) were treated with 20 mM cisplatin for 24 hr. Images of the scratched wounds were collected after treatment. The closing of the scratched wounds was regarded as the completion of the migration process. The migrated areas were assessed and identified using the ImageJ software. 2.7. ELISA The SK-OV-3 cells or ES-2 cells (Si-Ctrl or Si-Zfp90) were held in 6-well microplates for 24 hr. Then, the cells were treated with or without 20 mM cisplatin for another 24 h in a serum-free medium. The matrix metalloproteinases (MMPs) and bone morphogenic protein-7 (BMP-7) excreted in the culture medium were quantified using the MMPs activity and BMP-7 ELISA kit following the manufacturer's instructions (No. ab112146; ab99985, abcam, UK). 2.8. Statistical Analysis The data were presented as mean +- SEM. The data were evaluated using one way analysis of variance (ANOVA), followed by Tukey's test. A p value less than 0.05 was deemed statistically significant. The intensity of each band was indicated as the relative integrated density segmented by the average integrated density values from all of the internal controls in western blotting. 3. Results 3.1. Inhibition of Zfp90 Increases the Cisplatin Sensitivity in Ovarian Cancer Cells To analyze the role Zfp90 played in cisplatin treatment, we transfected si-Zfp90 to suppress its expression in SK-OV-3 cells and ES-2 cells. The cytotoxic impact of multiple concentrations (1, 10, 15 and 20 mM) of cisplatin in the SK-OV-3 and ES-2 cells with or without si-Zfp90 were identified by an alamarBlueTM assay in 24 or 48 h treatment. Our data indicated that 10, 15 and 20 mM cisplatin could significantly inhibit SK-OV-3 cell viability (*, p < 0.05, versus si-Ctrl group) and the knockdown of Zfp90 significantly enhanced cisplatin-induced cytotoxicity in both the 24 h treatment (1, 10, 15 and 20 mM) and the 48 h treatment (1, 10, 15 and 20 mM) (#, p < 0.05, versus same concentration cisplatin in si-Ctrl group individually). We also conducted a TUNEL stain to determine the cell apoptosis. The apoptotic impact of 20 mM cisplatin in the SK-OV-3 and ES-2 cells with or without si-Zfp90 was executed after 24 h treatment. The data revealed that the treatment of 20 mM cisplatin could significantly up-regulate the TUNEL signal (from 1.0 +- 0.5 to 16.4 +- 1.2) (*, p < 0.05, versus si-Ctrl group) and si-Zfp90 alone did not influence the SK-OV-3 cell death. In addition, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the SK-OV-3 sensitivity to cisplatin (from 16.4 +- 1.2 to 26.7 +- 2.2) (#, p < 0.05, versus 20 mM cisplatin group). Furthermore, we also employed an ES-2 cell line to validate the result. Our data demonstrated that the knockdown of Zfp90 significantly enhanced the cisplatin-induced cytotoxicity in both the 24 h treatment (1, 10, 15 and 20 mM) and 48 h treatment (10, 15 and 20 mM) (#, p < 0.05, versus same concentration cisplatin in si-Ctrl group individually). We also revealed that the treatment of 20 mM cisplatin could significantly up-regulate the TUNEL signal (from 2.5 +- 1.4 to 17.2 +- 3.5) (*, p < 0.05, versus si-Ctrl group) and si-Zfp90 alone did not affect the ES-2 cell death. In addition, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the ES-2 sensitivity to cisplatin-induced damage (from 17.2 +- 3.5 to 32.3 +- 4.6) (#, p < 0.05, versus cisplatin group). We used the human ovarian surface epithelial cells (HOSE) as normal cells to compare with the two OC cell lines. Zfp90 protein expression was performed in the HOSE, SK-OV-3 and ES-2 cells , original blot shown in Figure S1. The cytotoxic effect of the different concentrations (1, 10, 15 and 20 mM) of cisplatin in the HOSE cell with or without si-Zfp90 were performed for 24 h . The data showed that the inhibition of Zfp90 did not affect the cisplatin-induced damage to the HOSE cell. 3.2. Inhibition of Zfp90 Enhances the Cisplatin-Induced Apoptosis in Ovarian Cancer Cells We then evaluated the phosphorylation of p-P38, p-ERK, p-Akt and downstream apoptotic related protein expression to further determine the correlation between Zfp90 and cisplatin sensitization. The protein expression of 20 mM cisplatin in the SK-OV-3 and ES-2 cells with or without si-Zfp90 was identified by western blotting after 1 h treatment. Our data depicted that 20 mM cisplatin significantly increased the p-P38 protein expression and decreased the p-ERK and p-Akt expression (*, p < 0.05, versus si-Ctrl group). The knockdown of Zfp90 alone did not affect the p-P38, p-ERK and p-Akt protein expression . Furthermore, the co-treatment of 20 mM cisplatin and si-Zfp90 did not affect the cisplatin-induced up-regulation of p-P38 and significantly inhibited the cisplatin-induced down-regulation of p-ERK and p-Akt (#, p < 0.05, versus cisplatin group), original blot shown Figure S2. In the ES-2 cells, the data showed some trend. The outcome indicated that 20 mM cisplatin significantly decreased the p-Akt protein expression and increased the p-P38 protein expression. The knockdown of Zfp90 decreased the p-Akt protein expression . Moreover, the co-treatment of 20 mM cisplatin and si-Zfp90 only significantly enhanced the cisplatin-induced up-regulation of p-P38 (*, p < 0.05, versus si-Ctrl group) and did not affect the p-ERK and p-Akt expression , original blot shown in Figure S3. Apoptotic proteins, such as active caspase-3, Bcl-2 or Bax, were then conducted. The apoptotic protein of 20 mM cisplatin in the SK-OV-3 and ES-2 cells with or without si-Zfp90 were determined by western blotting after 24 h treatment. The data highlighted that 20 mM cisplatin significantly increased the active-caspase-3 and Bax, and decreased the Bcl-2 protein expression (*, p < 0.05, versus si-Ctrl group). However, the knockdown of Zfp90 alone did not affect the active-caspase-3, Bax and Bcl-2 protein expression . Furthermore, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the cisplatin-induced up-regulation of active-caspase-3 and Bax , and inhibited the cisplatin-induced down-regulation of Bcl-2 protein expression (#, p < 0.05, versus cisplatin group), original blot shown Figure S4. In the ES-2 cell, the data also expressed the same trend. The outcomes implied that 20 mM cisplatin significantly elevated the active-caspase-3 and Bax, and decreased the Bcl-2 protein expression (*, p < 0.05, versus si-Ctrl group). The knockdown of Zfp90 did not affect the active-caspase-3, Bax and Bcl-2 protein expression . Similarly, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the cisplatin-induced up-regulation active-caspase-3 and Bax , and did not affect the Bcl-2 protein expression (#, p < 0.05, versus cisplatin group), original blot shown in Figure S5. 3.3. Inhibition of Zfp90 Enhances the Cisplatin-Modulated Anti-Migrative Effect in Ovarian Cancer Cells Cell migration was assessed to determine the role of Zfp90 in OC. The anti-migrative effect of si-Zfp90 in the SK-OV-3 and ES-2 cells with or without 20 mM cisplatin were identified by a wound healing assay after 24 h treatment . The quantitative outcome indicated that 20 mM cisplatin significantly decreased the wound recovery area, more than the si-Ctrl group (*, p < 0.05, versus si-Ctrl group), and the knockdown of Zfp90 alone did not impact the wound recovery area. However, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the cisplatin-induced anti-migrative effect (#, p < 0.05, versus cisplatin group). We also conducted matrix metalloproteinases (MMPs) activity and migrative-related protein expression to confirm the anti-migrative effect of inhibiting Zfp90 in the molecule level. The MMPs activity and protein expression of si-Zfp90 in the SK-OV-3 and ES-2 cells with or without 20 mM cisplatin were observed after 24 h treatment. Our data showed that 20 mM cisplatin significantly decreased the MMPs activity (from 100.6 +- 4.5 to 57.0 +- 5.6) (*, p < 0.05, versus si-Ctrl group) and the knockdown of Zfp90 alone did not affect the MMPs activity. Furthermore, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced down-regulation of the MMPs activity (from 57.0 +- 5.6 to 33.8 +- 6.6) (#, p < 0.05, versus cisplatin group). We also determined the migrative-related proteins, including MMP-2, MMP-9 and E-cadherin expression. Our data demonstrated that 20 mM cisplatin significantly decreased the MMP-2, MMP-9 and E-cadherin protein expression (*, p < 0.05, versus si-Ctrl group) and the knockdown of Zfp90 only affected the E-cadherin protein expression (*, p < 0.05, versus si-Ctrl group). The co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced down-regulation of MMP-2 and MMP-9 , but did not affect the E-cadherin protein expression (#, p < 0.05, versus cisplatin group), original blot shown in Figure S6. In the ES-2 cells, we also detected the wound healing assay . The quantitative result revealed that 20 mM cisplatin and the knockdown of Zfp90 mitigated the wound recovery area significantly more than the si-Ctrl group individually (*, p < 0.05, versus si-Ctrl group). The co-treatment of 20 mM cisplatin and si-Zfp90 significantly enhanced the cisplatin-induced anti-migrative effect . We also performed MMPs activity and protein expression in the ES-2 cells. Our data showed that 20 mM cisplatin significantly decreased the MMPs activity (from 100.6 +- 4.5 to 65.2 +- 4.5) (*, p < 0.05, versus control group) and the knockdown of Zfp90 did not affect the MMPs activity. In addition, the co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced down-regulation of the MMPs activity (from 65.2 +- 4.5 to 40.5 +- 5.3) (#, p < 0.05, versus cisplatin group). In terms of protein expression, our data showed that 20 mM cisplatin significantly decreased the MMP-2, MMP-9 and E-cadherin protein expression, and the knockdown of Zfp90 affected the MMP-2 and E-cadherin protein expression (*, p < 0.05, versus si-Ctrl group). The co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced down-regulation of MMP-2 , but did not affect the MMP-9 and E-cadherin protein expression. (#, p < 0.05, versus cisplatin group), original blot shown in Figure S7. 3.4. Inhibition of Zfp90 Inhibited The Cisplatin-Induced Anti-Oxidative Effect in Ovarian Cancer Cells The anti-oxidative stress pathway nuclear factor erythroid 2-related factor 2 (Nrf2)/heme-oxygenase-1 (HO-1) cascade has often been highlighted as being involved in the mechanism of drug resistance. We then tested the associated protein, such as p-Nrf2, HO-1 and bone morphogenic protein-7 (BMP-7). The anti-oxidative effect of si-Zfp90 in the SK-OV-3 and ES-2 cells with or without 20 mM cisplatin were determined by western blotting and ELISA after 24 h treatment. Our data indicated that 20 mM cisplatin significantly increased the p-Nrf2 and HO-1 protein expression (*, p < 0.05, versus si-Ctrl group) and the knockdown of Zfp90 alone did not affect the protein expression mentioned above. The co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced up-regulation of the p-Nrf2 and HO-1 protein expression. The cisplatin-induced up-regulation of the BMP-7 concentration was also inhibited (#, p < 0.05, versus cisplatin group), original blot shown in Figure S8. In the ES-2 cells, the data showed that 20 mM cisplatin significantly increased the p-Nrf2 and HO-1 protein expression (*, p < 0.05, versus si-Ctrl group) and the knockdown of Zfp90 alone did not affect the protein expression mentioned above. The co-treatment of 20 mM cisplatin and si-Zfp90 significantly inhibited the cisplatin-induced up-regulation of p-Nrf2 and HO-1 protein expression. The cisplatin-induced up-regulation of the BMP-7 concentration was also inhibited (#, p < 0.05, versus cisplatin group), original blot shown in Figure S9. 3.5. Inhibition of HO-1 Reversed the Zfp-90-Induced Cisplatin Sensitization in Ovarian Cancer Cells We utilized the HO-1 inducer, carnosol, to revalidate the mechanism of action of Zfp90 in the cell viability and SOD activity. The cell viability of 12.5 and 25 mM carnosol in the SK-OV-3 and ES-2 cells with or without si-Zfp90 or cisplatin were determined by an alamarBlueTM assay in a 24 h treatment. Our data expressed that 12.5 and 25 mM carnosol both significantly reversed the si-Zfp90-induced down-regulation of the cell viability in the SK-OV-3 cells (and, p < 0.05, versus si-Zfp90 plus cisplatin group). In terms of the SOD activity, 12.5 and 25mM carnosol both significantly reversed the si-Zfp90-induced down-regulation of the SOD activity in the SK-OV-3 cells (and, p < 0.05, versus si-Zfp90 plus cisplatin group). In the ES-2 cells, the same trend was shown. The outcome implied that 12.5 and 25 mM carnosol both significantly reversed the si-Zfp90-induced down-regulation of the cell viability in the ES-2 cells (and, p < 0.05, versus si-Zfp90 plus cisplatin group). In addition, 12.5 and 25mM carnosol also significantly reversed the si-Zfp90-induced down-regulation of the SOD activity in the ES-2 cells (and, p < 0.05, versus si-Zfp90 plus cisplatin group). 4. Discussion OC is an extensive gynecology disease in women and the major limitation of OC therapy is cisplatin resistance . The statistical findings in the GWAS revealed that Zfp90 may play a crucial role in the modulation of drug resistance or tumorigenesis. To the best of our best knowledge, we are the first to investigate the role of Zfp90 in OC chemoresistance. This protein was originally discovered via the screening of zinc-finger-encoding genes . It is known to exhibit inhibitory activity and possesses a zinc finger domain. Later, the literature indicated that Zfp90 contributed to obesity . Hata et al., 2011 also demonstrated that Zfp90 inhibited the neuron-restrictive silencer factor (NRSF)-mediated transcriptional repression of fetal cardiac genes by inhibiting the NRSF binding to the neuron-restrictive silencer element (NRSE) . The original study of the correlation between Zfp90 and cancer was conducted by Yim et al., 2006 . The study indicated that the protein expression of Zfp90 significantly increased when 10mM cisplatin was treated in cervical carcinoma cells (HeLa). The same tendency was also found in the GWAS-related studies in OC . However, no study has explored the mechanism of the Zfp90 effect in OC development or drug resistance. To the best of our best knowledge, we are the first to investigate the role of Zfp90 in OC chemoresistance. In the current study, we presented the enhanced effect of Zfp90 inhibition on cisplatin sensitization. We initially confirmed that the inhibition of Zfp90 substantially increases the sensitization of the SK-OV-3 and ES-2 OC cells to cisplatin, which was validated by the decreasing IC50 of cisplatin. Prior studies also validated that the knockout of Zfp90 could help modulate cancer development. Yu et al., 2020, indicated that Zfp90 was regulated by NFATC2, and the knockout of Zfp90 could significantly impact the colorectal cancer (CRC) malignant phenotype, including the CRC sphere formation and tumor formation potential. They also discovered the smaller tumor size and the decrease in the tumor number in Zfp90-/- mice. Furthermore, the modulation of Zfp90 impacted the BMP4 and some oncogenic related pathways in CRC mouse models and patients . The same research team also discovered that Zfp90 might have played an important role in colitis-associated colorectal cancer (CAC) through the systemic analyses of the GWAS. They disclosed that gut microbiota depletion abolished the tumorigenic effect of Zfp90 in the CAC mouse model. The mechanistic studies indicated that Zfp90 elevated CAC development via the TLR4-PI3K-Akt-NF-kB pathway. This cascade facilitated an oncogenic environment and an innovative target for CAC prevention and treatment . Our studies showed a similar trend in that the knockdown of Zfp90 could improve the sensitization of two OC cell lines, SK-OV-3 and ES-2, to cisplatin damage in terms of cell viability and the TUNEL stain . In addition, we also confirmed that the effect of the knockdown of Zfp90 in normal human ovarian surface epithelial (HOSE) cells did not cause a significant difference in the cell viability . The HOSE cells were used as normal cells compared to the OC cell line in previous studies . Xie et al., 2016, used human normal ovarian surface epithelial cells to compare the expression of MUS81 with the SOC tissues at both the transcript and protein levels, and the expression level of the MUS81 protein in ovarian cancer cell lines was also higher than that in human normal ovarian surface epithelial cell lines. The above result showed a similar trend as us. The low expression of Zfp90 might also explain the minimal effect the knockdown of Zfp90 had on the cell viability. Many studies have highlighted that one mechanism of chemo-resistance is alterations of the apoptotic signal, which facilitates cell death not only in OC, but also in different kinds of cancer . Chowdhury et al., 2017, revealed that the binding of lectin with the receptors attributed to the phosphorylation of the Akt and ERK pathways, which also influence the downstream apoptosis signal, including Bcl-2 and Bax, is linked to the cytochrome c release and the generation of ROS in mitochondria that influence cell death . In addition, Wang et al., 2017, revealed that pterostilbene, an analog of resveratrol, could prevent Akt-modulated cytoskeleton assembly and lung cancer cell metastasis. The apoptotic pathway was also implicated in the inhibition of treating lung metastasis in the review . Furthermore, Yu et al., 2018, indicated that the knockdown of long non-coding (lnc) RNA HOTAIR could aid OC cells' sensitization to cisplatin via the stimulation of the autophagy. They observed that the transfection of si-Atg7 substantially enhanced the cisplatin-induced cytotoxic signal, including caspase-3 and Bax, and inhibited the anti-apoptosis molecule Bcl-2 in OC cells . Our analysis also revealed a similar trend in Zfp90. The inhibition of Zfp90 alone did not impact the apoptosis-related protein, such as p-P38, p-Akt and p-ERK. However, it enhanced the cisplatin-induced up-regulation of p-P38 and the down-regulation of p-Akt and p-ERK in the SK-OV-3 and ES-2 OC cells , which induced the downstream proteins Bcl-2, Bax and active caspase-3. The elevation of Bax and active caspase-3 and of the decrease in Bcl-2 induced by cisplatin were also enhanced by the knockdown of Zfp90 . Except in case of the apoptosis cascade, the migrative effect was extensively investigated. Almost 90% of cancer deaths are attributed to cancer metastasis and damage of secondary tumors . To treat OC more effectively, some analyses have focused on the inhibition of metastatic carcinoma cells and took metastasis as being crucial for cell proliferation. Qian et al., 2021, demonstrated that the kinesin family member 18A (KIF18A) was overexpressed in esophageal cancer (EC) patients, and the modulation of KIF18A could impact cancer cell migration and invasion in the EC cell lines. They also knocked-down si-KIF18A and activated the Insulin-like growth factor-II mRNA binding protein 3 (IGF2BP3) to reconfirm the role of the KIF18A function in cell movement . In addition, Zhang et al., 2019, also indicated histone H3 lysine 4 (H3K4) and H3 lysine 9 (H3K9) demethylase (KDM1A) as metastasis promoters in papillary thyroid cancer. They revealed that KDM1A could increase the MMP-9 expression and activity via binding to the active site of the tissue inhibitors of metalloproteinases-1 (TIMP-1). These effects influenced the decrease in the migrative effect in the wound healing assay and invasion assay . Furthermore, Si et al., 2020, expressed that the knockdown of cell adhesion molecules-1 (CADM1) influenced the growth, migration and invasion of OC cells. They also overexpressed CADM1 in OC cells and observed an increase in the cell growth and movements via a wound healing assay. The mechanism of action in CADM1 passed through the PI3K/Akt signaling pathway, which is comparable to our results . We conducted a wound healing assay in SK-OV-3 and ES-2 cells to evaluate the effect of Zfp90 knockdown on cell migration. The data indicated that the inhibition of Zfp90 could further decrease the cisplatin-induced down-regulation of the migrative effect in both cells. The MMPs activity also expressed the same trend. The inhibition of Zfp90 could substantially reduce the cisplatin-induced down-regulation of the MMPs activity . Some related protein expressions, including MMP-2, MMP-9 and E-cadherin, were also conducted. The cisplatin-induced down-regulation of MMP-2, MMP-9 and E-cadherin were greatly suppressed by the knockdown of Zfp90 . Although cisplatin played a significant role in the OC treatment, the issue of drug resistance in OC still requires attention. Drug resistance is always a critical issue in OC treatment . Among all the related pathways, the Nrf2/HO-1 signaling pathway has been explored significantly in cisplatin sensitization . Deng et al., 2020, revealed that the Nrf2/HO-1 pathway was determined as a drug resistance mechanism in SK-OV-3 cells, and the peroxisome proliferator-activated receptor-g coactivator 1-a (PGC1a) is implicated in the regulation of Nrf2 via increasing the p-GSK3b and p-GSK3b, which would conversely modulate the transcriptional activity of PGC1a. They demonstrated that the intervention of Nrf2 or PGC1a led to the enhancement of cisplatin sensitization in SK-OV-3 and A2780 cell lines . Li et al., 2021, outlined some factors that react to Nrf2 and cause resistance to cisplatin, including P62, CD99, ABCF2 and ATF2 . Xia et al., 2020, indicated that the overexpression of p62 in SK-OV-3 could shield the cell against vitamin K3-induced damage via an increase in the anti-oxidant genes, such as Nrf2, and the downstream factors, including HO-1 and NQO-1 . Bao et al., 2017, revealed that ABCF2 was impacted by the low expression of Nrf2, which influenced the upregulation of the cisplatin sensitization of A2780 by regulating the drug efflux pump . In our studies, we propose that Zfp90-regulated cisplatin sensitization in SK-OV-3 and ES-2 cells might occur through the Nrf2/HO-1 pathway. The up-regulation of Nrf2 and HO-1 protein expression was significantly mitigated by the knockdown of Zfp90. The upstream factor BMP-7 was also conducted by an ELISA, and the up-regulation of the BMP-7 concentration was greatly inhibited by the knockdown of Zfp90 . Conversely, we validate the association between Zfp90 and the Nrf2/HO-1 pathway via treating carnosol, a facilitator of HO-1. The data expressed that the treatment of carnosol could greatly abolish the si-Zfp90-induced enhancement of the cytotoxic effect. The SOD activity was also evaluated, and its trend is comparable to the cell viability . According to the results of our study, Zfp90 was shown to be a potential target to deal with cisplatin chemoresistance in OC via oxidative stress and the apoptotic pathway. However, further in vivo tests should be conducted to examine its role in OC chemoresistance. The data from the GWAS also showed a great difference between OC patients and normal people in terms of Zfp90 expression. We hope the above findings could help the development of target strategies employing Zfp90 siRNAs to complement the conventional chemotherapies for advanced OC. 5. Conclusions In conclusion, our data highlight that cisplatin treatment produces ROS that modulate apoptotic proteins expression (p-P38, p-ERK, p-Akt, Bcl-2, Bax and active caspase-3). The anti-oxidative signal (Nrf2, HO-1 and SOD) was also stimulated, which could inhibit cell migration (MMP-2, MMP-9, E-cadherin). The intervention of Zfp90 could substantially enhance the apoptosis pathway and inhibit the migrative pathway to regulate the cisplatin sensitivity in OC cells. Supplementary Materials The following supporting information can be downloaded at: Figure S1: The uncropped western membrane of Figure 1G (Zfp90 and b-actin in human ovarian surface epithelial cells (HOSE), ES-2 cell, SK-OV-3 cell) were provided in the supplemental information; Figure S2. The uncropped western membrane of Figure 2A of p-P38, P38, p-ERK, ERK, p-Akt and Akt in SK-OV-3 cell; Figure S3: The uncropped western membrane of Figure 2E of p-P38, P38, p-ERK, ERK, p-Akt and Akt in ES-2 cell); Figure S4: The uncropped western membrane of Figure 3A of active caspase-3, Bcl-2, Bax and b-actin in SK-OV-3 cell; Figure S5: The uncropped western membrane of Figure 3E of active caspase-3, Bcl-2, Bax and b-actin in ES-2 cell; Figure S6: The uncropped western membrane of Figure 4D of MMP-9, MMP-2, E-cadherin and b-actin in SK-OV-3 cell; Figure S7: The uncropped western membrane of Figure 4K of MMP-9, MMP-2, E-cadherin and b-actin in ES-2 cell; Figure S8: The uncropped western membrane of Figure 5A of p-Nrf2, HO-1 and b-actin in SK-OV-3 cell; Figure S9: The uncropped western membrane of Figure 5E of p-Nrf2, HO-1 and b-actin in ES-2 cell. Click here for additional data file. Author Contributions Methodology, C.-H.W., C.-L.W. and Z.-H.W.; validation, F.-H.T. and C.-L.W.; data curation, C.-H.W., C.-W.F. and F.-H.T.; writing--original draft preparation, C.-H.W., F.-H.T. and C.-W.F.; writing--review and editing, F.-H.T. and C.-Y.L.; supervision, F.-H.T.; project administration, C.-H.W.; All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement All relevant data are within the manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Effect of inhibiting Zfp90 on the cisplatin sensitivity of SK-OV-3, ES-2 and human ovarian surface epithelial (HOSE) cells. SK-OV-3 and ES-2 cells were treated with various concentrations of cisplatin (1, 10, 15, 20 mM) for 24 h and 48 h in the si-Ctrl or si-Zfp90 groups. Cell viability was determined by alamarBlueTM assay. SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 24 h in si-Control or si-Zfp90 cells, and the apoptotic effect was identified by the TUNEL assay. Cell viability of each group at (A) 24 h or (B) 48 h were observed in SK-OV-3 cell. (C) TUNEL stain of each group was detected in SK-OV-3 cell. Cell viability of each group at (D) 24 h or (E) 48 h was observed in ES-2 cell. (F) TUNEL stain of each group was discovered in the ES-2 cell. (G) Zfp90 protein expression was confirmed in the human ovarian surface epithelial (HOSE) cell, SK-OV-3 and ES-2 cells by western blotting. HOSE cells were treated with different concentrations of cisplatin (1, 10, 15, 20 mM) for 24 h. (H) Cell viability of each group at 24 h was observed in the HOSE cell. Data are expressed as the mean +- SEM (n = 8) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus same concentration cisplatin in si-Ctrl cell, respectively). Figure 2 The inhibition of Zfp90 modulated the cisplatin-induced p-P38, P38, p-ERK, ERK, p-Akt and Akt protein expression in the SK-OV-3 and ES-2 cells. The SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 1 h in the si-Ctrl or si-Zfp90 cells, and protein expression was identified by western blotting. (A) The p-P38, p-Akt and p-ERK protein expression of si-Ctrl, cisplatin, si-Zfp90, si-Zfp90 and cisplatin group were detected in the SK-OV-3 cell. Quantitative results of (B) p-P38, (C) p-ERK and (D) p-Akt were presented. (E) p-P38, p-Akt and p-ERK protein expression of si-Ctrl, cisplatin, si-Zfp90, si-Zfp90 and cisplatin group was also observed in the ES-2 cell. Quantitative results of (F) p-P38/P38, (G) p-ERK/ERK and (H) p-Akt/Akt were calculated. Total P38, ERK and Akt were used as internal control individually. The data are expressed as the mean +- SEM (n = 3) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus cisplatin group). Figure 3 The inhibition of Zfp90 modulated the cisplatin-induced active caspase-3, Bcl-2, Bax protein expression of SK-OV-3 and ES-2 cells. SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 24 h in the si-Ctrl or si-Zfp90 cells, and protein expression was determined by western blotting. (A) active caspase-3, Bcl-2, Bax protein expression of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90 and cisplatin group were detected in SK-OV-3 cell. Quantitative results of (B) active caspase-3, (C) Bcl-2 and (D) Bax were shown. (E) active caspase-3, Bcl-2, Bax protein expression of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90 and cisplatin group was also observed in ES-2 cell. Quantitative results of (F) active caspase-3, (G) Bcl-2, and (H) Bax were shown. Data are expressed as the mean +- SEM (n = 3) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus cisplatin group). Figure 4 Effect of inhibiting Zfp90 on cisplatin-induced down-regulation of the migrative effect in SK-OV-3 and ES-2 cells. SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 24 h in the si-Control or si-Zfp90 cells, and cell migration was identified by wound healing assay, ELISA and western blotting. (A) Wound healing assay of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90 and cisplatin group were observed in SK-OV-3 cell. (B) Quantitative results of SK-OV-3 wound healing assay were shown. (C) MMPs activity of each group were measured in SK-OV-3 cell. (D) MMP-2, MMP-9, E-cadherin protein expression of each group were also observed in SK-OV-3 cell and quantitative results of (E) MMP-2, (F) MMP-9 and (G) E-cadherin were shown. (H) Wound healing assay of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90andcisplatin group were observed in ES-2 cell. (I) Quantitative results of the ES-2 wound healing assay were shown. (J) MMPs activity of each group were measured in ES-2 cell. (K) MMP-2, MMP-9, E-cadherin protein expression of each group were observed in SK-OV-3 cell and quantitative results of (L) MMP-2, (M) MMP-9, and (N) E-cadherin were shown. Data are expressed as the mean +- SEM (n = 3) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus cisplatin group). Figure 5 Effect of inhibiting Zfp90 on cisplatin-induced up-regulation of p-Nrf2, HO-1 protein expression and BMP-7 protein secretion in SK-OV-3, and ES-2 cells. SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 24 h in the si-Ctrl or si-Zfp90 cells, and protein expression was ascertained by western blotting. (A) p-Nrf2, HO-1 protein expression of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90andcisplatin group were observed in SK-OV-3 cell. Quantitative results of (B) p-Nrf2, and (C) HO-1 were shown. SK-OV-3 and ES-2 cells were treated with 20 mM cisplatin for 24 h in the si-Ctrl or si-Zfp90 cells and BMP-7 protein secretion was determined by ELISA. (D) BMP-7 protein secretion of each group were observed in SK-OV-3 cell. (E) p-Nrf2, and HO-1 protein expression of si-Ctrl, cisplatin, si-Zfp90, and the si-Zfp90andcisplatin group were also observed in ES-2 cell. Quantitative results of (F) p-Nrf2, and (G) HO-1 were detected. (H) BMP-7 protein secretion of each group were also observed in ES-2 cell. Data are presented as the mean +- SEM (n = 3) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus cisplatin group). Figure 6 Effect of stimulation HO-1 on si-Zfp90-induced enhancement of cell death and down-regulation of SOD activity in SK-OV-3 and ES-2 cells. SK-OV-3 and ES-2 cells were pre-treated with carnosol (12.5 or 25 mM) for 1 h followed by 20 mM cisplatin for 24 h in the si-Zfp90 cells. Cell viability was determined by alamarBlueTM assay and superoxide dismutase (SOD) activity was determined by Superoxide Dismutase Activity Assay Kit (Colorimetric). (A) Cell viability of si-Ctrl, cisplatin, si-Zfp90, si-Zfp90 and cisplatin, si-Zfp90 and cisplatin and 12.5 mM carnosol and si-Zfp90 and cisplatin and 25 mM carnosol at 24 h were detected in SK-OV-3 cell. (B) SOD activity of si-Ctrl, cisplatin, si-Zfp90, si-Zfp90 and cisplatin, si-Zfp90 and cisplatin and 12.5 mM carnosol and si-Zfp90 and cisplatin and 25 mM carnosol at 24 h were also observed in SK-OV-3 cell. (C) Cell viability of each group at 24 h were also observed in ES-2 cell. (D) SOD activity of each group were observed in ES-2 cell. Data are presented as the mean +- SEM (n = 8) (*, p < 0.05, versus si-Ctrl group; #, p < 0.05, versus cisplatin group; and, &, p < 0.05, versus si-Zfp90 plus cisplatin group). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000493 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050966 foods-12-00966 Article Comparison of Commercial Fish Proteins' Chemical and Sensory Properties for Human Consumption Partanen Moona Validation Formal analysis Investigation Resources Writing - original draft Visualization 12* Honkapaa Kaisu Conceptualization Investigation Resources Writing - review & editing Supervision Project administration Funding acquisition 1 Hiidenhovi Jaakko Conceptualization Formal analysis Writing - review & editing 3 Kakko Tanja Conceptualization Formal analysis Writing - review & editing 4 Makinen Sari Formal analysis Writing - review & editing Funding acquisition 3 Kivinen Sanni Formal analysis Investigation Writing - review & editing 4 Aitta Ella Formal analysis Writing - review & editing Visualization 4 Vakevainen Kati Writing - review & editing Supervision 2 Aisala Heikki Conceptualization Methodology Formal analysis Writing - review & editing Supervision 1 Zeng Hongliang Academic Editor Zhang Yi Academic Editor 1 VTT Technical Research Centre of Finland Ltd., Tietotie 2, 02150 Espoo, Finland 2 Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70210 Kuopio, Finland 3 Food and Bioproducts, Production Systems, Natural Resources Institute Finland (Luke), Myllytie 1, 31600 Jokioinen, Finland 4 Food Sciences, Department of Life Technologies, University of Turku, 20014 Turku, Finland * Correspondence: [email protected]; Tel.: +358-40101198 24 2 2023 3 2023 12 5 96631 1 2023 20 2 2023 22 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). To stop overfishing and meet the protein needs of a growing population, more information is needed on how to use marine by-catches, by-products, and undervalued fish species for human consumption. Turning them into protein powder is a sustainable and marketable way to add value. However, more knowledge of the chemical and sensory properties of commercial fish proteins is needed to identify the challenges in developing fish derivatives. This study aimed to characterize the sensory and chemical properties of commercial fish proteins to compare their suitability for human consumption. Proximate composition, protein, polypeptide and lipid profiles, lipid oxidation, and functional properties were analyzed. The sensory profile was compiled using generic descriptive analysis, and odor-active compounds were identified with gas-chromatography-mass spectrometry-olfactometry (GC-MS/O). Results indicated significant differences in chemical and sensory properties between processing methods but not between fish species. However, the raw material had some influence in the proteins' proximate composition. Bitterness and fishiness were the main perceived off-flavors. All samples, apart from hydrolyzed collagen, had intense flavor and odor. Differences in odor-active compounds supported the sensory evaluation results. The chemical properties revealed that the lipid oxidation, peptide profile, and raw material degradation are likely affecting the sensory properties of commercial fish proteins. Limiting lipid oxidation during processing is crucial for the development of mild-tasting and -smelling products for human consumption. fish by-products lipid oxidation functional properties generic descriptive analysis volatile compounds nutritional value chemical characterization Finnish Operational Programme of the European Maritime and Fisheries Fund33338 This research was funded by the Finnish Operational Programme of the European Maritime and Fisheries Fund (the Project "Blue Welfare Network-Blue Products", Project no. 33338). pmc1. Introduction Fish is known to be one of the most nutritious foods on the planet , and it plays a major part in the future as a protein source as the population and the prevalence of malnutrition increase . However, overfishing of popular species is an increasing problem threatening aquatic resources , which urges the fish industry to utilize fishes and their by-products more efficiently. Over 20 million tons of fish are used as feed annually, even though 90% of it is food-grade fish . The majority of fishes used for feed are small fish that are hard to fillet and often have an unpleasant taste, color, or texture . To better utilize small food-grade fishes for human consumption, they can be processed into fish protein with, e.g., enzymatic hydrolysis, heat treatment, or pH-shift isolation . In addition to small fish, fish by-products can be used as raw material for fish proteins. By-products can cover up to 70% of fish and they are often used as feed . Despite fish proteins being excellent protein sources for humans, the demand is still low. This is likely due to their fishy odor and taste . Although several studies have been conducted about fish proteins, the information is dispersed, and the production methods and raw materials vary between studies. The study by Nisov et al. compared the chemical, functional, and sensory properties of fish proteins that were enzymatically hydrolyzed and pH-shift isolated from two different fish species. However, the study did not investigate explanatory factors for sensory challenges, such as volatile compounds or lipid oxidation. Similarly, the study by Aspevik et al. compared hydrolysates prepared from the heads and backbones of three fish species for their suitability in food products but did not consider functional properties and only examined peptide size as an explanatory factor for sensory evaluation results. To the best of our knowledge, there is currently no study that has analyzed the sensory profile of fish proteins using GC-MS-O in combination with sensory analysis. Additionally, most studies to date have only analyzed fish proteins produced at a laboratory scale. Therefore, a study on commercial fish proteins is necessary for the further development of food-grade fish proteins. This study aimed to characterize the chemical, functional, and sensory properties of commercial fish proteins and protein derivatives (fish concentrates, fish hydrolysates, and fish collagen) to compare the suitability of different production methods and fish species for human consumption as well as evaluate the processes causing sensory properties that are limiting the demand of food-grade fish proteins. Explaining factors such as free amino acids, lipid oxidation, and volatile compounds were analyzed to better understand the usability of these proteins. 2. Materials and Methods 2.1. Materials In April 2022, efforts were made to procure a large sample set of food-grade fish proteins from multiple manufacturers. However, the availability of such proteins remains constrained in the industry. A sample set of six commercial fish proteins could be acquired from reputable European manufacturers of fish proteins, except the hydrolyzed fish collagen was purchased directly from the retail store. The processing methods and fish species and parts used for the protein are presented in Table 1. Altogether, three fish concentrates (CONC1-3), two hydrolysates (HYDR1-2), and one hydrolyzed fish collagen (COLL1) were analyzed. All the samples were dried protein powders. Samples were received through the postal service at room temperature. After arrival at the research facilities, the samples were stored at -18 degC. The pH of the samples was measured before analyses after 30 min of mixing in a 5% water solution. To demonstrate the behavior of fish protein in use, the pH of all samples was left neutral (ranging from 6.4 to 7.1) without any adjustment. 2.2. Proximate Composition Crude protein was determined with the Dumas combustion method using rapid MAX N exceed equipment (Elementar Analysensysteme GmbH, Langenselbold, Germany), where a conversion factor of 5.58 was used for nitrogen as recommended by Mariotti et al. for the amino acid distribution of fish. For hydrolyzed collagen, 5.4 was used as a conversion factor following the earlier report of Ardekani et al. for the protein content of catfish derived gelatin. Analyses were performed in triplicate. Lipids of all samples except for COLL1 were extracted as reported by Damerau et al. with slight modifications. Briefly, 3-6 g of fish protein powder was suspended with 7 mL of 8.8% potassium chloride and the mixture was homogenized with an Ultra-Turrax (T 25 digital ULTRA-TURRAX(r), IKA(r)-Werke GmbH & Co. KG, Staufen, Germany) for 2 min. After the addition of 12 mL of 2-propanol and 12 mL of hexane, the mixture was homogenized again for 2 min, after which 12 mL of hexane was added. The mixture was vortexed for 1 min, and centrifuged (4 degC, 3000 rpm, 20 min), after which the upper phase was collected. The extraction was repeated with 30 mL hexane, and the organic phases of both extractions were collected. The collagen sample, due to its extremely low lipid content, was extracted using a Bligh and Dyer method, as reported by Ozogul et al. . The lipid content of all samples was measured gravimetrically after evaporation of the organic solvent. Analyses were performed in triplicate. The moisture and ash content were determined gravimetrically by drying the samples for 24 h at 105 degC for moisture and by combusting the samples in a muffle furnace (model N11, Nabertherm GmbH, Lilienthal/Bremen, Germany) at 550 degC for ash. Analyses were performed in triplicate. 2.3. Amino Acids and Peptide Profile 2.3.1. Amino Acids Total amino acid composition and free amino acids were determined as a subcontracted service with Ion Chromatography-UV-detector (IC-UV) using the ISO 13903:2005; EU 152/2009 standard method. With cysteine + cystine and methionine, the samples were oxidized with hydrogen peroxide and formic acid before the hydrolysis. The detection was carried out using post column derivatization with ninhydrin reagent at 440 and 570 nm. Tryptophan was determined using the ISO 13904:2016 standard method which included high-performance liquid chromatography (HPLC) and alkaline hydrolysis. Analyses were performed in triplicate. 2.3.2. SDS-PAGE Peptide weight was determined in reducing conditions by sodium dodecyl sulfide polyacrylamide gel electrophoresis (SDS-PAGE) according to Nisov et al. . The commercial Criterion TGX (Tris-glycine extended) stain-free precast gel (4-20%, 30 mL 18-well, Bio-Rad, Hercules, CA, USA) was used for the analysis. The molecular weight (MW) of protein bands was estimated using Precision Plus ProteinTM standards (10-250 K, Bio-Rad Lab., Inc., Hercules, CA, USA). Analyses were performed in duplicate. 2.3.3. Molecular Weight (MW) Distribution by Using Size-Exclusion Chromatography Size-exclusion chromatography (SEC) of commercial protein samples was performed by using Akta pure 25 M chromatographic system (Cytiva Sweden AB, Uppsala, Sweden) equipped with ALIAS Bio autosampler (DURATEC Analysentechnik GmbH, Hockenheim, Germany) with Superdex 75 HR 10/30 column (GE Healthcare Life Sciences, Uppsala, Sweden). The analysis was performed according to Makinen et al. . The total surface area of the chromatograms was integrated and separated into four MW ranges (>10,000, 1000-10,000, 200-1000, <200 Da), and the results were expressed as a percentage of the total area. Analyses were performed in quadruplicate. 2.4. Fatty Acid Composition Extracted oil (Section 2.2) was dissolved in chloroform and fatty acids were derivatized to methyl esters (FAME) using transesterification procedure with 2% (v/v) sulfuric acid in methanol . A gas chromatograph (model 6890 N, Agilent Technologies, Santa Clara, CA, USA) fitted with a CP-Sil 88 column (100 m x 0.25 mm i.d., 0.2 mm, Agilent Technologies, Santa Clara, CA, USA) and flame ionization detector were used in quantifying FAME. A temperature gradient program was used in the oven, and hydrogen was used as the carrier gas (constant pressure 206.8 kPa; nominal initial flow rate 2.1 mL min-1 ). The fatty acid composition was calculated as weight percentages using theoretical response factors . Analyses were performed in duplicate. 2.5. Lipid Oxidation The content of thiobarbituric acid reactive substances (TBARS) in the samples was measured according to Logren et al. . Briefly, malondialdehyde (MDA) was released from proteins using alkaline hydrolysis after which acid precipitation was used to diminish the proteins. Supernatants were reacted with thiobarbituric acid (TBA) to form MDA-TBA adducts and Ultra-High-Performance Liquid Chromatography (UHPLC) analysis was used to measure the MDA-TBA adducts. Analyses were performed in quadruplicate. Peroxide values (PVs) were determined from the extracted lipids using a ferric thiocyanate method as described by Lehtonen et al. . PV could not be analyzed from samples COLL1 and HYDR2 due to their extremely low lipid contents. Results were calculated as meq/kg powder ("as is") based on the lipid content of the powders. Analyses were performed in triplicate. 2.6. Determination of Functional and Sensory Properties 2.6.1. Functional Properties The nitrogen solubility was determined by dissolving 2.5 g of sample in milliQ water until 50.0 mL was reached. The 5% solution was mixed constantly for 30 min. The solution was centrifuged for 15 min at 10,000x g and the supernatant was collected for protein content measurements with the Dumas method (Section 2.2). Analyses were performed in triplicate. Foaming capacity (FC) and foaming stability (FS) were determined from 5% (w/w) solution as described by Nisov et al. . The foam was produced by Aerolatte (UK) by keeping the mixer 60 s still at the bottom of the measuring cylinder. The total volume (upper limit of the foam) and drainage (upper limit of the liquid part) were measured at time points of 0, 1, 5, 10, and 20 min. The results are presented as percentage of volume compared to the original volume. Analyses were performed in triplicate. Heat induced gelation was evaluated according to Nisov et al. . One milliliter of 15% (w/w) protein-water solutions was pipetted to a 2 mL tube, stirred, and heated at 98 degC for 20 min. Heated tubes were placed in a refrigerator overnight. The sample was classified as gel if the sample stayed at the bottom of the tube after tilting it upside down. Analyses were performed in triplicate. Water holding capacity (WHC) was determined following the AOAC method 56-30.01. Fat binding capacity (FBC) of protein samples was determined by modified procedure of Cho et al. . Briefly, 20 mg of protein sample was mixed with 1 mL of rapeseed oil and held at room temperature. The protein-oil mixture was stirred with a vortex mixer for 5 s at a time interval of 15 min. After 1 h, mixtures were centrifuged at 450x g for 20 min. The upper phase was removed, and the tube was drained for 30 min on a filter paper by tilting to a 45 angle. The FBC were calculated as the weight of the contents of the tube after draining divided by the weight of the dried protein sample and expressed as the g of oil/g of dried protein. Analyses were performed in triplicate. 2.6.2. Sensory Properties The color of the samples was measured with a colorimeter (Minolta Chroma meter, CR-200 Handheld, Osaka, Japan) by filling 50 mm plastic petri dish with the sample. The results were reported in the CIE system as lightness (L*), red-green (a*), and yellow-blue (b*). Analyses were performed with five replicate measurements. The whiteness of the samples was calculated using the following equation :(1) Whiteness=100-100-L2+a2+b2 The sensory profile was determined with general descriptive analysis (GDA) . Nine panelists from VTT Technical Research Centre of Finland's trained sensory panel were recruited to evaluate the three-digit coded and randomized samples. The panel consisted of 6 females and 3 males. Informed consent was obtained from the panelists before the evaluation, where the possible allergens (fish and seafood) were disclosed, and the response confidentiality was assured. The panelists could withdraw themselves from the evaluation at any time without giving a reason. The microbiological safety of the tested products was assessed before the evaluations. The evaluations were performed as a taste-and-spit assay. Odor and appearance were analyzed from 5% (w/w) solutions of fish proteins in tap water whereas flavor and mouthfeel properties were analyzed from 1% (w/w) solutions. A volume of 30 mL of solution was given to the assessors. The samples were served in a randomized Latin square serving order. Appropriate concentrations of the protein solutions and preliminary lexicon for the samples were discussed with a subsection of the panelists and sensory experts. Altogether 15 sensory attributes were chosen for GDA (6 taste attributes, 4 odor attributes, and 5 mouthfeel, texture, and appearance attributes). Panelists were provided with reference samples for some attributes. The evaluated attributes and their respective descriptions and selected reference samples are listed in Supplementary Materials (Table S1). The intensities of the sensory attributes were evaluated in triplicate using an unstructured line scale with labeled endpoints ranging from no intensity (0) to high intensity (10) using EyeQuestion software version 5.0.8.5 (EyeQuestion Software, Logic8 B.V., Elst, The Netherlands). 2.6.3. Odor-Active Volatile Compounds Volatile compounds were determined using HS-SPME-GC-MS/O. First, three samples (CONC3, HYDR1, and HYDR2) chosen by pretesting were analyzed with GC-MS-O with four trained assessors using detection frequency method for the identification of odor-active compounds. Then, relative concentration (RC) was determined for all samples by adding 1-butanol (1048 ng/vial) as an internal standard (ISTD), whose RC was set to 100, and comparing the compound area to ISTD's compound area using the following equation:RC = (Compound area)/(ISTD's compound area) x ISTD RC(2) The odor-active compounds were collected from all identified volatile compounds with two methods: (1) collecting all odor-active compounds identified with GC-MS-O analysis and (2) additional compounds found in GC-MS analysis that have been determined as odor-active in prior literature . The GC-MS/O analysis was performed using an Agilent 6890N gas chromatograph equipped with an Agilent 5973 mass spectrometer (Agilent Technologies, Santa Clara, CA, USA), with olfactometry ODP4 sniffing port, (Gerstel, Linthicum, Maryland, USA) and PAL3 autosampler system (RTC, CTC Analytics AG, Swingen, Switzerland). Samples were analyzed with a capillary column Vf-Wax (60 m x 0.25 mm i.d. x 0.5 mm, Agilent Technologies, Santa Clara, CA, USA). High-purity helium was applied as the carrier gas. GC eluent was split 1:1 with the detectors. With MS, the ion detection range was 25-450 m/z, the temperatures were 250 degC for the ion source and 150 degC for the quadrupole. The injector temperature was 250 degC. The temperature program for GC was modified based on Kakko et al. : 40 degC held for 3 min, 40-150 degC at a rate of 12 degC/min, 150-240 degC at the rate of 10 degC/min and held at 240 degC for 5.8 min. The temperature for olfactometry and the transfer line was 220 degC. Samples were incubated (60 degC, 20 min) in 25% (w/v) water solution, and the volatile compounds were collected from the headspace of the 20 mL vial to SPME fiber (2 cm, DVB/CAR/PDMS, phase thickness 50/30 mm, Supelco Inc., Saint Loius, MO, USA). Samples were injected in splitless mode with a purge time of 8 min. Analyses were performed in triplicate. The three samples that were first analyzed with the GC-MS-O were also analyzed with two assessors with an Agilent 6890 GC-FID/O (Agilent Technologies, Santa Clara, CA, USA) equipped with DB-5 (60 m x 0.25 mm i.d. x 1.0 mm, Agilent Technologies, Santa Clara, CA, USA) column to confirm the compound candidates. GC-FID/O used the same GC parameters as GC-MS-O. FID temperature was 220 degC. 2.7. Statistical Analysis The data were analyzed with analysis of variance (one-way ANOVA) with Tukey's post hoc analysis using <5% as a limit for statistical significance. Kruskal-Wallis one-way ANOVA was used when the results were not normally distributed. Normality was tested with a Shapiro-Wilk test and by visual inspection of the distributions. With sensory evaluation, data were analyzed with a two-way mixed model analysis of variance (two-way ANOVA) with samples as the fixed factor and the assessors as a random factor. Statistical analysis was performed with IBM SPSS Statistics 28 for Windows (Version 27, IBM Corp., Armonk, NY, USA). The multivariate analyses were performed with Unscrambler X (version 10.5.1, Camo Software AS, Oslo, Norway). The panel performance in the sensory evaluation was analyzed with PanelCheck (version 1.4.2, Nofima, Tromso, Norway). 3. Results and Discussion 3.1. Proximate Composition The proximate composition of the samples is presented in Table 2. Overall, the concentrates contained more total lipids and ash compared to the hydrolyzed samples. All the samples were high in protein, but the hydrolysates had the highest protein content. With HYDR2 and COLL samples the ash content was remarkably low. With enzymatic hydrolysis, the soluble peptides are separated and collected from lipids and other insoluble matter but with heat treatment, the fat cells are merely ruptured, and the lipids are pressed out from minced raw material . These differences in processing methods cause variation in the proximate composition. For the COLL1 sample, the conversion factor for protein is most likely too high, since the proximate composition is over 107% with the lipids, moisture, and ash taken into consideration. However, when we sum up the amino acids in the COLL1 sample (see Section 3.2.1 Amino acids), it sums up to 87.7 +- 16.65 g or protein/100 g of sample. This is likely closer estimation of the true protein content. The part of fish used as a raw material in the fish proteins did not have an influence on the practical level the proximate composition of the samples, since the CONC2 (cod filleting by-products) and CONC3 (only cod backbones) had only minor differences between them. On the other hand, the results showed the effect of the raw material and the processing method on the lipid content of the samples. For example, in sample CONC1 (cod, saithe, and haddock), the lipid content was higher than in sample CONC2 (only cod). In addition, the HYDR2 (by-products of salmon filleting) had fewer lipids than HYDR1 (whole blue whiting), even though salmon is generally considered a slightly fattier fish than blue whiting. The total lipid content of sample CONC3 was 4.2% in dry matter, which is less than previously reported in the concentrate made from cod backbone (8.8-9.3%) and more than reported with concentrates made from saithe and haddock fillets (0.5-0.6%) . The difference may be due to the processing or lipid extraction methods. Saithe and haddock fillets were analyzed with Soxhlet extraction, which is ineffective for extracting fish oil . A study by Egerton et al. found the lipid content of blue whiting hydrolysates to be between 0.0-3.0% of dry weight which is similar to the hydrolysate sample tested in this study (HYDR1, 0.4%). However, Slizyte et al. reported a 2.2-6.2% lipid content of salmon backbone hydrolysates, which is different from the sample HYDR2 (0.1%) in this study. Despite the different findings, the methods used in both studies and the samples tested in this study are similar and the results are considered comparable. The lipid content of fish collagen from different species and fish parts is reported to be 0.2-1.2% similar to the COLL1 sample (0.1%). Overall, the lipid content of concentrates is higher than hydrolysates and the collagen samples have a very low level of lipid content. 3.2. Amino Acid and Peptide Profile 3.2.1. Amino Acids Total amino acids of the commercial fish proteins are presented in Table 3. Amino acid content was the same across concentrates and hydrolysates with only minor statistically significant differences. The essential amino acid to non-essential amino acid ratios were high in concentrates and hydrolysates. Previously, pH-shift extracted protein isolates from two fishes were found to have higher essential to non-essential amino acid ratios compared to hydrolysates from same raw materials . COLL1 on the other hand had major differences compared with the other proteins. Concentrates and hydrolysates contained adequate amounts of all essential amino acids. As expected, COLL1 lacked tryptophane and had low amounts of other essential amino acids as well. The only essential amino acid that COLL1 collagen had adequately was lysine. The lysine content was high also in concentrates and hydrolysates . COLL1 had high amounts of glycine, proline, hydroxyproline, and alanine, which was in line with previous studies . These amino acids were also high in HYDR2, which therefore likely contains collagen . This could be due to the proportionally high amount of fish skin in salmon by-products compared to, e.g., whole blue whiting (HYDR1). CONC3 differed from CONC1 and CONC2 samples only with tryptophan and even with that, the difference was minimal. This is consistent with other studies. For example, Aspevik et al. found that both backbones and heads have high nutritional values. Neither the fish species nor the part of the fish used seemed to affect to the nutritional quality of the protein in concentrates and hydrolysates. Free amino acids are presented in Table 4. Generally, the hydrolysates contained more free amino acids than concentrates or hydrolyzed collagen. Especially high free amino acid content can be found with sample HYDR1. Free amino acids were measured as an explaining factor for sensory properties and therefore they are discussed more in Section 3.6. 3.2.2. Peptide Profile The duplicate SDS-PAGE runs showed consistent molecular weight distribution results and therefore only one of the runs is presented in Figure 1. Hydrolyzed collagen often leads to peptides ranging from 3-5 kDa , as demonstrated previously with fish . As expected, the collagen sample showed no bands except one very light band smaller than 10 kDa. Samples HYDR1 and HYDR2 showed molecular weight under 10 kDa apart from faint band with HYDR1 sample over 250 kDa. Nisov et al. reported a similar faint band with hydrolyzed fish protein. However, the band over the 250 kDa mark did not appear in the HYDR2 sample which might be due to heavy filtration. The protein concentrates showed a larger variation of different bands with an intense band at approximately 40 kDa referring to actin, which have been found previously with pH-shift method . A band between 15 and 20 kDa indicated myosin light chains and the faint band between 150 and 250 kDa indicated myosin heavy chains. Samples CONC1 and CONC2 had degraded more than CONC3, which could be due to a different raw material. No significant differences were seen between fish species in CONC samples, which was expected since all the raw materials belonged to the same Gadidae family. As can be seen from the SEC chromatograms , compounds with a molecular weight greater than 10 kDa comprised the most prominent fraction in the CONC samples . Both CONC1 and CONC2 had almost identical MW distribution profiles, while CONC3 had a lower proportion of compounds with molecular weight < 1 kDa compared to the other protein concentrates. It should be noted that the amount of dissolved protein obtained by Bio-Rad DC Protein Assay (Bio-Rad Laboratories, Hercules, CA, USA) for the fish concentrate samples was very low: 0.3 mg/mL, 0.4 mg/mL, and 0.6 mg/mL for CONC1, CONC2, and CONC3, respectively. Thus, obtained SEC profiles represent dissolved protein, not the total protein. However, it was found that the protein solubility for CONC samples was very low. Therefore, the obtained SEC results correspond well to the experiments performed in aqueous solutions. The most prevalent fraction in both hydrolysate samples was 1-10 kDa. With HYDR1, compounds above 10 kDa were almost negligible, while with HYDR2 they were moderately present at about 15% of total protein . In the HYDR1, the proportion of compounds below 1 kDa, which correspond to peptides of fewer than ten amino acids or free amino acids, was the highest among the examined samples. Surprisingly, in HYDR2 their proportion was even lower than in CONC samples. The results show that in sample HYDR1 the enzymatic treatment effectively hydrolyzed the fish proteins into peptides, having MW < 1 kDa. In general, bioactive peptides that are suitable for use in therapeutic foods primarily have a molecular weight of less than 1 kDa . Although the proportion of > 10 kDa in the COLL1 sample was of the same order of magnitude as in the CONC samples, the SEC profile was different. It lacked the major peak near the void volume typical of CONC samples . In addition, there were practically no compounds smaller than 1 kDa in the COLL1 samples. 3.3. Fatty Acid Composition Fish oil is widely regarded as an important source of long-chain polyunsaturated fatty acids (PUFA), particularly eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3). Eating fish has many health benefits that have been linked to n-3 fatty acids. For example, clinical trials have shown that fish oils prevent arterial hypertension, type 2 diabetes, and memory impairment in older people . Indeed, the European Food Safety Authority (EFSA) has approved several health claims related to EPA and DHA, listed in Valimaa et al. . The fatty acid compositions of the commercial protein concentrates are shown in Table 5. The fatty acid compositions of HYDR1, HYDR2, and COLL1 could not be determined due to analytical problems. However, the total amount of lipids in these samples were very low (0.4%, 0.1%, and 0.1%, respectively), making the composition of the fatty acids an unimportant factor. All protein concentrates were good sources of n-3 fatty acids as in CONC1, CONC2, and CONC3 the proportion of n-3 fatty acids was 29.2%, 34.2%, and 40.9% of the total amount of fatty acids, respectively. No statistically significant differences were found between the samples. Interestingly, the amount of DHA seemed to be inversely proportional to the oxidation of the concentrates. According to Falch et al. , the DHA content of cod, saithe, and haddock by-products was of the same order of magnitude (except for saithe caught in winter it was lower). Since CONC1 is made from the by-products of cod, saithe, and haddock, and CONC2 and CONC3 from the by-products of cod filleting and backbone, respectively, the DHA concentrations of the samples could be expected to be quite similar. Therefore, the lower DHA content of CONC1 may be due to the degradation of DHA caused by oxidation. 3.4. Lipid Oxidation Primary lipid oxidation in fish protein concentrates and hydrolysates were assessed by quantification of PVs . Due to the extremely low lipid content of COLL1 and HYDR2 (0.1% and 0.1%, respectively), no PVs were obtained for these two samples. Of the rest of the samples, HYDR1 had by far the lowest PV. The concentrates (CONC1, CONC2, and CONC3) had higher PVs compared to the hydrolysate, but considerably lower than what was previously observed for roach and Baltic herring protein isolates (3-25 meq/kg sample) , and lower than for Nile tilapia muscle during frozen storage (1.7-4 meq/kg sample) . CONC1 (by-products of cod, saithe, and haddock) had a significantly higher PV (meq/kg powder) compared to CONC2 and CONC3 from cod, which was likely due to its higher lipid content (Table 2). However, due to the fast decomposition of hydroperoxides, PV should be considered together with secondary lipid oxidation products. Lipid oxidation in the fish protein concentrates and hydrolysates was assessed further by measuring the TBARS as MDA content . MDA is formed as a secondary product in the lipid oxidation . Among the samples, HYDR1 showed the highest MDA content whereas COLL1 had the lowest . The higher MDA concentration of the HYDR1 in comparison to the COLL1 could be partly because the HYDR1 sample has a higher total lipid content (Table 2), but it is unlikely that this is the major factor. This is because the CONC samples, which contained even more lipids (fats) than the HYDR1 sample, had a lower concentration of MDA. The results suggest that fish species is one putative factor affecting the lipid oxidation level. Among the samples, HYDR1 is the only one prepared from blue whiting. Thereby, the results indicated that blue whiting fatty acids may be more susceptible to oxidation in comparison to the other samples. The MDA content of HYDR1 was similar to protein hydrolysate prepared from saithe fillets with alkali aided hydrolysis (90.5 nmol/g) . In addition, higher MDA content compared to this study have been reported for example, for pickled Baltic herring fillets and marinated Atlantic herring . 3.5. Functional Properties The functional properties of fish proteins are presented in Figure 6. Protein solubility in water results follow the consensus that protein hydrolysates are extremely soluble due their low molecular mass and high concentration of ionizable groups whereas protein concentrates are less soluble due to protein denaturation caused by heating during processing . However, if only the middle soluble part of heated fish-water suspension is collected in protein concentrate production, the proteins have higher solubility ranging from 63.4% to 87% as demonstrated by Sathivel et al. . Solubility is a crucial functionality in proteins as it affects proteins' WHC, gelation, foaming, and emulsification abilities and thus the usability of the product in foodstuffs . FBC is an important function in a protein since the fat-binding ability affects the mouthfeel and texture of the food . FBCs were low in all samples compared to previous literature with hydrolysates and concentrates . In comparison, the hydrolyzed samples had higher FBC than concentrated samples, since with enzymatic hydrolysis more hydrophobic peptides are available . Protein ingredients need to possess some water holding capacity to function in a food matrix since it fundamentally affects the texture properties such as mouthfeel and juiciness . WHC of the food-grade samples is presented in Figure 6C. The WHC of CONC samples was good compared to plant and soy protein and very similar to whey protein . Fish meals have been reported to have even higher WHC . Hydrolyzed samples had poor WHC compared to previous research . Hydrolysates were expected to have higher WHC due to hydrolysates' low molecular weight and high protein-water interactions, but the solubilization of hydrophilic protein groups might affect WHC . Foaming properties of proteins affects the body, smoothness, and lightness of the food . Hydrolyzed samples showed better FC than the protein concentrates . Enzymatic hydrolysis has been shown to improve FC in various matrices . The FC of the hydrolyzed samples was over 200%, which is quite high compared to previous research . However, good FC indicates a suitable degree of hydrolysis and high solubility . High solubility and hydrophobic amino acids have been associated with better FS . The effect of hydrophobic amino acids does not seem to be significant with fish proteins, since HYDR1 has the most hydrophobic amino acids but has the poorest FS . Gelling properties of proteins affects the texture of food, mainly juiciness, body, and mouthfeel . Unfortunately, none of the samples showed any gelation properties at 15% concentration. To form a rigid gel network, proteins need to form covalent bonds and aggregate between denaturized protein strands . The lack of gelling properties can be a result of a too-high degree of hydrolysis . With concentrates, the low solubility and higher fat content can be factors behind lack of gelation properties. However, surimi or isolates produced with pH-shift can form gel networks usable in food solutions . To sum up, regarding the functionality of the proteins, the usability of fish proteins mainly depends on the production method. Based on solubility and foaming properties, fish protein hydrolysates (HYDR and COLL samples) could be used in liquid-based foods or beverages in addition to solid foods . On the contrary, with good WHC, fish protein concentrates (CONC samples) could be added to solid foods to add nutritional value to, e.g., pasta, but due to the low solubility, the possibly gritty mouthfeel could decrease the pleasantness of the fortified food. 3.6. Sensory Evaluation, Odor-Active Compounds, and Other Explanatory Factors The color of the samples is presented in Table 6. Nisov et al. found hydrolyzed herring and roach proteins whiter than pH-shifted alternatives. However, Sathivel et al. found even higher whiteness values when studying herring and arrowtooth flounder (Atheresthes stomias) protein powder produced by heat treatment. Sathivel et al. determined that lipid oxidation plays a role in yellow discoloration. This negative correlation was also seen in the present study: HYDR1 had the highest TBARS values (100.5 nmol MDA/g) and the lowest whiteness value of all the hydrolyzed samples (66.4). In addition, HYDR1 had the highest yellow-blue value (27.0) of all samples. CONC1 had a significantly higher peroxide value (15.3 meq/kg oil) and TBARS (33.1 nmol MDA/g) values of all CONC samples and the lowest whiteness value (62.5) of all the samples. The appearance of the fish proteins could possibly be improved if lipid oxidation is prevented. The intensities of the sensory properties are found in Table 7, and the spider plot of mean values is found in the supplementary materials . The sensory evaluation clustered the proteins according to their processing method, which has been observed previously by Nisov et al. . However, all the proteins were equally intense in flavor and odor except for COLL1. The PLS correlation loadings plot of explanatory factors for the sensory properties of fish proteins is presented in Figure 7. Umami taste was strongly associated with HYDR1, which could be due to relatively large amounts of free glutamic acid and aspartic acid compared to other samples . Additionally, complex flavor formation has been associated before with a large number of free amino acids , which could be affecting the taste of HYDR samples. In GDA, hydrolysates were found to be more bitter and more metallic than the concentrates. The results were in accordance with previous studies that demonstrated bitterness to be the main sensory challenge with fish hydrolysates . The peptide size analysis showed that the HYDR 1-2 samples consisted mostly of peptides under 10 kDa, which have previously been associated with a bitter taste . Peptides with exposed hydrophobic side chains are associated with a bitter taste , and with smaller peptides, more side chains are exposed leading to a more bitter taste. Contrary to the results of Halldorsdottir et al. , the secondary lipid oxidation products did not seem to affect the intensity of bitterness in this study: HYDR2 was perceived as more bitter than HYDR1, which had significantly higher TBARS values. Hydrophobic amino acids (Trp, Phe, Val, Leu, Iso, Try) are a key factor affecting the bitterness of the protein . However, significant differences could not be found in the amino acid analysis between concentrates and hydrolysates, but the free amino acid analysis showed a clear and significant increase of hydrophobic amino acids in hydrolysates compared to concentrates. These free amino acids combined with peptide size are likely the key factors affecting the bitterness of the hydrolysates. A diverse peptide size distribution was found in CONC samples (see Section 3.2.2. Peptide profile), which has been associated with complex taste sensations that can be affecting the formation of fishy flavor and flavor intensity. The nearly tasteless COLL sample had the most monotonous peptide size distribution. A total of 33 compounds were detected with GC-MS-O, from which 20 could be identified. After including the additional compounds typically mentioned in the literature (as described in Section 2.6.3) via the GC-MS, 46 different odor-active compounds likely affecting the odor and taste of the fish proteins were found. Out of these 46 compounds, 33 could be identified. It is important to mention that the compounds detected through olfactometry play a larger role in creating the odor of fish protein and therefore are given more emphasis in the discussion. Detection frequencies (DF) of compounds detected with GC-MS-O are found in supplementary materials (Table S2). The compounds and their relative concentrations are presented in Table 8. Four compounds could not be quantified with GC-MS, so with those compounds and with unidentified compounds, only detection frequency is shown. Hydrolyzed samples had more unidentified odor-active compounds suggesting the need for further information on compounds affecting fish hydrolysates' odor, such as brothy odor. The odor and flavor properties identified with GDA correlated well with the odor-active compounds. The PLS correlation loading plot found in supplementary materials showed a correlation between odor and taste intensity and methional, trimethylamine (TMA), and 3-methylbutanal. Methional has such a low odor threshold that it could be a significant compound affecting the odor and taste intensity. Trimethylamine has been determined to be one of the most important fishy odor sources in fish products . All the samples, apart from COLL1, contained trimethylamine. The prevention of TMA formation is crucial for producing fish proteins with mild odor and taste. Recently, Goris et al. demonstrated enzyme-mediated conversion to TMAO as a working approach to reduce the TMA content in fish proteins. 3-Methylbutanal is formed by the degradation of isoleucine and the concentration increases as the degradation of fish progresses . 3-Methylbutanal has previously been found, for example, in surimi samples and Baltic herring . This sour-bread-smelling compound could be affecting the overall odor and taste intensity in processed fish products. The concentrates were found to be fishier and more sea or seaweed-like than the hydrolysates, which have been reported to be an issue with all fish proteins regardless of the processing method . In addition to TMA, fishiness of the sample has largely been associated with secondary lipid oxidation products . However, fishiness did not seem to be associated with TBARS, since the values were the same between, e.g., samples HYDR2 and CONC3, but the fishy odor and taste intensity differed largely between the samples. Association between fishiness and lipid oxidation was found from the odor-active volatile compounds. Fish protein concentrates had the most abundant amounts of lipid oxidation derived volatile compounds, such as 2,3-butanedione, (Z)-4-heptenal, octanal, heptanal, and hexanal. These compounds have been associated with fishy odor and taste development . 2,3-Butanedione, (Z)-4-heptenal, and hexanal were previously reported as significant odorants in pH-shifted protein isolate from Baltic herring . COLL1 was the whitest, and mildest in taste and odor, which are desired properties of fish protein. The COLL1 was positioned on the opposite side of the ellipse from odor-active compounds such as TMA, (Z)-4-heptenal, methional, and 3-methylbutanal . This indicates that this study successfully identified the odor-active compounds of fish commercial fish proteins. However, rotting-cabbage-smelling methanethiol, which was detected also with GC-MS-O, was associated with the COLL1 sample, which could be affecting its mild odor, and thus the odor activity of methanethiol should be taken into consideration. Methanethiol has been previously found in fish sauce . Methanethiol, hydroxyacetone, and 2-heptanone were found in fish proteins for the first time in this study. To produce mild-tasting and -smelling fish protein products, the lipid oxidation and degradation of raw material should be assessed carefully. Lipid oxidation could be prevented, e.g., with the addition of antioxidants . To limit the degradation of raw materials, appropriate storage conditions and quick processing after capture is essential. Additionally, the storage stability of final products throughout the shelf-life should be assessed carefully. 4. Conclusions The processing method has been shown to fundamentally affect the functional properties of fish proteins and thus, the usability in food solutions. In this study, raw material had some effect on the proximate composition of the proteins, but not on the chemical or sensory properties. Generally, protein hydrolysates had better functional properties compared to concentrates, therefore making them the most potential option for food ingredients. However, concentrates had a better amino acid composition, higher amount of lipids, and better fatty acid quality. This leads to better nutritional value in fish concentrates, if used as food ingredients. However, the sensory properties, mainly fishiness and bitterness, are potentially limiting the food-grade fish protein markets. These challenges are likely caused by lipid oxidation and raw material degradation, and limiting those with, e.g., adding antioxidants during processing or low oxygen processing conditions would likely lead to milder tasting and smelling product more suitable for human consumption. Acknowledgments The authors would like to thank Riitta Pasanen, Leila Kostamo, Minna Aalto, Satu Orling-Vigren, Auli Lehtonen, and Marja Kallioinen for their technical assistance in conducting the experimental work, and Raija Lantto for her valuable comments on the manuscript. Heidi Leskinen is thanked for her guidance on fatty acid analyses. Supplementary Materials The following supporting information can be downloaded at: Table S1: Sensory attributes, their descriptions and reference samples; Figure S1: Spider plot of the mean values of the sensory evaluation; Table S2: The detection frequencies (DF) and odor descriptions of compounds detected with GC-MS-O (VF-Wax column) from commercial fish proteins; Figure S2: Partial least regression correlation loading of odor-active compounds and odor and flavor sensory properties of commercial fish proteins. Click here for additional data file. Author Contributions Conceptualization, K.H., J.H., T.K. and H.A.; methodology, H.A.; validation, M.P.; formal analysis, M.P., J.H., T.K., S.M., S.K., E.A. and H.A.; investigation, M.P. and S.K.; resources, M.P. and K.H.; writing--original draft preparation, M.P.; writing--review and editing, K.H., J.H., T.K., S.M., S.K., E.A., K.V. and H.A; visualization, M.P., T.K. and E.A.; supervision, K.H., K.V. and H.A.; project administration, K.H.; funding acquisition, K.H. and S.M. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the fact that the materials were provided by commercial operators. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The reducing SDS-PAGE image of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen. To lines 1-6 was pipetted 20 mL of solution and to lines 7-12 25 mL of solution. Line numbers represent samples: 1 and 7 = CONC3, 2 and 8 = CONC1, 3 and 9 = CONC2, 4 and 10 = HYDR1, 5 and 11 = HYDR2, 6 and 12 = COLL1. Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. Standard is abbreviated as std. Figure 2 Size exclusion chromatograms (SEC) of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen. (A) CONC1, (B) CONC2, (C) CONC3, (D) HYDR1, (E) HYDR2, and (F) COLL1. Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. Figure 3 Proportion (%) of molecular weight (MW) distributions of commercial fish protein concentrates, hydrolysates, and hydrolyzed fish protein. Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. Different letters within the same molecular weight grade indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Figure 4 Peroxide values (meq/kg protein powder, "as is") in three commercial fish protein concentrate (CONC1-3) and a hydrolysate (HYDR1). Different letters indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Figure 5 Malondialdehyde (MDA) contents (nmol MDA/g powder "as is") of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen. Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. Different letters indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Figure 6 Functional properties of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen. (A) Protein solubility, (B) water holding capacity (WHC), (C) fat binding capacity (FBC), (D) foaming capacity (FC), and (E) foaming stability (FS). In figure (E), the results are compared by timepoints between the samples. Different letters indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. Figure 7 The Partial Least Squares (PLS) correlation loading of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen, where the free amino acids, lipid oxidation, peptide profile, odor-active volatile compounds identified with GC-MS-O, color, solubility, water holding capacity (WHC), fat binding capacity (FBC), and foaming capacity (FC) are the predictors (blue) of sensory properties (black). Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. foods-12-00966-t001_Table 1 Table 1 The processing methods and raw materials of the commercial fish protein samples. Sample Raw Material Part Used CONC1 Cod (Gadus morhua), Saithe (Pollachius virens), and Haddock (Melanogrammus aeglefinus) Fish filleting by-products CONC2 Cod (Gadus morhua) Fish filleting by-products CONC3 Cod (Gadus morhua) Cod backbones HYDR1 Blue whiting (Micromesistius poutassou) Whole fish HYDR2 Salmon (Salmo salar) Fish filleting by-products COLL1 NA NA NA = Information not available. foods-12-00966-t002_Table 2 Table 2 Proximate composition of the commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen with mean and standard deviation of three replicate measurements. Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Sample Protein (%) Total Lipids (%) Moisture (%) Ash (%) CONC1 63.0 +- 0.00 a 8.5 +- 0.07 a 4.2 +- 0.11 a 21.4 +- 0.04 a CONC2 70.8 +- 0.00 b 4.8 +- 0.08 b 4.0 +- 0.21 b 22.5 +- 0.03 b CONC3 69.3 +- 0.00 c 4.1 +- 0.04 c 5.3 +- 0.81 ac 19.1 +- 0.02 c HYDR1 82.9 +- 0.00 d 0.4 +- 0.01 d 4.1 +- 0.03 ac 9.8 +- 0.40 d HYDR2 93.4 +- 0.00 e 0.1 +- 0.01 e 3.0 +- 0.01 d 2.7 +- 0.01 e COLL1 99.3 +- 0.00 f 0.1 +- 0.02 e 7.8 +- 0.01 d 0.2 +- 0.01 f Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. foods-12-00966-t003_Table 3 Table 3 Total amino acids (mg/g protein) in commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen with mean and standard deviation of three replicate measurements. The amounts are compared to the daily requirement (mg/kg) . Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Essential CONC1 CONC2 CONC3 HYDR1 HYDR2 COLL1 His 23.8 +- 3.33 a 23.4 +- 3.28 a 19.6 +- 2.75 a 18.7 +- 2.62 a 23 +- 3.22 a 7.6 +- 1.06 b 15 Ile 47.6 +- 6.67 a 46.5 +- 6.51 a 38.1 +- 5.34 ab 40.8 +- 5.70 ab 32.5 +- 4.54 b 16.4 +- 2.30 c 30 Leu 83.0 +- 11.62 a 81.8 +- 11.46 a 69.6 +- 9.74 a 76.2 +- 10.67 a 57.3 +- 8.02 a 32.6 +- 4.57 b 59 Lys 83.8 +- 11.73 a 87.3 +- 12.23 a 75.1 +- 10.52 a 85.9 +- 12.02 a 81.2 +- 11.36 a 50.5 +- 7.06 b 45 Met 32.4 +- 4.54 a 32.8 +- 4.59 a 28.5 +- 4.00 ab 26 +- 3.64 a 26.8 +- 3.75 a 14.6 +- 2.04 b 22 1 Phe 22.8 +- 6.22 a 43.3 +- 6.06 a 36.6 +- 5.12 a 37.9 +- 5.31 a 31.7 +- 4.43 ab 23.0 +- 3.21 b 38 2 Thr 50.5 +- 7.06 a 47.9 +- 6.71 a 41.2 +- 5.77 ab 41.7 +- 5.84 ab 43.8 +- 6.14 ab 30.9 +- 4.33 b 23 Trp 12 +- 1.21 a 11.7 +- 1.17 a 9.2 +- 0.92 b 7.6 +- 0.76 b 5 +- 0.49 c <0.01 d 6 Val 28.5 +- 7.67 a 53.4 +- 7.48 a 44.9 +- 6.28 a 47.3 +- 6.62 a 41.8 +- 5.85 ab 28.7 +- 4.02 b 39 Non-Essential Ala 67.1 +- 9.40 a 67.6 +- 9.48 a 65.8 +- 9.21 a 68.7 +- 13.58 a 86.1 +- 12.06 a 121.9 +- 17.06 b Arg 71.4 +- 10.00 72.6 +- 10.16 67.6 +- 9.47 64.8 +- 9.07 79.4 +- 11.11 94.1 +- 13.17 Asp 109.2 +- 15.29 a 107.8 +- 15.10 a 95.4 +- 13.36 ab 102.7 +- 14.38 a 106 +- 14.84 a 65.6 +- 9.17 b Glu 146 +- 20.44 154.5 +- 21.62 141.2 +- 19.77 154.3 +- 21.61 161.7 +- 22.64 110.8 +- 15.5 Gly 79.5 +- 11.13 a 77.7 +- 10.87 a 94.9 +- 13.29 a 70.9 +- 9.92 a 161.7 +- 22.64 b 287 +- 40.1 c Hyp 9.9 +- 1.97 a 10.4 +- 2.09 a 18.6 +- 3.73 a 11.6 +- 2.31 a 43.9 +- 8.78 b 96.8 +- 19.36 c Orn <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 Pro 50.0 +- 7.00 ab 49.2 +- 6.89 ab 50.8 +- 7.12 ab 41.8 +- 5.86 a 73.3 +- 10.26 b 131.9 +- 18.47 c Ser 53.3 +- 7.46 50.9 +- 7.12 49.7 +- 6.96 43.8 +- 6.12 51.1 +- 7.15 40.2 +- 4.43 Tyr 36.2 +- 5.06 a 36.1 +- 5.05 a 29.4 +- 4.11 ab 29.4 +- 4.12 ab 22 +- 3.07 b 3.5 +- 0.49 c Cys 11.1 +- 1.56 a 10.3 +- 1.44 a 9.7 +- 1.26 a 9.2 +- 1.29 a 5.8 +- 0.80 b 0.3 +- 0.04 c Essential:non-essential 0.61 +- 0.01 a 0.67 +- 0.00 a 0.58 +- 0.00 a 0.64 +- 0.00 a 0.43 +- 0.00 a 0.21 +- 0.00 b Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1; 1 Methionine + cysteine (16 + 6); 2 Phenylalanine + tyrosine. foods-12-00966-t004_Table 4 Table 4 Free amino acids (mg/g) in commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen with mean and standard deviation of three replicate measurements. Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Essential CONC1 CONC2 CONC3 HYDR1 HYDR2 COLL1 His <0.18 <0.18 <0.18 2.12 +- 0.34 a 0.63 +- 0.1 b <0.18 Ile <0.18 <0.18 <0.18 7.4 +- 0.74 a 0.61 +- 0.06 b <0.18 Leu 0.19 +- 0.02 a <0.08 0.1 +- 0.01 a 26 +- 2.08 b 2.46 +- 0.2 c <0.08 Lys 0.3 +- 0.05 a 0.13 +- 0.02 a 0.14 +- 0.02 a 9.31 +- 1.49 b 1.15 +- 0.18 a <0.07 Met <0.08 <0.08 <0.08 7.86 +- 0.63 a 0.59 +- 0.05 b <0.08 Phe <0.16 <0.16 <0.16 12.7 +- 1.78 a 0.77 +- 0.11 b <0.16 Thr <0.03 0.07 +- 0.01 a <0.03 5.51 +- 0.55 b 0.5 +- 0.05 a <0.03 Trp <0.1 <0.1 <0.1 1.94 +- 0.19 a 0.16 +- 0.02 b <0.1 Val 0.1 +- 0.01 a <0.08 0.09 +- 0.01 a 10.5 +- 1.26 b 1.12 +- 0.13 a <0.08 Non-Essential Ala 0.37 +- 0.03 a 0.24 +- 0.02 a 0.47 +- 0.04 a 9.43 +- 0.75 b 1.46 +- 0.12 c 0.14 +- 0.01 a Arg 0.25 +- 0.03 a 0.08 +- 0.01 a 0.05 +- 0.01 a 14.1 +- 1.41 b 1.09 +- 0.11 a < 0.05 Asp <0.09 <0.09 <0.09 2.47 +- 0.22 a 0.79 +- 0.07 b 0.2 +- 0.02 c Glu <0.11 <0.11 <0.11 6.26 +- 0.44 a 2.14 +- 0.15 b <0.11 Gly 0.31 +- 0.03 ab 0.18 +- 0.02 a 0.3 +- 0.03 ab 1.74 +- 0.16 c 0.66 +- 0.06 d 0.43 +- 0.04 b Tau 3.05 +- 0.31 a 1.71 +- 0.17 b 4.41 +- 0.44 c 5.9 +- 0.59 d 3.02 +- 0.3 a <0.09 Orn <0.1 <0.1 <0.1 <0.1 0.18 +- 0.02 <0.1 Pro <0.1 0.14 +- 0.01 <0.1 <0.1 <0.1 <0.1 Ser <0.08 <0.08 <0.08 4.52 +- 0.5 a 0.68 +- 0.07 b <0.08 Tyr <0.12 <0.12 <0.12 7.03 +- 1.27 a 0.6 +- 0.11 b <0.12 Cys <0.07 0.11 +- 0.02 a <0.07 5.71 +- 0.91 b 1.74 +- 0.28 c <0.07 Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. foods-12-00966-t005_Table 5 Table 5 Fatty acid composition (percent of total fatty acids) of the commercial fish protein concentrates (CONC1-3) with mean and standard deviation of two replicate measurements. There were no statistically significant differences between the samples with Kruskal-Wallis one-way analysis of variance. Fatty Acid CONC1 CONC2 CONC3 C14:0 3.1 +- 0.0 2.6 +- 0.0 1.5 +- 0.0 C16:0 15.4 +- 0.1 17.8 +- 0.0 17.8 +- 0.1 C18:0 3.5 +- 0.0 3.5 +- 0.0 4.2 +- 0.0 Total SFA 23.6 +- 0.2 25.2 +- 0.0 24.7 +- 0.1 C16:1 n-7 6.0 +- 0.0 3.8 +- 0.0 2.2 +- 0.0 C18:1 n-9 13.4 +- 0.1 11.5 +- 0.0 11.4 +- 0.0 C18:1 n-7 5.4 +- 0.0 4.1 +- 0.0 3.6 +- 0.0 C20:1 n-9 5.9 +- 0.0 6.1 +- 0.0 3.9 +- 0.0 C22:1 n-11 2.8 +- 0.0 3.1 +- 0.0 1.2 +- 0.0 C24:1 n-9 0.9 +- 0.0 1.2 +- 0.0 1.5 +- 0.0 Total MUFA 41.5 +- 0.1 35.8 +- 0.1 29.4 +- 0.2 C18:3 n-3 0.4 +- 0.0 0.4 +- 0.0 0.3 +- 0.0 C18:4 n-3 1.8 +- 0.0 1.0 +- 0.0 0.5 +- 0.0 C20:5 n-3 11.4 +- 0.1 11.4 +- 0.0 12.6 +- 0.0 C22:5 n-3 1.1 +- 0.0 1.0 +- 0.0 1.0 +- 0.0 C22:6 n-3 13.0 +- 0.1 19.6 +- 0.0 25.8 +- 0.2 Total n-3 29.2 +- 0.3 34.2 +- 0.1 40.9 +- 0.3 C18:2 n-6 1.2 +- 0.0 1.2 +- 0.0 0.9 +- 0.0 C20:4 n-6 1.6 +- 0.0 1.7 +- 0.0 2.3 +- 0.0 Total n-6 3.7 +- 0.0 3.6 +- 0.0 3.8 +- 0.0 Total PUFA 34.5 +- 0.3 38.6 +- 0.1 45.3 +- 0.2 SFA = saturated fatty acids, MUFA = monounsaturated fatty acids, PUFA = polyunsaturated fatty acids. foods-12-00966-t006_Table 6 Table 6 The color measurement of the commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen with mean and standard deviation of five replicate measurements. Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). L* = lightness, a* = red-green, b* = yellow-blue. Sample L* a* b* Whiteness CONC1 68.4 b +- 0.44 3.3 b +- 0.06 19.9 b +- 0.19 62.5 b +- 0.30 CONC2 73.8 c +- 0.26 2.3 c +- 0.07 17.4 c +- 0.27 68.4 c +- 0.28 CONC3 84.6 a +- 0.15 0.1 a +- 0.03 13.3 a +- 0.05 79.6 a +- 0.12 HYDR1 80.2 d +- 0.10 2.7 d +- 0.26 27.0 d +- 0.23 66.4 d +- 0.17 HYDR2 87.5 e +- 0.21 1.7 e +- 0.04 21.1 e +- 0.11 75.4 e +- 0.14 COLL1 93.2 f +- 0.18 -1.8 f +- 0.04 13 a +- 0.14 85.2 f +- 0.21 Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. foods-12-00966-t007_Table 7 Table 7 The sensory attributes of commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen with mean and standard deviation of 27 (3 x 9) evaluations. Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). Attribute HYDR1 HYDR2 COLL1 CONC1 CONC2 CONC3 Sedimentation 0.9 +- 1.1 a 0.2 +- 0.4 a 0.2 +- 0.4 a 8.0 +- 0.8 b 7.9 +- 0.9 b 7.3 +- 1.0 b Color saturation 9.7 +- 0.6 a 8.4 +- 1.0 a 4.8 +- 0.4 b 4.9 +- 1.8 b 5.5 +- 1.9 b 5.5 +- 1.2 b Cloudiness 1.2 +- 1.1 a 0.5 +- 0.7 a 0.4 +- 0.6 a 9.3 +- 1.0 b 9.2 +- 1.1 b 8.6 +- 1.6 b Particle distinctiveness 0.1 +- 0.2 a 0.1 +- 0.2 a 0.1 +- 0.1 a 4.8 +- 2.0 b 6.0 +- 2.9 b 4.7 +- 2.8 b Oily mouthfeel 1.8 +- 2.1 a 0.5 +- 0.6 a 0.4 +- 0.8 a 1.9 +- 2.4 a 1.8 +- 1.9 a 1.7 +- 2.0 a Taste intensity 5.0 +- 2.3 a 4.55 +- 2.4 a 1.0 +- 0.9 b 4.5 +- 2.3 a 4.7 +- 2.2 a 4.7 +- 2.4 a Sea/seaweed flavor 0.7 +- 0.6 a 0.5 +- 0.6 a 0.2 +- 0.3 a 2.7 +- 1.9 b 1.7 +- 1.1 c 1.7 +- 1.3 c Metallic flavor 2.1 +- 2.7 ab 3.1 +- 2.6 a 1.1 +- 1.7 b 1.2 +- 1.7 b 1.0 +- 1.5 b 0.8 +- 1.0 b Fishy flavor 3.7 +- 1.9 b 2.0 +- 1.9 c 0.4 +- 0.4 d 4.7 +- 1.9 ab 4.8 +- 2.1 ab 5.3 +-1.8 a Bitterness 2.7 +- 2.3 a 3.9 +- 2.0 a 0.8 +- 1.2 b 1.1 +- 1.4 b 1.0 +- 1.4 b 1.0 +- 1.4 b Umami flavor 3.3 +- 2.5 a 2.7 +- 2.4 a 0.4 +- 0.4 b 1.1 +- 1.2 b 1.2 +- 1.3 b 1.2 +- 1.4 b Odor intensity 5.5 +- 2.1 a 6.2 +- 1.9 a 2.7 +- 2.4 b 6.1 +- 1.6 a 6.3 +- 1.5 a 6.0 +- 1.8 a Fishy odor 4.1 +- 2.5 bc 2.9 +- 2.9 cd 1.3 +- 2.0 d 6.7 +- 1.5 a 6.7 +- 1.3 a 6.2 +- 2.1 a Brothy odor 4.9 +- 2.6 b 7.4 +- 1.9 a 1.3 +- 1.5 c 1.9 +- 2.0 c 1.7 +- 2.3 c 2.3 +- 2.3 c Sea/seaweed odor 1.1 +- 1.0 bc 0.6 +- 0.9 c 1.1 +- 1.1 bc 2.0 +- 1.6 ab 2.2 +- 1.4 a 2.1 +- 1.6 a Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, hydrolyzed fish collagen = COLL1. foods-12-00966-t008_Table 8 Table 8 Relative concentration (mean +- standard deviation) of different odor-active volatile compounds identified with GC-MS-O and previous literature from commercial fish protein concentrates, hydrolysates, and hydrolyzed collagen. The RI was determined with polar WF-Wax column. The identification is marked with RI+, if the compound could be identified also with non-polar DB-5 column. Different letters within the same row indicate a statistically significant difference with ANOVA post hoc pair comparison (p < 0.05). # Volatile Compound RI Identification Odor Description Relative Concentration (RC) 1 or Detection Frequency (DF) 2 CONC1 CONC2 CONC3 HYDR1 HYDR2 COLL1 1 Trimethylamine <600 RI+, MS, O Fishy, fatty 146 +- 16 a 100 +- 57 a 160 +- 79 a 350 +- 75 b 57 +- 15 a ND 2 Methanethiol 700 RI, MS, O Cabbage, musty ND 3 1 +- 1 a 3 +- 1 a ND 5 +- 1 b 3 +- 1 a 3 Heptane 701 RI+, MS - 4 9 +- 6 a 14 +- 2 a 2 +- 0 b ND ND ND 4 Propanal 801 RI, MS - ND ND 27 +- 4 a 3 +- 0 b ND ND 5 3-Methylbutanal 929 RI+, MS, O Sour bread 137 +- 9 a 107 +- 27 a 36 +- 8 b 127 +- 26 a 34 +- 4 b 3 +- 1 b 6 2-Ethylfuran 964 RI, MS - 52 +- 2 ac 50 +- 5 ac 12 +- 1 a 181 +- 44 b 72 +- 9 c 10 +- 1 a 7 2,3-Butanedione 986 RI+, MS, O Sweet, butter, toffee 13 +- 1 a 8 +- 4 ac 10 +- 2 a 4 +- 1 bc 1 +- 0 b ND 8 Unknown 1 1026 Glue, medicinal NA 5 NA DF 75 6 DF 0 DF 0 NA 9 2,3-Pentanedione 1073 RI+, MS Unclear 30 +- 7 a 21 +- 4 ab 15 +- 7 b ND ND ND 10 Dimethyl disulfide 1103 RI+, MS - ND ND ND 51 +- 12 a ND 71 +- 7 b 11 Hexanal 1103 RI, MS, O Grass 227 +- 101 a 113 +- 33 bc 39 +- 5 cd ND 16 +- 3 d ND 12 Unknown 2 1115 Coffee, solvent NA NA DF 0 DF 75 DF 50 NA 13 1-Penten-3-ol 1170 RI+, MS - 210 +- 10 a 233 +- 37 a 143 +- 26 b ND ND ND 14 2-Heptanone 1202 RI+, MS, O Medicinal, burnt 31 +- 2 a 39 +- 11 a 4 +- 1 b 21 +- 6 a 3 +- 1 b 1 +- 0 b 15 Heptanal 1206 RI+, MS - 121 +- 11 a 94 +- 26 a 11 +- 5 b 14 +- 6 b 6 +- 1 b 2 +- 1 b 16 2-Pentylfuran 1247 RI, MS - ND 6 +- 5 a ND 13 +- 5 ab 20 +- 4 b 5 +- 1 a 17 (Z)-4-Heptenal 1263 RI, MS, O Fishy, pungent 110 +- 8 a 112 +- 15 a 20 +- 4 b 10 +- 3 bc 1 +- 0 c ND 18 2-Octanone 1307 RI+, MS, O Metallic 24 +- 4 a 30 +- 4 a 13 +- 4 b 6 +- 2 bc 1 +- 1 c ND 19 Octanal 1310 RI+, MS, O Citrus, metallic 79 +- 11 a 64 +- 23 a 6 +- 4 b 12 +- 3 b 6 +- 1 b 8 +- 1 b 20 1-Octen-3-one 1324 RI, O Mushroom NA NA DF 100 DF 75 DF 0 NA 21 Hydroxyacetone 1337 RI, MS, O Mushroom, meat broth ND ND ND ND 4 +- 1 NA 22 Unknown 3 1358 Dog food, leather NA NA DF 0 DF 75 DF 0 NA 23 2-Acetyl-1-pyrroline 1375 RI+, O Popcorn, Basmati rice NA NA DF 100 DF 100 DF 50 NA 24 Unknown 4 1394 Floral, raspberry, green NA NA DF 0 DF 0 DF 100 NA 25 Unknown 5 1396 Metallic, iron NA NA DF 57 DF 0 DF 0 NA 26 Nonanal 1415 RI+, MS - 65 +- 8 a 58 +- 14 a 12 +- 5 b 41 +- 14 c 44 +- 9 ac 49 +- 4 ac 27 2,3,5-Trimethylpyrazine 1435 RI+, MS, O Musty 31 +- 3 a 22 +- 11 a 10 +- 2 b 21 +- 7 * 1 +- 1 b ND 28 Dimethyl trisulfide 1436 RI+, MS - ND ND ND ND 2 +- 0 a 29 3-Isopropyl-2-metoxypyrazine 1438 RI, O Soy sauce, green NA NA 22 +- 7 b ND ND ND 30 Unknown 6 1446 Ink, musty, burnt NA NA DF 0 DF 0 DF 75 NA 31 1-Octen-3-ol 1449 RI, MS - 77 +- 5 a 89 +- 13 a 22 +- 7 b ND ND ND 32 Acetic acid 1467 RI+, MS - ND ND ND 347 +- 150 ND ND 33 Methional 1492 RI+, O Boiled potato NA NA DF 100 DF 75 DF 75 NA 34 2-Decanone 1514 RI+, MS - 22 +- 2 ac 34 +- 11 a 2 +- 1 b 11 +- 3 bc 1 +- 0 b ND 35 2,4-Heptadienal 1531 RI, MS - 4 +- 2 a 2 +- 2 a ND ND ND ND 36 Unknown 7 1543 Burnt, black currant NA NA DF 0 DF 0 DF 100 NA 37 1-Octanol 1559 RI+, MS, O Sour, pungent 17 +- 1 a 19 +- 3 a 5 +- 1 b ND 3 +- 1 b ND 38 Unknown 8 1595 Musty, green, pungent NA NA DF 0 DF 75 DF 0 NA 39 2-Undecanone 1621 RI+, MS, O Pungent 31 +- 4 a 50 +- 13 b 6 +- 2 c ND ND ND 40 Unknown 9 1649 Berry NA NA DF 50 DF 50 NA NA 41 2-Methylbutanoic acid 1687 RI, MS, O Musty, sulfuric ND 0.0 ND 33 +- 20 a 6 +- 3 b ND 42 2-Dodecanone 1727 RI+, MS, O Meat broth ND 6 +- 6 a ND 1 +- 1 a ND ND 43 Unknown 10 1757 Liquorice, cloying NA NA DF 75 DF 75 DF 0 NA 44 Unknown 11 2074 Sweet, cotton candy NA NA DF 50 DF 75 DF 100 NA 45 Unknown 12 2084 Rhubarb, acidic NA NA DF 0 DF 0 DF 50 NA 46 Unknown 13 >2186 Solvent, ink NA NA DF 50 DF 0 DF 0 NA Fish protein concentrates = CONC1-3, fish protein hydrolysates = HYDR1-2, Hydrolyzed fish collagen = COLL1. * Same peak in chromatogram contained both 2,3,5-trimethylpyrazine and dimethyl trisulfide. 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PMC10000494 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051042 foods-12-01042 Article Mesoporous Activated Biochar from Crab Shell with Enhanced Adsorption Performance for Tetracycline Sun Jiaxing Conceptualization Software Validation Data curation Writing - original draft Visualization 1 Ji Lili Conceptualization Methodology Writing - review & editing 1* Han Xiao Conceptualization Methodology Validation Formal analysis Writing - original draft Visualization 2 Wu Zhaodi Software 2 Cai Lu Formal analysis Investigation Resources 3 Guo Jian Investigation Resources 2 Wang Yaning Resources 1 Ozogul Yesim Academic Editor 1 National Marine Facilities Aquaculture Engineering Technology Research Center, Zhejiang Ocean University, Zhoushan 316022, China 2 College of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316022, China 3 Institute of Ocean Higher Education, Zhejiang Ocean University, Zhoushan 316022, China * Correspondence: [email protected] 01 3 2023 3 2023 12 5 104204 1 2023 11 2 2023 21 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). In this study, three mesoporous-activated crab shell biochars were prepared by carbonation and chemical activation with KOH (K-CSB), H3PO4 (P-CSB), and KMnO4 (M-CSB) to evaluate their tetracycline (TC) adsorption capacities. Characterization by SEM and a porosity analysis revealed that the K-CSB, P-CSB, and M-CSB possessed a puffy, mesoporous structure, with K-CSB exhibiting a larger specific surface area (1738 m2/g). FT-IR analysis revealed that abundant, surface ox-containing functional groups possessed by K-CSB, P-CSB, and M-CSB, such as -OH, C-O, and C=O, enhanced adsorption for TC, thereby enhancing their adsorption efficiency for TC. The maximum TC adsorption capacities of the K-CSB, P-CSB, and M-CSB were 380.92, 331.53, and 281.38 mg/g, respectively. The adsorption isotherms and kinetics data of the three TC adsorbents fit the Langmuir and pseudo-second-order model. The adsorption mechanism involved aperture filling, hydrogen bonding, electrostatic action, p-p EDA action, and complexation. As a low-cost and highly effective adsorbent for antibiotic wastewater treatment, activated crab shell biochar has enormous application potential. crab shell activated biochar tetracycline adsorption mechanism the Fundamental Research Funds for Zhejiang Provincial Universities and Research InstitutesNo. 2021J004 This study was supported by the Fundamental Research Funds for Zhejiang Provincial Universities and Research Institutes (No. 2021J004). pmc1. Introduction In spite of being utilized to treat biological bacterial infections , antibiotics can also be used as biological additives and growth promoters. Tetracycline (TC) is widely used as a broad-spectrum antibiotic due to its high quality, low cost, high antibacterial activity, and limited side effects . Nevertheless, humans, livestock, and poultry are unable to absorb TC antibiotics completely, resulting in 70-90% of the antibiotics being excreted in feces and urine, causing environmental pollution . In addition, the fact that TC is highly water soluble and chemically stable makes it easy for it to accumulate in the water environment , threatening human health and the environment's ecology. Apart from inducing the transfer of bacterial resistance genes into the human body, TCs can enter the body and induce bone marrow suppression, hemolytic anemia, visual neuritis, or peripheral neuritis . Tetracycline is one of the most common antibiotic contaminants in the water environment. It is used on a large scale in the aquaculture and medical industries. Concentrations in shallow groundwater have been measured at 184.2 ng/L . The content of TC in wastewater discharged from pharmaceutical factories and aquaculture farms is higher than the content in domestic wastewater . Consequently, eliminating residual TCs from the environment has become a research focus. In recent years, numerous techniques for removing TCs from aqueous solutions have been developed. These include the microbial method , chemical oxidation , photocatalytic oxidation , physical separation , and adsorption . Among these techniques, the application of microbial methods is limited due to the difficulty of biodegrading stable TC . Chemical oxidation is an expensive and energy-intensive process. Physical separation is inefficient and prohibitively expensive. The adsorption technique has been extensively studied due to its high efficiency, low cost, and simple operation . The type of adsorbent determines the adsorption efficiency. Various adsorbents have been developed for the adsorptive removal of TCs, such as biochar , mineral materials, nanomaterials , and metal skeletal organics . Biochar, a carbon-rich byproduct produced by pyrolysis under anaerobic or limited oxygen conditions, possesses a large surface area, a rich pore structure, and various active groups . Wang et. al compared the effects of rice straw biochar and pig manure biochar on the removal of tetracycline from aqueous solutions. Their results indicated that the rice straw biochar, which was prepared at 600 degC, had a higher tetracycline adsorption capacity (14.185 mg/g) . Biochar could also efficiently remove food and plant residues from aqueous solutions, demonstrating a maximum adsorption capacity of up to 15.2508 mg/g . Conventional pyrolysis-produced biochars are limited in their specific surface area, pore volume, and functional groups, resulting in their relatively low actual TC removal in aqueous solutions. Recently, an engineered biochar, modified to remove contaminants, has been proposed . It is defined as a carbon-rich solid manufactured from biomass using pyrolysis technology in combination with modification techniques such as chemical, physical, or biological modification. This results in a higher specific surface area and adsorption capacity than conventional biochar. It also results in an increase in the removal of contaminants from wastewater . Among the modification techniques, chemical modification typically employs acidic or basic chemicals to activate the biochar, increasing the availability of functional groups, cation exchange capacity, and surface area . For instance, a lignin biochar activated by H3PO4 exhibited a superior adsorption performance with a maximum adsorption capacity of 475.48 mg/g for TC . The biochar derived from aerobic granular sludge was modified by ZnCl2 (Zn-BC) to remove TC from an aqueous solution; its maximum TC adsorption performance was 93.44 mg/g . Therefore, it is worthwhile to produce a high-performance engineered biochar as an adsorbent for further research. The purpose of this study was to prepare a new crab shell biochar adsorbent through carbonization and chemical activation using KOH, H3PO4, and KMnO4. Its adsorption properties were characterized by FTIR, XRD, SEM, and BET. The mechanism of adsorption was analyzed accordingly. This study provides a new and promising research proposal for the treatment of antibiotic-contaminated wastewater using crab shell biosorbents. 2. Materials and Methods 2.1. Materials and Chemical Reagents The crab shell used in the experiment was obtained from the Zhoushan seafood market, washed with tap water multiple times, dried overnight at 70 degC, and crushed through a 100 mesh sieve (ASTM standard). KOH, H3PO4, KMnO4 were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China), while TC hydrochloride (purity > 96%) was purchased from Sinopharm Chemical Reagent Co., Ltd. This experiment utilized only analytical-grade chemical reagents. 2.2. Preparation of Crab Shell Biochar The pretreated crab shell was placed in a crucible and pyrolyzed in a tube furnace. Pre-pyrolysis, N2 was introduced into the tube furnace for 30 min to ensure an inert atmosphere. The pretreated crab shell was then calcined at 500, 600, 700, 800, and 900 degC for 2 h with a heating rate of 10 degC/min and an N2 flow rate of 0.25 L/min before being cooled to room temperature. The prepared crab shell biochar varieties are denoted as 500-CSB, 600-CSB, 700-CSB, 800-CSB, and 900-CSB. 2.3. Preparation of Modified Crab Shell Biochar Specifically, 800-CSB was modified with KOH, H3PO4, and KMnO4 to produce an engineered crab shell biochar. The specific procedures are as follows. KOH modification: The 800-CSB was thoroughly mixed with solid KOH (CSB/KOH (w/w) = 1:3). The the mixture was calcined at 800 degC for 2 h at a heating rate of 10 degC/min and an N2 flow rate of 0.25 L/min. After bringing the sample to room temperature, it was washed with deionized water until the pH was neutral, dried in an oven at 85 degC for 12 h, and sieved through a 100 mesh screen (ASTM standard). K-CSB stands for KOH-modified crab shell biochar. H3PO4 modification: An amount of 5 g 800-CSB was immersed in 50 mL of a 20% H3PO4 solution for 24 h under magnetic agitation. The resulting solution was washed with deionized water until the pH was neutral, dried in an oven at 85 degC for 12 h, and sieved through a 100 mesh screen (ASTM standard). The biochar derived from crab shells modified with H3PO4 is designated as P-CSB. KMnO4 modification: An amount of 5 g 800-CSB was immersed in 50 mL 100 g/L KMnO4 solution for 24 h under magnetic agitation. The resulting solution was washed with deionized water until the pH was neutral, dried in an oven at 85 degC for 12 h, and sieved through a 100 mesh screen (ASTM standard). KMnO4, also known as modified crab shell biochar, was called M-CSB. 2.4. Characterization of Crab Shell Biochar A scanning electron microscope (SU8010, Hitachi, Tokyo, Japan) was used to examine the morphology and microstructure of the as-prepared samples. The N2 adsorption-desorption isotherm was determined by a static volumetric adsorption analyzer (Micromeritics ASAP 2460, Norcross, GA, Micromeritics USA) at 573K. The specific surface area and pore size distribution of the prepared samples were evaluated based on Brunauer-Emmett-Teller (BET) and Barret-Joyner-Halenda (BJH). The phase composition was analyzed by X-ray diffraction (XRD, D8 Advance, Bruker, Ettlingen, Germany) in the 10-80deg angle range, and the functional groups were analyzed by Fourier transform infrared spectroscopy (FTIR, Nicolet 6700, Thermo Fisher Scientific, Waltham, MA, USA). 2.5. Batch Adsorption Experiments Using modified crab shell biochars, the effects of as-prepared adsorbent dose, initial pH, TC concentration, and adsorption time on the TC adsorption performance were investigated. In the following experiments, the temperature was 25 degC, a 250 mL beaker was selected, and the stirring speed was 500 rpm. The adsorbent (K-CSB, P-CSB, and M-CSB) doses were 0.01, 0.03, 0.05, 0.07, and 0.09 g, and the initial pH values was adjusted to 3.0, 5.0, 7.0, 9.0, and 11.0, respectively, using 0.1 mol/L HCl or 0.1 mol/L NaOH. The TC concentration was within 100-500 mg/L, and the adsorption time was 0-3600 min for the batch adsorption experiments. After adsorption, the reaction system was centrifuged at 3800 r/min for 5 min, the supernatant was collected, and its absorbance value (OD, UV 2600, Shimadzu, Japan) was measured at 360 nm. The TC concentration (C0 and Ce) in the adsorption system was calculated. The adsorption rate (R) and equilibrium adsorption capacity of modified the CSBs for TC (qe) were determined from formulas in Equation (1) and Equation (2), respectively. (1) qe=(C0-Ce)Vm (2) R%=C0-CeC0x100% where qe (mg/g) is the adsorption capacity of modified CSBs for TC at equilibrium, C0 (mg/L) and Ce (mg/L) are the initial and at-equilibrium TC concentrations, V (mL) is the volume of the TC solution, m (g) is the amount of modified crab shell biochar, and R (%) represents the TC adsorption rate. 2.6. Adsorption Kinetics and Isothermic Studies In the adsorption kinetic experiments, 0.05 g of as-prepared adsorbent was added to 50 mL of TC solution with concentrations of 100, 200, and 400 mg/L, respectively. The adsorption capacity of the modified crab shell biochars for TC was calculated at different adsorption times, ranging from 0 to 2880 min, at 298 K. The adsorption kinetics of TC on the modified crab shell biochar were analyzed by the pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetics models in Equations (3) and (4) . (3) ln(qe-qt)=lnqe-K1t (4) tqt=1K2qe2+tqe where qe (mg/g) and qt (mg/g) are the adsorption amounts of TC at equilibrium and at time t (min), respectively, and K1 (min-1) and K2 (g/mg min) are the rate constants of PFO and PSO, respectively. In the adsorption isotherm experiments, 0.05 g of as-prepared adsorbent was added to 50 mL of a TC solution with initial concentrations of 50, 100, 150, 200, 300, 400, and 500 mg/L, respectively. After adsorption equilibrium, the adsorption capacity of the modified crab shell biochars for TC was calculated. The adsorption isotherm was analyzed by the Langmuir and Freundlich model in Equations (5) and (6) . (5) ceqe=ceqm+1KLqm (6) lnqe=lnKF+1nlnce where qm (mg/g) is the maximum adsorption capacity of the modified crab shell biochars for TC, qe (mg/g) is the adsorption capacity at equilibrium, Ce (mg/L) represents the TC concentration at equilibrium, KL (L/mg) is the Langmuir adsorption equilibrium constant, KF [(mg/g) (L/mg)1/n] is the Freundlich constant, and 1/n is the adsorption intensity factor or surface heterogeneity. 3. Results and Discussion 3.1. Characterization of Biochar 3.1.1. Porous Structure Table 1 shows the specific surface area, pore volume, and average pore size of the crab shell biochar prepared at different pyrolysis temperatures. Compared with the original crab shells, the specific surface areas of the crab shell biochar after high temperature pyrolysis are significantly higher, indicating that organic matter in the crab shells escapes and forms new pore structures in a high-temperature and oxygen-free environment. Moreover, with the increase in temperature, the specific surface area of the crab shell biochar firstly increases and then decreases, reaching a maximum at 800 degC. The variation trend of pore volume is consistent with that of specific surface area, while the variation trend of the average pore size is the opposite. This is because with the increase in the pyrolysis temperature, the organic matter in the crab shell gradually decomposes and forms new pores, increasing the specific surface area and pore volume. The pore could collapse or be blocked when the pyrolysis temperature is excessive; this affects the specific surface area and pore volume. In conclusion, 800-CSB can be selected as the original material for subsequent modifications according to the size of its specific surface area. Figure 1 depicts the N2 adsorption and desorption isotherms of K-CSB, P-CSB, and M-CSB. According to the IUPAC classification, it could be demonstrated that their N2 adsorption isotherms are all Type IV, with irreversible adsorption and desorption isotherms. It can be seen from the N2 adsorption isotherms of the four samples that there is an obvious and sharp upward trend under low pressure. This is due to the monolayer adsorption of the micropores. It then rises slowly under medium pressure due to the capillary condensation of the adsorption liquid film on the pore wall, until it finally reaches the high-pressure region. In addition, the K-CSB isotherm shows a hysteresis loop at P/P0 > 0.4. This is consistent with the H4 hysteresis ring, indicating the presence of mesopores . Furthermore, the pore size distribution (PSD) of the modified crab shell biochar was analyzed using a non-local density functional theory (NLDFT) model. The PSDs of K-CSB, P-CSB, and M-CSB are primarily in the range of 2-20 nm and are primarily composed of mesopores. The BET method analysis of the N2 adsorption isotherm data reveals that the specific surface area of 800-CSB is 181.79 m2/g. At the same time, the specific surface areas of K-CSB, P-CSB, and M-CSB after activation reached 1095.14, 381.16, and 271.25 m2/g, as shown in Table 2. It was demonstrated that KOH activation could produce materials with a greater specific surface area and pore volume. This is because at high temperatures, KOH is capable of reacting with the biochar C to produce K2CO3, K2O, and H2. K2CO3 and K2O can then react with C to form metallic K and CO, endowing its pore structure as metallic K enters the carbon interlayer and escapes the volatile gas . 3.1.2. Morphological Analysis Figure 2 depicts the microstructures of 800-CSB, K-CSB, P-CSB, and M-CSB at various magnifications. The structure of 800-CSB is relatively compact, with few openings and humps. Following the activation of the crab shell biochar, K-CSB, P-CSB, and M-CSB all display fluffy structures, with K-CSB displaying an irregular, layered structure with an abundance of micropores and mesopores, P-CSB displaying an etched, porous structure with abundant apertures on the surface, and M-CSB displaying a rough surface with numerous cracks. As activators, KOH, H3PO4, and KMnO4 can dehydrate or erode the carbohydrate shell of biochar in the chemical activation process to obtain a higher specific surface area and more surface functional groups . This could provide more active sites for the adsorption of TCs. 3.1.3. XRD Analysis The X-ray diffraction analyses of the as-prepared samples were performed between 10deg and 80deg (2th); Figure 3 depicts the XRD patterns. The 24.8deg and 43.6deg diffraction peaks correspond to amorphous C for the (002) and (100) crystal planes, respectively , and are all indexed by JCPDS card number 81-2030. The very sharp peaks of K-CSB indicate that C changes from amorphous to crystalline during the activation process, and the peaks at 29.4deg, 35.9deg, and 39.4deg correspond to the (010), (110), and (11-3) crystal planes of graphite carbon (PDF#47-1743). Moreover, the diffraction peak at 32.6deg is attributed to the (330) crystal plane of K2CO3 because KOH reacts with the C from the crab shell biochar to produce K2CO3 . In addition, there are two prominent peaks at 12.8deg (101) and 41.2deg (220); these correspond to minerals containing primarily calcium and aluminum. Compared to the XRD pattern of 800-CSB, the patterns of P-CSB and M-CSB are unchanged. However, M-CSB displays a new diffraction peak at 36.1deg, corresponding to the (211) crystal plane of Mn3O4 (JCPDS card No. 80-0382) and indicating that MnOx is loaded onto the surface of the crab shell biochar. 3.1.4. FTIR Analysis Figure 4 depicts the FTIR spectra of the samples as prepared. It can be demonstrated that the FTIR spectra of M-CSB and P-CSB are nearly identical to those of 800-CSB, while the spectra of KCSB vary significantly, which is consistent with the XRD results. The hydroxyl groups (-OH) in alcohol, phenol, and carboxylic acid are responsible for the adsorption peaks at 3440 cm-1 and 3381 cm-1 . Those near 1600 cm-1 correspond to C=O stretching vibrations on the aromatic ring; those at 1096 cm-1 and 1061 cm-1 are due to C-O stretching vibrations on the ester, alcohol, ether, and acid . Those near 600 cm-1 belong to the stretching vibration of the metal oxygen bond in the fingerprint region . In addition, the adsorption peak located at 1388 cm-1 in the K-CSB spectra is the characteristic peak of K2CO3: at 2168 cm-1 it is ascribed to the stretching vibration C=C or CC, while at 881 cm-1 it is due to the bending vibration of C-H on the benzene ring. Furthermore, the adsorption peak at 1096 cm-1 in the P-CSB spectrum is due to the vibration of P=O , while the peak at 548 cm-1 in the M-CSB spectrum is the characteristic peak of MnOX. Thus, chemical activation endows crab shell biochar with an abundance of oxygen-containing functional groups, such as -OH, C-O, and C=O. These act as an p electron donor with an p electron acceptor ( ring or amino functional group) in TC, forming a p-p electron donor-acceptor (p-p EDA) that is beneficial to the adsorption of TC. 3.2. Batch Adsorption Experiments 3.2.1. Effect of Initial TC Concentration The adsorption capacities of K-CSB, P-CSB, and M-CSB to TC with different initial concentrations vary with adsorption time, as depicted in Figure 5a, 5c, and 5d. It can be shown that the adsorption capacities of K-CSB, P-CSB, and M-CSB to TC initially spike and then gradually level off until they reach equilibrium. This is because there are numerous adsorption sites on the surface of the modified crab shell biochar at the beginning of adsorption; when the surface adsorption sites are filled, the TC begins to spread inward. This is a relatively slow process. In addition, it can be observed that as the initial concentration of TC rises, it takes longer to achieve equilibrium in the adsorption process. The effects of different initial TC concentrations on the equilibrium adsorption capacity (qe) and adsorption rate (R) of K-CSB, P-CSB, and M-CSB to TC are depicted in Figure 5b, 5d, and 5f, respectively. With an increase in the initial TC concentration, the equilibrium adsorption capacity (qe) of the K-CSB, P-CSB, and M-CSB to TC increases gradually and then levels off. In contrast, the adsorption rate (R) decreases. When the initial concentration of TC was 100 mg/L in the adsorption experiment, the adsorption rate of the samples was the highest (96.98%, 97.29%, and 91.79%). With the increase in the initial concentration of TC solution, the adsorption rates of the materials began to decline. When the initial concentration of TC was 500 mg/L, the adsorption rates of materials were 74.73%, 66.20%, and 52.93%, respectively. For example, in a 400 mg/L TC solution, the maximum adsorption capacities of K-CSB, P-CSB, and M-CSB to TC are 380.92, 331.53, and 281.38 mg/g, respectively, and the corresponding adsorption rates are 95.23%, 82.89%, and 70.41%, respectively. 3.2.2. Effect of Adsorbent Dose Figure 6 depicts the effect of various adsorbent doses on the equilibrium adsorption capacity (qe) and adsorption rate (R) of K-CSB, P-CSB, and M-CSB to TC. As the adsorbent dose (K-CSB, P-CSB, and M-CSB) increases, the adsorption capacity (qe) demonstrates a general downward trend, initially declining rapidly and then tending to decline gradually. Although the increase in biochar dosage provides more adsorption sites for adsorption and increases the overall adsorption capacity, the total amount of TC adsorbed in the solution is fixed. The adsorption capacity of biochar dispersed to each unit mass will decrease when the dosage increases. As can be seen from Figure 6, when the dosage is 0.01-0.05 g, the adsorption rates of the three samples with respect to TC increase at the adsorption equilibrium with an increase in the dosage. When the dosage was 0.05 g, the adsorption rate reached its highest value and showed a slightly decreasing trend between 0.05-0.09 g. This is because the increase in biochar in a certain range can promote an increase in the adsorption rate. On one hand, the decrease occurs because the excessive dosage leads to a collision between the materials or the agglomeration of blocks, reducing the adsorption sites. On the other hand, the concentration of the TC solution decreases with the process of adsorption, and the interaction force between the TC and the biochar surface gradually decreases , reducing the adsorption rate of the materials. When the material dosage is 0.05 g, the adsorption capacity of the modified crab shell biochars for the TC solution reaches its maximum. Therefore, the adsorption of 1 g/L TC of 50 mL is optimal when the dosage of K-CSB, P-CSB, and M-CSB is 0.05 g. 3.2.3. Effect of Initial pH Figure 7 illustrates the effect of the initial pH on the TC adsorption rate of K-CSB, P-CSB, and M-CSB. It can be demonstrated that the adsorption capacity for TC of modified CSBs initially gradually increases and then decreases as the initial pH increases, primarily due to the charge difference between the TC and the modified carbohydrate shell biochar under different pH conditions. Tetracycline antibiotics all contain a phenolic hydroxyl group, an enol hydroxyl group, and a dimethylamine group. These drugs are amphoteric compounds with three pKa values of 2.8~3.4, 7.2~7.8, and 9.1~9.7, respectively. . At pH < 3.3, TC primarily exists as cations; at pH < 7.7, it exists as amphoteric ions and gradually changes from cations to neutral ions and anions; and at pH > 7.7, it primarily exists as an anion . Additionally, the surface charge of the modified carbohydrate shell biochar varies with the pH. The H+ in the acidic solution protonates the biochar surface, giving it a positive charge; in the alkaline solution, the charge is negative . When pH = 3-7, electrostatic repulsion occurs between the positively charged biochar and the cationic TC. As the pH increases, the TC changes from a cationic state to a neutral ion or anionic state, the repulsion gradually decreases, and the adsorption rate reaches its maximum at pH = 7. When the pH > 7, the repulsive interaction between the negatively charged biochar and the anionic TC gradually increases. Therefore, the optimal pH for TC adsorption by K-CSB, P-CSB, and M-CSB is 7. 3.2.4. Effect of Adsorption Time Figure 8 depicts the effect of adsorption time on the adsorption of TC by K-CSB, P-CSB, and M-CSB. In order to explore the influence of adsorption time on the adsorption effect of TC, an initial concentration of TC of 400 mg/L was used, and the sampling time lasted 3600 min. As the rich pore structure and functional groups on the surface of the as-prepared samples can provide many TC adsorption sites, the adsorption rates of the three TC adsorbents increases dramatically between 0 and 360 min. The optimal adsorption time for the three sorbents is 2880 min. In the 360-2880 min adsorption stage, the adsorption sites become progressively occupied, the TC begins to diffuse to the internal sites and functional groups of the biochar, and the adsorption rate continues to exhibit a slow growth trend. Moreover, between 2880 and 3600 min, the adsorption reaches an equilibrium or decreases slightly, indicating that equilibrium has been reached. 3.3. Adsorption Kinetics Studies The experimental kinetic data for the adsorption kinetics of modified carbohydrate shell biochar for TC at different concentrations are fitted by PFO and PSO models, as shown in Figure 9. The adsorption kinetic parameters are shown in Table 3. It can be observed that the R2 values of the PSO model are greater than those of the PFO model. Therefore, the PSO model best describes the adsorption of TC by K-CSB, P-CSB, and M-CSB. It used to calculate the adsorption amounts of TC at equilibrium in a 400 mg/L TC solution (384.62, 333.33, and 277.77 mg/g), which are in good agreement with experimental data (380.92, 331.53 and 281.38 mg/g). It indicates that the adsorption of TC on K-CSB, P-CSB, and M-CSB is a chemical process involving the exchange of electrons between functional groups. In addition, the fitting adsorption capacity (qe) increases as the initial TC concentration rises due to the intense competition among TC for the surface-active sites of biochar in a solution with a high TC concentration. 3.4. Adsorption Isotherm Studies The Langmuir model and the Freundlich model of TC adsorption on K-CSB, M-CSB, and P-CSB were fitted by adsorption isotherm experiments, as depicted in Figure 10, and the adsorption isotherm model parameters are listed in Table 4. The correlation coefficients R2 of the Langmuir isotherm equation were 0.9852, 0.9933, and 0.9939, respectively, higher than those of Freundlich isotherm equation (R2 = 0.6901, 0.8259, and 0.7208). This indicates that the adsorption of the modified crab shell biochars is more consistent with the Langmuir isothermal model distribution. Therefore, the adsorption of TC on K-CSB, P-CSB, and M-CSB is mainly monolayer adsorption. The Langmuir isotherm equation is commonly used to evaluate the maximum adsorption capacity (qe) of adsorbed materials. Using the Langmuir equation, the equilibrium adsorption amounts of TC in a 400 mg/L TC solution are calculated to be 400.00, 357.14, and 277.78 mg/g, which agree with the experimental data (380.92, 331.53, and 281.38 mg/g). 4. Adsorption Mechanism Experiments on batch adsorption demonstrated that adsorbents prepared from activated crab shell biochar have a superior TC adsorption performance. The adsorption performance of K-CSB is the best, followed by P-CSB and M-CSB. The results of adsorption kinetics and isotherms indicate that the adsorption process of TC by K-CSB, P-CSB, and M-CSB is chemical monolayer adsorption. At the same time, the abundant porous structure of the three adsorbents contributes to the adsorption of TC molecules by aperture filling, i.e., physical adsorption. The above is the mechanism of TC adsorption by three adsorbents. Chemical adsorption involves hydrogen bonding, electrostatic action, p-p EDA action, and complexation . These oxygen-containing functional groups on the biochar surface can protonate with H+ to form positively charged functional groups, which then combine electrostatically with negatively charged TC . Moreover, these oxygen-containing functional groups, such as -OH, C-O, and C=O, can act as p electron donors with p electron acceptors (N-heteroaromatic ring or amino functional group) in TC, forming an p-p electron donor-acceptor. In addition, a high concentration of -OH on the surface may form hydrogen bonds with the amino group . In addition, the XRD analysis results suggest that the mineral ions on the surface of activated crab shell biochar may facilitate the complexation-based adsorption of TC. 5. Conclusions In this study, waste crab shell was used as the original biomass material for preparing activated biochar with KOH, H3PO4, and KMnO4, endowing them with a greater specific surface area, a well-developed porosity, an abundance of oxygen-containing functional groups, and a vast number of bonding sites for TC molecules. In addition, the unique, mesoporous structures of the activated crab shell biochar contribute to its excellent adsorption performance. The maximum TC adsorption capacities of K-CSB, P-CSB, and M-CSB are 380.92, 331.53, and 281.38 mg/g, respectively. The Langmuir and pseudo-second-order model can better describe the adsorption of three kinds of adsorbents on TC, indicating that the adsorption process of K-CSB, P-CSB, and M-CSB on TC is dominated by chemical monolayer adsorption. Furthermore, the adsorption mechanism of TC by the three adsorbents comprises physical and chemical adsorption, i.e., aperture filling, hydrogen bonding, electrostatic action, p-p EDA action, and complexation. The results indicate that crab shells could serve as an innovative, cost-effective, and promising biosorbent for the treatment of the wastewater polluted by antibiotics. Author Contributions Conceptualization, L.J., X.H. and J.S.; methodology, L.J. and X.H.; software, Z.W. and J.S.; validation, J.S. and X.H.; formal analysis, L.C. and X.H.; investigation, L.C. and J.G.; resources, L.C., J.G. and Y.W.; data curation, J.S.; writing--original draft preparation, J.S. and X.H.; writing--review and editing, L.J.; visualization, J.S. and X.H. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 N2 adsorption-desorption isotherms and pore size distribution of the samples ((a,e) are K-CSB; (b,f) are P-CSB; (c,g) are M-CSB; and (d,h) are 800-CSB). Figure 2 SEM images of crab shell biochar ((a,b) are 800-CSB; (c,d) are K-CSB; (e,f) are P-CSB; and (g,h) are M-CSB). Figure 3 XRD pattern of modified biochar. Figure 4 Infrared spectrum of crab shell biochar. Figure 5 Adsorption of TC with different initial concentrations by modified carbon shell biochars at different times ((a,b) are K-CSB; (c,d) are P-CSB; and (e,f) are M-CSB). Figure 6 The effect of absorbent dosage on TC adsorption by modified crab shell biochar ((a) is K-CSB; (b) is P-CSB; and (c) is M-CSB). Figure 7 The effect of initial pH on TC adsorption by modified carb shell biochar ((a) is K-CSB, (b) is P-CSB, and (c) is M-CSB). Figure 8 The effect of time on 400 mg/L TC adsorption by modified biochar ((a) is K-CSB; (b) is P-CSB; and (c) is M-CSB). Figure 9 The adsorption kinetics models of TC adsorption on modified crab shell biochar ((a,c,e) are pseudo-first-order model of K-CSB, P-CSB and M-CSB, respectively; and (b,d,f) are pseudo-second-order model of K-CSB, P-CSB and M-CSB, respectively). Figure 10 The adsorption isotherm models of TC adsorption on modified crab shell biochar ((a,c,e) are Langmuir isotherm models of K-CSB, P-CSB, and M-CSB, respectively; and (b,d,f) are Freundlich isotherm models of K-CSB, P-CSB, and M-CSB, respectively). Figure 11 Mechanism diagram of TC adsorption on activated crab shell biochar. foods-12-01042-t001_Table 1 Table 1 BET parameters of crab shell biochar at different pyrolysis temperatures. Sample SBET (m2/g) Vtot (cm3/g) Average Pore Diameter (nm) CS 9.57 0.03 10.84 500-CSB 41.16 0.02 2.26 600-CSB 78.11 0.04 2.05 700-CSB 127.38 0.05 1.68 800-CSB 181.79 0.11 2.37 900-CSB 177.91 0.11 2.41 foods-12-01042-t002_Table 2 Table 2 Texture characteristics of the samples. Sample SBET (m2/g) Vtot (cm3/g) Average Pore Diameter (nm) 800-CSB 181.79 0.11 2.37 M-CSB 271.25 0.18 2.66 K-CSB 1095.14 0.63 2.18 P-CSB 381.16 0.21 2.24 foods-12-01042-t003_Table 3 Table 3 The adsorption kinetic parameters of TC adsorption on modified carb shell biochars. Sample PFO PSO qe 1 (mg/g) K1 g/(mg*min) R2 qe 2 (mg/g) K2 g/(mg*min) R2 K-CSB 100 mg/L 47.8322 0.0025 0.7955 98.0392 0.0003 0.9994 200 mg/L 125.8134 0.0024 0.9874 196.0784 0.0001 0.9968 400 mg/L 172.0526 0.0020 0.7737 384.6154 0.0001 0.9994 P-CSB 100 mg/L 36.4339 0.0025 0.7783 98.0392 0.0005 0.9998 200 mg/L 81.5731 0.0028 0.8008 181.8182 0.0002 0.9995 400 mg/L 130.5949 0.0018 0.6621 333.3333 0.0001 0.9992 M-CSB 100 mg/L 57.9511 0.0027 0.9046 86.9565 0.0001 0.9770 200 mg/L 98.4944 0.0002 0.9287 172.4138 0.0001 0.9958 400 mg/L 174.2690 0.0014 0.7280 277.7778 0.0001 0.9954 foods-12-01042-t004_Table 4 Table 4 The adsorption isotherm model parameters of TC adsorption on modified carb shell biochar. Sample Langmuir Freundlich qm (mg/g) KL (L/mg) R2 n KF [(mg/g)(L/mg)1/n] R2 K-CSB 400.00 0.1142 0.9852 2.1044 59.7041 0.6901 P-CSB 357.14 5.5044 0.9933 2.5714 57.0484 0.8259 M-CSB 277.78 1.8072 0.9939 2.7034 49.8291 0.7208 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Gao B.R. Dou M.M. Wang J. Li S.M. Wang D.Y. Ci L. Fu Y. Efficient persulfate activation by carbon defects g-C3N4 containing electron traps for the removal of antibiotics, resistant bacteria and genes Chem. Eng. J. 2021 426 131677 10.1016/j.cej.2021.131677 2. Wang B. Zhang Y. Zhu D. Li H. 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PMC10000495 | Over the past decades, several study programs have conducted genetic testing in cancer patients to identify potential genetic targets for the development of precision therapeutic strategies. These biomarker-driven trials have demonstrated improved clinical outcomes and progression-free survival rates in various types of cancers, especially for adult malignancies. However, similar progress in pediatric cancers has been slow due to their distinguished mutation profiles compared to adults and the low frequency of recurrent genomic alterations. Recently, increased efforts to develop precision medicine for childhood malignancies have led to the identification of genomic alterations and transcriptomic profiles of pediatric patients which presents promising opportunities to study rare and difficult-to-access neoplasms. This review summarizes the current state of known and potential genetic markers for pediatric solid tumors and provides perspectives on precise therapeutic strategies that warrant further investigations. precision medicine pediatric solid tumor actionable mutations Genomic Thailand Project of the Health Systems Research Institute, ThailandHSRI64-130 Faculty of Medicine Ramathibodi Hospital, Mahidol University, ThailandThis study was funded by the Genomic Thailand Project of the Health Systems Research Institute, Thailand, grant number HSRI64-130 (to D.P., S.S., S.H., U.A.). The APC was funded by Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand. pmc1. Introduction Cancer occurrence before the age of 20 years is rare, but it is one of the leading causes of disease-related mortality in children and adolescents globally . Approximately 300,000 children aged 0-19 years old worldwide are diagnosed with cancer each year , and 80% of these patients live in middle-income countries (LMCs). Hematologic malignancies are more common among pediatric cancers, comprising about half of all cases. Solid malignancies are rarer and heterogenous as following an age-specific pattern. In early childhood, embryonal-type solid tumors are common, such as neuroblastoma, retinoblastoma, medulloblastoma, hepatoblastoma, and Wilms tumor . The prognosis for childhood cancer has improved dramatically over the past four decades, particularly for hematologic malignancies . Nonetheless, treatment outcomes for childhood solid malignancies remain unsatisfactory, especially in LMCs . Genetic sequencing studies have led to the identification of somatic gene alterations as cancer hallmarks and germline predisposition and targeted the molecular abnormalities for the development of precise treatment . Dramatic differences in the genetic repertoire between normal and cancer cells provide advantages of molecular targeted therapies over traditional strategies based on the target selectivity . Several components in cellular signaling pathways, i.e., tyrosine receptor kinase (TRK), mitogen-activating protein kinase (MAPK) and phosphoinositide 3-kinases (PI3K)-mammalian target of rapamycin (mTOR), have been commonly identified as actionable mutations that would recommend appropriately targeted therapies . These generic biomarker-driven precise treatments have been investigated in several pre-clinical and clinical trials since the early 2000s . Progress in designing treatments targeting molecular alterations specific to pediatric cancers is considerably slow due to the rare and unique genetic alterations in children compared to adults . A report from the European Union (E.U.) revealed that up to 26 anticancer drugs approved for adults might be also effective in pediatric malignancies; however, only four of these drugs have been approved for childhood cancers . Nishiwaki S. and Ando Y. reported that only 3 out of 66 drugs with adult indications have been approved for pediatrics in the E.U., United States, and Japan . Thus far, larotrectinib and entrectinib have been two of the most successful molecularly targeted therapies for children with solid tumors and have shown their promising responses in patients with NTRK-fusion . In 2018, larotrectinib became the first drug to receive FDA approval to treat NTRK fusion-positive solid tumors in children and adults . Similarly, entrectinib, a multi-kinase inhibitor, also received approval for the treatment of TRK fusion solid tumors in patients aged >= 12 years . Combinatorial treatment of dabrafenib and trametinib has been recently approved by FDA (June 2022) for use in adult and pediatric patients > 6 years of age with unresectable or metastatic solid tumors with BRAF V600E mutation [New Drug Application (NDA): 202806 and 204114]. Note that abnormalities in NRAS, ABL1, JAK2, KIT, ALK and BRAF were among the group of common genetic variants found in adult and childhood cancers. In this review, we summarize the progress in the identification of actionable mutations in pediatric malignancies, FDA-approval status for pediatric and childhood treatment, and the recent update from clinical studies to explore the feasibility and utility of genomics-driven precision medicine. 2. Genetic Alterations on Cancer Hallmarks 2.1. Cancer Hallmarks and Common Targeted Signaling Pathways Cancers are driven by changes in cellular DNA which further promote the transition of genetic landscape, especially in cell survival programs, leading to unstoppable cell growth with abnormal cellular characteristics . In contrast to normal tissues, cancer cells can dysregulate their own signaling cascades autonomously, thus controlling their own cell fate . Besides their proficiency in cancer hallmarks in evading growth suppressors, resisting cell death, reprogramming cellular mechanisms, and avoiding immune destruction, cancer cells can also acquire the capability to sustain proliferative signaling in several alternative ways . Cancer cells may send signals to activate normal cells within the tumor parenchyma, which reciprocally communicate to supply cancer cells with various growth-promoting factors . Furthermore, common downstream components in distinct signaling cascades also allowed cancer cells to control cell fate in a growth factor-independent manner by triggering the downstream molecules directly, negating the need for ligand-mediated receptor activation . Hence, the vast majority of different cancers are coordinately modulated by canonical oncogenic drivers, including KRAS, MYC, NOTCH, and TP53. This factors highlights the need to fully elucidate their regulatory networks for further therapeutic development . 2.2. Tumor Cells Have Both Germline and Somatic Variants in Their Genome Cancer gene mutations can be either inherited or acquired. Hereditary or germline mutations refer to the genomic changes that occur in germ cells and can be detected in all cells of the offspring and are passed inter-generationally . Genetic predisposition has been described by certain characteristics, including ; Familial history of the same or related cancers; Occurrence of bilateral or multifocal cancers; Earlier age at disease onset; Physical suggestive of a predisposition syndrome; Appearance of specific tumor types corresponding to the genetic predisposition. Several studies have described germline mutations in cancer including BRCA1/2, TP53, ATM, CHEK2, MSH2 and PALB2 . Cancer cells harboring these germline predispositions are prone to increase cancer susceptibility, developing cancers at younger ages than usual. Using the 565 cancer-predisposing gene (CPG) panel for germline mutation analysis in children and adolescents with pan-cancer (n = 1120), Zhang et al. reported that 95 pathogenic variants were detected in 21 of the 60 autosomal dominant CPGs in 94/1120 patients. Interestingly, the prevalence of germline mutation was greatest among patients with non-CNS solid tumors (16.7%), followed by brain tumors (8.6%) and leukemia (4.4%) . Genetic predisposition syndromes associated with rare cancers of pediatric solid malignancies are provided in Table 1 . Cancer predisposition syndrome such as Li-Fraumeni syndrome (LFS) with TP53 mutation generally promotes the onset of various benign and malignant neoplasms, such as neuroblastoma (NB), osteosarcoma (OS), soft tissue sarcomas (STS), and brain tumors . Mutations in NF1 are associated with neurofibromatosis (NF), high-grade gliomas (L/HGGs), and malignant peripheral nerve sheath tumors. Mutations in SUFU or PTCH1 in Nevoid basal cell carcinoma are relevant to the development of the sonic hedgehog (SHH) subgroup-medulloblastoma (MB) . Somatic mutations are de novo genetic alterations that spontaneously develop in an individual cell over time and play a vital role in cancer development and progression . Studies have shown that the number of genetic abnormalities identified in each cancer patient may increase over time, leading to tumor survival against the selective pressure of drug actions, thereby acquiring resistance and causing disease progression . Commonly identified somatic mutations include those involved in RTK signaling (PDFGRA, ERBB2 and EGFR), MAPK signaling (NF1, KRAS, and MAP2K1), PI3K-mTOR signaling (PIK3CA, MTORC1/2 and PTEN), cell cycle (CDKN2A/B, RB1 and ATM), DNA maintenance (TP53), transcriptional regulators (MYC and MYCN), and epigenetic modifiers (SMARCB1 and ATRX) . Cancers usually involve a different spectrum of mutation which are strongly associated with pathogenesis and disease prognosis. A pan-cancer analysis reported by Grobner et al. showed that 93% of adult cancer patients harbor at least one significantly mutated gene, while only 47% presented such mutations in pediatric tumors. However, approximately 30% of recurrent hot-spot mutations in pediatrics overlapped with adult cancers, highlighting some potential druggable targets based on finding from adult cancers. Hence, advances in identifying and understanding oncogenic drivers and actionable mutations would further improve the current therapeutic strategies for the development of precision medicine in cancers. 2.3. Germline and Somatic Variants Classified as Druggable In the context of defining mutational actionability, the relevant effects of genomic aberration participating in cancer phenotypes are considered. DNA aberrations include missense, nonsense, frameshift mutations, and chromosome rearrangements, with some changes affecting only a single DNA base that may or may not alter the protein's property and some point mutations completely abrogating protein expression. A wide variety of gene alterations have been detected such as activating point mutation in BRAF, ALK, EGFR and FGFR1 genes, high copy number gains in PDGFRA and ERBB2, loss-of-function mutation affecting PTEN, PTPN11, PIK3R1, and MTORC1, CDKN2A/2B deletions, or in-frame expression of large indels (NOTCH1 and FOXA1) . Other changes involving larger stretches of DNA may include rearrangements, deletions, or duplications of long stretches of DNA . For example, exon skipping on MET exon 14 proto-oncogenes resulting from intronic mutation increases the protein lifespan and promotes MET activation in lung carcinogenesis . The significance of genetic variants may vary depending upon their potential effects on cellular functions. An "actionable" mutation is defined as a genetic aberration that is potentially responsive to targeted therapy, while a "driver" mutation refers to variants that confer a growth advantage to cancer cells but may not be targetable with a specific treatment yet. Passenger mutation is used to designate cancer-neutral variations and is unlikely to be under selective pressure during the evolution of the cancerous cells . The "passenger" mutation has the lowest tendency to impact protein function, most of which are synonymous substitutions; however, these mutations occur more frequently than driver or actionable mutations. Unraveling the passenger mutational paradigm has otherwise revealed the existence of pre-existing latent driver mutations in which certain combinations of the passenger mutations could indeed be functional drivers. One example is the non-hotspot, passenger mutation of the Akt1 gene at position L52R, C77F, and Q79K, which promotes its membrane localization similarly to the E17K driver. In contrast, the co-existence of D32Y, K39N, and P42T passenger mutations can lead to Akt conformational inactivation, suggesting that treatment decisions based only on genetics may overlook crucial actionable components . In addition, silent mutations occurring near the donor splice junction could contrarily affect exon splicing. For example, T125T mutation in TP53 is a recurrent mutation that is generally considered a non-functional passenger event; however, its existence at the -1 donor site of exon 4 raises the possibility that this mutation affects splicing. Further integration with RNA-seq data demonstrated that T125T mutation resulted in the retention of intron 4 and introduced a premature stop codon such as nonsense-mediated decay . Thus, aberrant splicing caused by silent mutations should be carefully evaluated during interpretation of the sequencing results. The accumulated data of genetic composition data from the tumors of patients has become a growing compendium of molecular biomarkers for precise treatment with FDA-approved drugs. Figure 1 summarizes the actionable mutations currently approved by FDA consortium for targeted therapy in adult cancers and pediatric solid tumors. Common actionable genetic aberrations associated with the National Comprehensive Cancer Network (NCCN) guidelines or FDA-approved targeted therapies are extensively summarized in Table 2. The data were predominantly gathered from the OncoKB database and the representative cancer types, and levels of evidence were included . 3. Pediatric Cancer Genome 3.1. Pediatric vs. Adult Cancer Development Pediatric cancers reflect a heterogeneous group of disorders distinct from adult cancers in terms of cellular origins, genetic complexity, and specific driver alterations . Pediatric malignancies typically occur in developing mesoderm rather than adult epithelia (ectoderm) and are often induced by inherited or sporadic errors during development . Studies have quantified the mutation burden in many pediatric cancers, identifying approximately 5 to 10 protein-coding variants identified across multiple tumor types except in osteosarcoma, which showed an average of 25 protein-affecting mutations. In contrast, the average number of mutations in adult cancers ranges between 33 to 66 in pancreatic, colon, breast, and brain cancers while mutagen-caused adult tumors (such as melanoma and lung cancers) can include up to 200 protein-coding variants . At diagnosis, patients with pediatric cancers tend to have less complexity on mutational spectra than those in adult cancers; however, with treatment-refractory tumors and recurrence--the mutation rates in pediatric tumors have increased to be comparable to adult tumors . Moreover, the rare occurrence of pediatric cancers and the low frequency of recurrent genomic alterations have a great impact on the investigations and the availability of targeted agents. Thus, there is an urgent need to accelerate the pace of genomic data acquisition and clinical trials in children to design more effective strategies for pediatric precision oncology. 3.2. Somatic and Germline Mutations Identified in Pediatric Cancer Cohorts Single nucleotide variations (SNVs) and small indels are the usual mutations identified in adult cancers. In contrast, childhood cancers show a relatively high prevalence of copy number aberrations (CNAs) and specific structural variations (SVs). Note that insertion and deletion lead to adding and removing at least one nucleotide to the gene, respectively, which can affect protein functions and contribute to carcinogenesis. Current data suggest that approximately 10% of pediatric cancers are caused by genetic predisposition . Zhang et al. revealed that 95 out of 1120 (8.5%) patients younger than 20 years of age harbor germline mutations in cancer-predisposing genes. Diets et al. performed trio-based whole-exome sequencing on the germline DNA of 40 selected children with cancer and their parents. Of these, germline pathogenic mutations were identified in 20% (8/40) of children with cancer . Similarly, Grobner et al. reported that most germline variants were related to DNA repair genes from mismatch (MSH2, MSH6, PMS2) and double-stranded break (TP53, BRCA2, CHEK2) repair. Using combined somatic and germline sequencing for children with solid tumors, Parsons et al. identified actionable mutations in up to 40% (47/121) of pediatric solid tumor tissues. Likewise, Wong et al. performed the combination of tumor and germline sequencing (WGS) and RNA sequencing (RNA-seq) to identify 968 reportable molecular aberrations (39.9% in both WGS and RNA-seq; 35.1% in WGS only and 25.0% in RNA-seq only) in 247 high-risk pediatric cancer patients with 252 tumor tissues. Interestingly, 93.7% of these patients had at least one germline or somatic aberration, 71.4% had therapeutic targets, and 5.2% had a change in diagnosis . These cohort studies emphasized that comprehensive molecular profiling could resolve molecular aberration in high-risk pediatric cancer and provide clinical benefits in a significant number of patients. In the era of next-generation sequencing, publicly genomic data access is considered one of the keys to accelerate research. The St. Jude Cloud is one of the most promising data-sharing ecosystems, with genomic data from >10,000 pediatric patients with cancer and long-term survivors. When exploring the mutational profile of pediatric solid tumors, the resource has revealed common genetic alterations among the different cancer types, as shown in Table 3. This integrative view of genomic data could be further used to expedite studies of pediatric cancer-associated risk factors and initiate novel therapeutic investigations for improving treatment outcomes. 3.3. Predictive and Common Genetic Variant Abnormalities Identified in Pediatric Tumors The reports of actionable mutations identified in various studies have ranged from 27% to 100%, depending on the study design . Several methods have been adopted for comprehensive molecular analysis to discover the actionable mutations that result in the targeting of cancer-associated elements. Table 4 contains a comprehensive, up-to-date summary of genomic aberrations found in pediatric solid tumors, together with potential targeted treatments, based on several public databases . We systemically reviewed genomic alterations with high prevalence in pediatric cancers using comprehensive WES and RNA-seq data via the St. Jude Cloud (www.stjude.cloud; accessed on 26 September 2022) . Importantly, the genomic point mutations and gene fusions reported by this public domain are unique and different from those variants identified in the OncoKB database (the mutational collection of adult cancers) . In addition, the potential druggable targets of these significant genomic alterations required further testing in pediatric solid tumor patients. A significant number of studies were reported by the Clinical Interpretation of Variants in Cancer (CIViC) database accessed on 18 September 2022) which matched genomic alteration and molecularly targeted therapies tested in pediatric patients. These treatment designs were translated from the clinical care of adults across different tumor types but harboring the same genetic dysregulation, which gave satisfactory clinical outcomes. For pediatric solid tumors with no clinical evident support or undruggable genomic alterations, we listed the potential targeted therapies based on the knowledge from adult cancers as suggested by cBioPortal (www.cbioportal.org; accessed on 30 April 2022) and OncoKB accessed on 17 April 2022) that should be considered for further investigation and optimization for pediatric treatments. As of now, fewer number of patients could hinder the availability of molecular characterization and statistically meaningful preclinical/clinical outcomes. However, this challenge can be overcome by the initiation of multi-institutional cooperation and international data sharing, which would enable clinicians to effectively explore optimized therapeutic interventions toward pediatric precision oncology. 4. Current Progress in Clinical Trials for Pediatric Precision Oncology Genomic precision medicine has demonstrated preferential outcomes among ongoing genomic-driven clinical trials in adult cancers. Yet, clinical investigations based on pediatric tumor genetics are still lacking. Based on the patient genetic profile screening, scattered reports on molecularly defined pediatric patients are showing prominent responses to some targeted therapies. For example, targeting ALK has shown success in treatments of ALK(+) non-small cell lung cancers and also in childhood anaplastic large cell lymphoma (ALCL) and inflammatory myofibroblastic tumor using the ALK inhibitor crizotinib . While ALK mutation is the most common somatic mutation in neuroblastoma, crizotinib was compromised due to the interference by common ALK mutation F1174 . Since then, ceritinib, alectinib, brigatinib, and lorlatinib have been approved against advanced ALK+ NSCLC . Intriguingly, the third-generation TKI that targets both ALK and ROS1, lorlatinib, has recently shown promise in patients with ALK mutated neuroblastoma, but most of the studies are still at phase I clinical trial. . Nonetheless, repotrectinib, a next-generation ROS1/TRK inhibitor with >90-fold potency against ROS1 than crizotinib in NSCLC patients is also being tested for dose escalation in phase II clinical trial with patients aged >= 12 years . Another promising example is the targeted therapy against Ras-Raf-MEK-ERK signaling cascade which include somatic BRAF alterations (BRAF V600E and BRAF fusions). The prototype for targeting BRAF V600E/K is cutaneous melanoma, where 40-60% of patients with these mutations are eligible for the FDA-approved BRAF-inhibitor, vemurafenib . Low-grade-gliomas have been identified to contain multiple alterations in Ras-Raf-MEK-ERK pathway, and a single treatment of vemurafenib in malignant glioma resulted in tumor regression . Recently, Jain et al. reported that a combination of BRAF-inhibitor dabrafenib and MEK-inhibitor trametinib enhanced treatment efficacies in pediatric low-grade-glioma carrying KIAA1549-BRAF fusion. Additionally, several studies have utilized the combination of molecularly targeted agents and traditional chemotherapy or radiation to reduce the severe side effects caused by an intensive dose of chemo/radiotherapy while minimizing acquired drug resistance due to selective pressure (Table 5). The following large-scale pediatric and young-adult precision oncology programs have been launched with multiple-arm trials for patients with matched molecular profiles: TAPUR (ClinicalTrials.gov identifier NCT02693535), NCI-COG Pediatric MATCH (NCT03155620), the Tumor-Agnostic Precision Immuno-Oncology and Somatic Targeting Rational for You (TAPISTRY) (NCT04589845). These global, multicenter, open-label, multi-cohort studies are now at phase II, and the treatment assignment has relied on the basis of relevant onco-genotypes as identified by a Clinical Laboratory Improvement Amendments (CLIA)-certified or a validated next-generation sequencing (NGS) assay. While the eligible criteria of TAPUR are open for patients aged 12 years old or older, most of the patients enrolled are reported to have adult cancer phenotypes . In contrast, the NCI-COG Pediatric MATCH aims to evaluate the molecular-targeted therapies with selected biomarkers of childhood and young adult patients with a reported detection rate of actionable alterations of 31.5% from the first 1000 tumors screened. Assignments to treatment arms were made for 28% of patients screened and 13% of patients enrolled in the treatment trial . In the TAPISTRY study, nine targeted treatments are being examined, and eleven non-randomized treatment arms are available for participants of all ages with locally advanced/metastatic solid tumors. The purpose of this study is to evaluate the safety and efficacy of different targeted therapies and immunotherapies in patients as single agents, but the results of the study are still to be released. Overall, the advancements in high-throughput sequencing technology have closed the gap between the current treatment paradigm and precision medicine, markedly improving rates of response, progression-free survival (PFS), and overall survival (OS) compared to traditional randomized trials. Moreover, the multicenter, open-label, multi-arm treatment designs can further benefit treatment strategies by yielding efficacy and toxicity data in a timely manner with cost-effectiveness. Therefore, in the future, international coordination will be crucial to generate a database to inform rational trial design and to evaluate the combination of treatments/interventions that ensure more favorable outcomes. The current applications of precision study designs for pediatric cancers (summarized from clinicaltrials.gov; accessed on 17 August 2022) are shown as single-arm and multiple-arm designs in Table 5 and Table 6, respectively. 5. Challenges and Perspectives Large-scale cancer sequencing studies such as the 1000 Genomes Project , The Cancer Genome Atlas (TCGA) , and the International Cancer Genome Consortium (ICGC) provide an extensive landscape of tumor genomic profiles which substantially facilitate the predication of recurrent hot-spot mutations on the selected type of cancers. Other large databases aim to collect the profile of childhood cancers include St. Jude/Washington University Pediatric Cancer Genome Project (PCGP) and NCI's Therapeutically Applicable Research to Generate Effective Treatments (TARGET) which are accessible via the St. Jude Cloud accessed on 26 September 2022) public data repository. These large-scale studies have confirmed that the spectra of genomic alterations and their relevant mechanisms differ in childhood tumors from those predominantly occurring in adult cancer--at least by half. Thus, the actionability of pediatric-driven mutations needs to be carefully interpreted before translating into a targeted treatment option. Several challenges need to be addressed when researchers launch the study/trial for pediatric cancer treatment. Many pediatric cancers are rare, and finding the right patient population for the drugs is challenging. In fact, a small patient population and a prolonged trial duration are not uncommon issues in the settings of rare diseases and low-incidence pediatric cancers . Optimal statistical designs for less stringent comparisons, for example, by relaxing type I error (higher than 5%) or power (lower than 80%) can still provide meaningful results from small but faster trials . Implementing multi-arm multi-stage trial design would allow patients with poor prognosis to be stratified into multiple phase II arms; receiving the window-of-opportunity/experimental therapies and restaging by serial biopsies and molecular characterizations to inform ongoing treatment choices . These approaches remain useful to increase the overall feasibility for rare disease trials, i.e., keeping the sample size as small as possible while maintaining the power and ability to address the trial objectives. Only 45% of pediatric cancer driver genes are shared with adult cancers, suggesting that novel therapeutic agents are required for pediatric cancer. Additionally, pediatric cancers are often driven by structural variants that can be challenging to identify and target. Nonetheless, children with cancers have accumulated fewer genetic mutations, thus making genomic targeting simpler than adults . In a broad view, cancer intrinsic targets (e.g., mutated oncogene, tumor suppressor, epigenetics, synthetic lethal, and DNA damage) play crucial roles in cancer pathogenesis and thus could serve as the key stones for drug development against childhood cancers . Another approach in drug development strategy is a mechanisms-of-action (MoA)-driven approach which successfully exemplified the efficiency of nivolumab and larotrectinib as targeted anticancer drugs against programmed cell death protein-1 (PD1) and TRK receptors, respectively . Nonetheless, lessons learned from adult cancers have warned us that many pediatric cancers would have failed to express mutated kinase targets, and resistance to targeted therapies would rapidly occur. Recently, newly emerging cancer targets have been discovered upon multidimensional complexity of the dynamic oncogenic states, for example, tumor archetypes, master regulators, cancer-associated protein-protein interactions, and metabolic vulnerabilities . The development of drugs against the emerging classes of cancer targets may deliver adjunct/complementary agents for combination with targeted therapeutic regimens . The emergence of gene editing technologies such as transcription activator-like effector nucleases (TALENS) and clustered regularly interspaced palindromic repeats (CRISPR) paired with the CRISPR-associated endonuclease 9 (CRISPR-CAS9) offer the powerful customizable therapeutic options to precisely edit the targeted genes , thus providing hope to all pediatric cancers to be benefited from genomic-driven precision medicine approach. Comprehensive molecular profiling of the genetic variants/mutations, gene expression at both transcripts and protein levels, and perhaps information on post-translational modifications and metabolites are coordinately utilized to improve the accuracy of molecularly targeted agents. Challenges in this grand scheme, besides big data sharing and multi-omics integration, are interpreting complex high-dimensional data in the biological sense, prioritizing findings into actionable targets/pathways, and achieving the candidate compounds/drugs for precise treatment. Aberrant expression of messenger RNA associated with genomic changes could contribute to the biology of tumor progression. In most cases, RNA-seq analysis can increase the coverage number of variant curations, especially the comprehensive gene fusion discovery and tumor expression subgroup analysis, when compared to WGS alone . A novel molecularly guided approach, so-called transcriptomic connectivity analysis, utilizes the power of RNA-seq to detect aberrant gene expression and employs transcriptomic reversal of cancer cells/tissues for repurposing FDA-approved drugs . This molecularly guided therapeutic approach could be an asset for prioritizing the approved drugs for off-label use in childhood cancer trials. Despite the promising demonstration of ongoing genomic-driven clinical trials of targeted anticancer small molecules, cancer immunotherapies have become significant advances for pediatric solid tumors . Ganglioside GD2 is a sialic acid-containing glycosphingolipid that highly expressed on the surface of multiple pediatric solid tumors, i.e., neuroblastoma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, and brain tumors including diffuse intrinsic pontine glioma (DIPG) and medulloblastoma . Thus, GD2 is recognized as one of the most promising targets for pediatric cancer immunotherapy. Dinutuximab, anti-GD2 monoclonal antibody, has been approved as the first-line therapy for high-risk pediatric neuroblastoma , while GD2-specific chimeric antigen receptor (CAR) T cell therapy is under investigation in the early phase trials for children with neuroblastoma, osteosarcoma, and brain tumors (ClinicalTrials.gov identifier NCT03721068, NCT04539366, NCT04099797, NCT04196413). Besides GD2, newly emerging targets for pediatric cancer immunotherapy, including PD1/PD-L1 (NCT04544995, NCT04796012), B7-H3 (CD276; NCT04864821, NCT04743661), HER2 (NCT00902044, NCT04616560) and CD47 (NCT04525014, NCT04751383), have been actively investigated for pediatric sarcomas and brain tumors. Last but not least, it should be noted that new therapeutics often lack dosage guidelines for children . Acknowledging children have different drug responses and tolerance profiles compared to adults, it is crucial to define the optimal dosages of new drugs/biologics (and the off-label use of FDA-approved medications) to achieve preferred therapeutic outcomes. Recent innovations in study designs (i.e., phase I dose-finding design for pediatric population, the potential inclusion of children in adult trials, cooperative group trials) , together with the regulatory initiatives in the United States (US) and the E.U. which encourage the development of novel anticancer therapies in children , provide guidance to address this challenge while accelerating the pace of genomic-driven precision medicine in pediatric oncology. 6. Conclusions Essential questions that need to be addressed in applications of precision therapeutic program include the applicability of the genetic testing, the significance of the mutation variant, and the existence of an approved targeted therapy. Although targeted agents are approved for a set of tumors harboring specific mutations, future development of clinical guidelines may recommend these agents to be used off-label in different tumor types with the same mutations. Identifying the mutational signatures of pediatric solid tumors will open opportunities for new targeted therapeutic strategies since their malignant origin manifests differently from the adults. Similar genomic-driven precision medicine approaches have been launched by several institutes, while the long-term effects of many of those novel agents are just beginning to be evaluated. These treatments could improve survival and reduce toxicity in pediatric patients and maximize therapeutic advantages when incorporated into standard care. Acknowledgments The graphical abstract was created with BioRender.com (accessed on 29 November 2022). Author Contributions Conceptualization, S.C.; methodology, P.S., W.C., P.C. (Parunya Chaiyawat), P.C. (Pongsakorn Choochuen), D.P., S.S., S.H., U.A. and S.C.; resources, D.P., S.S., S.H. and U.A.; data curation, P.S.; writing--original draft preparation, P.S.; writing--review and editing, W.C., P.C. (Parunya Chaiyawat), P.C. (Pongsakorn Choochuen), D.P., S.S., S.H., U.A. and S.C.; visualization, P.S. and S.C.; supervision, D.P., S.S., S.H., U.A. and S.C.; funding acquisition, D.P., S.S. and U.A. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Abbreviations TRK Tyrosine receptor kinase MAPK Mitogen-activating protein kinase PI3K Phosphoinositide 3-kinases NTRK Neurotrophic tyrosine receptor kinase CPG Cancer predisposing gene CNS Central nervous system RTK Receptor tyrosine kinase WGS Whole genome sequencing WES Whole exome sequencing TGFB Transforming growth factor beta NSCLC Non-small cell lung cancer Figure 1 Oncogenic drivers identified in adult and pediatric solid tumors. These selective biomarkers are predicted to be responsive to various levels of FDA-approved drugs (detailed in Table 1). Note that targeted therapies against PTCH1 and ALK in medulloblastoma and neuroblastoma are currently undergoing clinical assessment and awaiting further approval. cancers-15-01418-t001_Table 1 Table 1 Mutated genes and dysregulated signaling pathways in selected cancer predisposition syndromes. Cancer Predisposition Syndrome Common Solid Tumors Mutated Genes (Inheritance) Dysregulated Pathways Reference Beckwith-Wiedemann syndrome Wilms tumor, hepatoblastoma, neuroblastoma, rhabdomyosarcoma CDKN1C (AD) Cell cycle Constitutional mismatch repair deficiency Brain tumor, neuroblastoma, Wilms tumor, osteosarcoma, rhabdomyosarcoma MLH1, MSH2, MSH6, PMS2 (AR) DNA mismatch repair Hereditary retinoblastoma Retinoblastoma, melanoma, osteosarcoma, pineoblastoma RB1 (AD) Cell cycle Li-Fraumeni syndrome Brain tumor, sarcoma, neuroblastoma, rhabdomyosarcoma, retinoblastoma TP53 (AD) Cell cycle, apoptosis Neurofibromatosis Glioma, astrocytoma, ependymoma, malignant peripheral nerve sheath tumors, neuroblastoma, rhabdomyosarcoma NF1, NF2 (AD) RAS/MAPK Rhabdoid tumor predisposition syndrome Atypical teratoid/rhabdoid tumor, malignant rhabdoid tumor SMARCB1, SMARCA4 (AD) Wnt/b-catenin, Sonic hedgehog Multiple endocrine neoplasia Ependymoma, Medullary thyroid cancer MEN1, RET (AD) Transcriptional activity Nevoid basal cell carcinoma Medulloblastoma, rhabdomyosarcoma PTCH1, PTCH2, SUFU (AD) Sonic hedgehog Familial adenomatous polyposis Medulloblastoma, hepatoblastoma APC (AD) Wnt/b-catenin Tuberous sclerosis Subependymal giant cell astrocytoma, rhabdomyosarcoma TSC1, TSC2 (AD) mTOR Bloom syndrome Osteosarcoma, Wilms tumor BLM (AR) DNA double-strand repair Rubinstein-Taybi syndrome Medulloblastoma, neuroblastoma, rhabdomyosarcoma CREBBP (AD) Transcriptional regulation Noonan syndrome Rhabdomyosarcoma, neuroblastoma, glioma, hepatoblastoma PTPN11, SOS1, RAF1, KRAS, MAP2K1 (AD) RAS/MAPK Abbreviations: AD, autosomal dominant; AR, autosomal recessive. cancers-15-01418-t002_Table 2 Table 2 Targeted therapies recommended for the selected genetic alterations according to FDA-approved or NCCN guidelines . Gene Alterations Targeted Therapies Cancer Types FDA-Approved Level a AKT1 E17K AZD5363 Breast Cancer, Ovarian Cancer; Endometrial Cancer Lv.3 ALK Fusions Alectinib; Brigatinib; Ceritinib; Crizotinib Non-Small Cell Lung Cancer Lv.1 Brigatinib; Ceritinib; Crizotinib Inflammatory Myofibroblastic Tumor Lv.2 Oncogenic Mutations Lorlatinib Non-Small Cell Lung Cancer; Neuroblastoma c Lv.1 Crizotinib Non-Small Cell Lung Cancer; Neuroblastoma c Lv.R2 ARAF Oncogenic Mutations Sorafenib Non-Small Cell Lung Cancer Lv.3 ARID1A Truncating Mutations PLX2853; Tazemetostat All Solid Tumors Lv.4 ATM Oncogenic Mutations Olaparib Prostate Cancer Lv.1 BRAF V600E Dabrafenib + Trametinib Melanoma; Non-Small Cell Lung Cancer; Low grade glioma b; High grade glioma b Lv.1 Encorafenib + Cetuximab Colorectal Cancer Fusions or V600E Selumetinib Pilocytic Astrocytoma Lv.2 V600E Dabrafenib + Trametinib, Vemurafenib + Cobimetinib Diffuse Glioma; Encapsulated Glioma; Ganglioglioma Fusions Trametinib; Cobimetinib Ovarian Cancer Lv.3 V600E Dabrafenib + Trametinib Biliary Tract Cancer G464, G469A, G469R, G469V, K601, L597 PLX8394 All Solid Tumors Lv.4 BRCA1/2 Oncogenic Mutations Niraparib; Olaparib; Olaparib + Bevacizumab; Rucaparib Ovarian Cancer; Peritoneal Serous Carcinoma Lv.1 Olaparib; Rucaparib Prostate Cancer Olaparib; Talazoparib Breast Cancer Lv.3 BRIP1 Oncogenic Mutations Olaparib Prostate Cancer Lv.1 CDK4 Amplification Palbociclib; Abemaciclib Dedifferentiated Liposarcoma; Well-Differentiated Liposarcoma Lv.4 CDK12 Oncogenic Mutations Olaparib Prostate Cancer Lv.1 CDKN2A Oncogenic Mutations Palbociclib; Ribociclib; Abemaciclib All Solid Tumors Lv.4 CHEK1/2 Oncogenic Mutations Olaparib Prostate Cancer Lv.1 EGFR Exon 19 deletion, L858R Afatinib; Dacomitinib; Erlotinib; Erlotinib + Ramucirumab; Gefitinib; Osimertinib Non-Small Cell Lung Cancer Lv.1 Exon 20 insertion Amivantamab; Mobocertinib G719, L861Q, S768I Afatinib T790M Osimertinib A763_Y764insFQEA Erlotinib Lv.2 E709_T710delinsD Afatinib Lv.3 Exon 19 insertion Erlotinib; Gefitinib Exon 20 insertion Poziotinib Kinase Domain Duplication Afatinib A763_Y764insFQEA or Exon 19 insertion or L718V, L747P Afatinib Lv.4 D761Y Osimertinib Kinase Domain Duplication Erlotinib; Gefitinib Amplification or A289V, R108K, T263P Lapatinib Glioma Exon 20 insertion, T790M Erlotinib; Gefitinib; Afatinib Non-Small Cell Lung Cancer Lv.R1 C797S, D761Y, G724S, L718V Osimertinib; Gefitinib Lv.R2 ERBB2 Amplification Ado-Trastuzumab; Emtansine; Lapatinib + Capecitabine; Lapatinib + Letrozole, Margetuximab + Chemotherapy; Neratinib; Neratinib + Capecitabine; Trastuzumab + Pertuzumab + Chemotherapy; Trastuzumab + Tucatinib + Capecitabine; Trastuzumab Deruxtecan; Trastuzumab, Trastuzumab + Chemotherapy Breast Cancer Lv.1 Pembrolizumab + Trastuzumab + Chemotherapy; Trastuzumab + Chemotherapy; Trastuzumab Deruxtecan Esophagogastric Cancer Lv.1 Trastuzumab + Lapatinib; Trastuzumab + Pertuzumab; Trastuzumab Deruxtecan Colorectal Cancer Lv.2 Oncogenic Mutations Ado-Trastuzumab; Emtansine; Trastuzumab Deruxtecan Non-Small Cell Lung Cancer Lv.2 Neratinib Breast Cancer; Non-Small Cell Lung Cancer Lv.3 ESR1 Oncogenic Mutations AZD9496; Fulvestrant Breast Cancer Lv.3 FANCL Oncogenic Mutations Olaparib Prostate Cancer Lv.1 FGFR1 Amplification Debio1347; Infigratinib; Erdafitinib Lung Squamous Cell Carcinoma Lv.3 Oncogenic Mutations Debio1347; Infigratinib; Erdafitinib; AZD4547 All Solid Tumors Lv.4 FGFR2 Fusions Erdafitinib Bladder Cancer Lv.1 Infigratinib; Pemigatinib Cholangiocarcinoma Oncogenic Mutations Debio1347; Infigratinib; Erdafitinib; AZD4547 All Solid Tumors Lv.4 FGFR3 Fusions or G370C, R248C, S249C, Y373C Erdafitinib Bladder Cancer Lv.1 G380R, K650, S371C Erdafitinib Lv.3 Oncogenic Mutations Debio1347; Infigratinib; Erdafitinib; AZD4547 All Solid Tumors Lv.4 FLI1 EWSR1-FLI1 Fusion TK216 Ewing Sarcoma Lv.4 HRAS Oncogenic Mutations Tipifarnib Bladder Urothelial Carcinoma; Head and Neck Squamous Cell Carcinoma Lv.3 IDH1 R132 Ivosidenib Cholangiocarcinoma Lv.1 Oncogenic Mutations Chondrosarcoma Lv.2 R132 Glioma Lv.3 KDM6A Oncogenic Mutations Tazemetostat Bladder Cancer Lv.4 KIT A502_Y503dup, K509I, N505I, S476I, S501_A502dup, A829P and 5 other alterations, D572A and 65 other alterations, K642E, T670I, V654A Imatinib; Regorafenib; Ripretinib; Sunitinib Gastrointestinal Stromal Tumor Lv.1 A829P and 5 other alterations Sorafenib Gastrointestinal Stromal Tumor Lv.2 KRAS G12C Sotorasib Non-Small Cell Lung Cancer Lv.1 Adagrasib Non-Small Cell Lung Cancer Lv.3 Adagrasib; Adagrasib + Cetuximab Colorectal Cancer Oncogenic Mutations Cobimetinib; Trametinib; Binimetinib All Solid Tumors Lv.4 MAP2K1 Oncogenic Mutations Cobimetinib; Trametinib Melanoma; Non-Small Cell Lung Cancer; Low grade glioma c Lv.3 MDM2 Amplification Milademetan Dedifferentiated Liposarcoma; Well-Differentiated Liposarcoma Lv.4 MET D1010, Exon 14 deletion, Exon 14 splice mutation Capmatinib; Tepotinib Non-Small Cell Lung Cancer Lv.1 Amplification or D1010, Exon 14 deletion, Exon 14 splice mutation Crizotinib Lv.2 Y1003mut Tepotinib; Capmatinib; Crizotinib Lv.3 Fusions Crizotinib All Solid Tumors Lv.4 MTOR E2014K, E2419K Everolimus Bladder Cancer Lv.3 Q2223K Everolimus Renal Cell Carcinoma L2209V, L2427Q Temsirolimus Oncogenic Mutations Everolimus; Temsirolimus All Solid Tumors, Rhabdomyosarcoma c Lv.4 NF1 Oncogenic Mutations Selumetinib Neurofibroma b Lv.1 Trametinib; Cobimetinib All Solid Tumors Lv.4 NRG1 Fusions Zenocutuzumab All Solid Tumors Lv.3 NTRK1/2/3 Fusions Entrectinib; Larotrectinib All Solid Tumors b Lv.1 PALB2 Oncogenic Mutations Olaparib Prostate Cancer Lv.1 PDGFB COL1A1-PDGFB Fusion Imatinib Dermatofibrosarcoma Protuberans Lv.1 PDGFRA Exon 18 in-frame deletions or insertions, Exon 18 missense mutations Avapritinib Gastrointestinal Stromal Tumor Lv.1 Oncogenic Mutations Regorafenib Gastrointestinal Stromal Tumor; Medullary thyroid cancer c, Hepatocellular carcinomac Lv.2 Imatinib; Ripretinib; Sunitinib Gastrointestinal Stromal Tumor D842V Dasatinib D842V Imatinib Gastrointestinal Stromal Tumor Lv.R1 PIK3CA C420R and 10 other alterations Alpelisib + Fulvestrant Breast Cancer Lv.1 Oncogenic Mutations (excluding C420R, E542K, E545A, E545D, E545G, E545K, Q546E, Q546R, H1047L, H1047R and H1047Y) Alpelisib + Fulvestrant Lv.2 PTCH1 Truncating Mutations Sonidegib; Vismodegib Medulloblastoma Lv.3 PTEN Oncogenic Mutations GSK2636771; AZD8186 All Solid Tumors Lv.4 RAD51B, RAD51C, RAD51D, RAD54L Oncogenic Mutations Olaparib Prostate Cancer Lv.1 RET Fusions or Oncogenic Mutations Pralsetinib; Selpercatinib Non-Small Cell Lung Cancer, Thyroid Cancer, Medullary Thyroid Cancer b Lv.1 Fusions Cabozantinib Non-Small Cell Lung Cancer; Sarcoma c Lv.2 Vandetanib Non-Small Cell Lung Cancer Lv.3 ROS1 Fusions Crizotinib Non-Small Cell Lung Cancer Lv.1 Entrectinib Biomarker (+), solid and brain b SMARCB1 Deletion Tazemetostat Epithelioid Sarcoma Lv.1 STK11 Oncogenic Mutations Bemcentinib + Pembrolizumab Non-Small Cell Lung Cancer Lv.4 TSC1/2 Oncogenic Mutations Everolimus Encapsulated Glioma; Subependymal giant cell astrocytoma b Lv.1 a FDA-approved level 1 = FDA-recognized biomarker predictive of response to an FDA-approved drug in this indication; level 2 = Standard care biomarker recommended by the NCCN or other professional guidelines predictive of response to an FDA-approved drug in this indication; level 3 = Standard care or investigational biomarker predictive of response to an FDA-approved or investigational drug in another indication; level 4 = Compelling biological evidence supports the biomarkers as being predictive of response to a drug; level R1 = Standard care biomarker predictive of resistance to an FDA-approved drug in this indication; level R2 = Compelling clinical evidence supports the biomarker as being predictive of resistance to a drug. b FDA-approved for pediatrics used . c Clinical trial in pediatrics. cancers-15-01418-t003_Table 3 Table 3 Somatic and germline mutated genes of selected pediatric tumors. Tumor Significantly Mutated Genes (# Prevalence) Medulloblastoma DDX3X (5.8%), KMT2D (5.8%), CTNNB1 (5.5%), PTCH1 (5.1%), TP53 (4.0%), SMARCA4 (3.6%), KDM6A (3.1%), SUFU (1.3%), SMO (1.5%), KMT2C (1.4%), CREBBP (1.3%), APC + (0.6%), IDH1 (0.4%) High grade glioma TP53+++(28.5%), ATRX (11.3%), PIK3CA (5.6%), PDGFRA++(5.1%), BCOR (3.0%), PPM1D++(3.9%), CREBBP++(1.8%), NF1+(0.8%), EGFR++(0.6%) Ependymoma RELA++(25.0%), IGF2R+(20.0%) Low grade glioma FGFR1++(33.3%), BRAF (8.7%), NF1+(3.9%), KIAA1549 (1.9%) Neuroblastoma MYCN (36.2%), MYCNOS (33.0%), ATRX (22.2%), DDX1 (22.3%), ALK (1.4%), RYR1 (0.5%), PTPN11 (0.7%) Wilms tumor MYCN (12.4%), MYCNOS (12.4%), TP53 (3.2%), DROSHA++(1.8%), WT1 (1.6%), CTNNB1 (1.5%), DGCR8 (1.1%) Osteosarcoma TP53+(30.0%), RB1+(15.4%), ATRX (9.7%) Ewing's sarcoma EWSR1 (29.6%), FLI1 (25.9%), ERG (4.7%), STAG2 (2.4%) Retinoblastoma RB1+(51.6%), BCOR (3.2%) Rhabdomyosarcoma PAX3++(28.6%), FOXO1++(25.9%), PAX7++(16.7%), TP53+++(12.3%), FGFR4++(7.7%), NRAS++(4.6%) # Prevalence of mutated genes in the selected pediatric tumor. Data from cBioPortal for cancer genomics (www.cbioportal.org; accessed on 30 April 2022). + Germline, ++ Relapse. Data from St. Jude Cloud public data repository (www.stjude.cloud; accessed on 18 September 2022). cancers-15-01418-t004_Table 4 Table 4 Significant genomic alterations of actionable genetic mutations in pediatric solid tumors. Signaling Pathway Gene Alterations Effected Domain Pediatric CANCER Types Potentially Targeted Therapy (Level of Evidence) Additional References for Targeted Therapy Tyrosine Kinase ALK Fusion NBL Crizotinib, Ceritinib, Alectinib, Lorlatinib cBioPortal F1174L ++ CAD exon23 NBL Crizotinib (B) F1245V CAD exon24 NBL R1275Q/L +++ CAD exon25 NBL NTRK1 TPM3::NTRK1 HGG Larotrectinib (A) NTRK2 Fusion HGG, LGG Larotrectinib (A) NTRK3 ETV6::NTRK3 HGG, LGG Larotrectinib (A) PDGFRA Y288C Exon6 HGG Imatinib, sunitinib, regorafenib and ripretinib cBioPortal E311_E7splice Exon7 HGG N659K ++ PKD exon14 HGG Imatinib, sunitinib, regorafenib and ripretinib cBioPortal D842Y PKD exon18 HGG Avapritinib, Imatinib, Sunitinib cBioPortal ROS1 Fusion OS, HGG Crizotinib, Entrectinib cBioPortal MAPK signaling NF1 Fusion OS, NBL, MB, HGG Trametinib, Cobimetinib cBioPortal Mutation LGG, NBL Selumetinib (B) BRAF KIAA1549::BRAF LGG, PA Selumetinib (B), Sorafenib (C) V600E LGG, HGG, PA, NBL Selumetinib (B), Vemurafenib (B), Dabrafenib (B) KRAS G12D GTPase exon2 LGG, NBL Trametinib, Cobimetinib, Binimetinib cBioPortal NRAS G12S GTPase exon2 HGG Binimetinib, Binimetinib + Ribociclib cBioPortal Q61K ++/R GTPase exon3 RHB, NBL PTPN11 E69K Exon3 NBL, PA A72T/D Exon3 NBL E76A Exon3 NBL, PA Notch signaling NOTCH2 Fusion OS, NBL R5_P6fs Exon1 OS, NBL, RHB P6fs Exon1 NBL, MB, PA, WLM Sonic hedgehog signaling PTCH1 Mutation MB Sonidegib (B) A300fs Exon6 MB Sonidegib, Vismodegib cBioPortal Y804fs Exon15 MB Sonidegib, Vismodegib cBioPortal SMO L412F MB Vismodegib # (C) W535L MB Vismodegib # cBioPortal Wnt signaling CTNNB1 D32 Exon3 MB S33 Exon3 MB G34 Exon3 MB, RHB, ACT, HB S37 Exon3 MB T41A/N Exon3 WLM, MB, RHB N387K ++ Exon8 WLM PI3K signaling PTEN Fusion OS GSK2636771, AZD8186 cBioPortal R130 CAD exon5 HGG R233 * Exon7 HGG PIK3CA R88Q SBD exon2 HGG Alpelisib + Fulvestrant cBioPortal N345K ++ Exon5 MB, RHB, EPD E545K Exon10 HGG Q546K Exon10 HGG, MB E888 * CAD exon18 NBL H1047R/L CAD exon21 HGG, MB, RHB, NBL FGFR1 Fusion LGG Erdafitinib, Infigratinib cBioPortal Internal tandem duplication CAD LGG N546K CAD exon12 LGG, NBL, PA, WLM, HGG Pemigatinib (C) K656E CAD exon14 PA, HGG, WLM Erdafitinib, Infigratinib cBioPortal FGFR4 V550L ++ CAD exon13 RHB EGFR A289V Exon7 HGG Lapatinib cBioPortal TGFB signaling ACVR1 R206H CAD exon6 HGG R258G CAD exon7 HGG G328E/V CAD exon8 HGG G356_E9splice CAD exon9 HGG Cell cycle and DNA repair RB1 Fusion OS W78 * Exon2 OS R320 * Exon10 RB, HGG R445 *+ Exon14 RB R552 * Exon17 RB, OS, HGG R579 * Exon18 RB TP53 Mutation HGG, WLM, OS, MB Vismodegib (C) T125T/R + DBD exon4 HGG, WLM, ACT R175H +++ DBD exon5 HGG, WLM, MB, RHB, ACT C176F DBD exon5 RHB, EWS, NBL R213 *+ DBD exon6 HGG, MB G245S DBD exon7 HGG, MB R248Q/W + DBD exon7 MB, HGG, OS, WLM R273C +/H DBD exon4 HGG, EWS, ACT, MB, OS R282W + DBD exon8 OS, HGG, MB R337H + Exon10 ACT R342 */P Exon10 HGG, WLM CDK1 V124G CAD exon5 MB PPM1D W427 * Exon6 HGG S516 * Exon6 HGG, NBL E525 * Exon6 HGG, MB Transcriptional regulation EWSR1 FLI1::EWSR1 EWS TK216 cBioPortal ERG::EWSR1 EWS BCOR R1164* Exon7 HGG H1481fs Exon11 HGG SIX1 Q177R DBD exon1 WLM MYCN Fusion NBL P44L Exon2 WLM, NBL, MB PAX7 FOXO1::PAX7 RHB PAX3 FOXO1::PAX3 RHB RNA processing DROSHA E1147K Ribonuclease exon29 WLM D1151 Ribonuclease exon29 WLM, NBL DGCR8 E518K RBM exon7 WLM DDX1 DDX1::DDX1 NBL MYCN::DDX1 NBL DDX3X R351W HD exon11 MB M380I HD exon11 MB R534 HD exon14 MB Epigenetics ATRX ATRX::ATRX NBL N294fs Exon9 OS ASXL1 R643fs Exon13 WLM R693 * Exon13 HGG, EPD H3-3A (H3F3A) K28M Exon2 HGG, LGG G35R Exon2 HGG KMT2C T1636P Exon33 MB E2798fs Exon38 MB I4084L Exon48 MB SMARCA4 T910M HD exon19 MB H3C2 (HIST1H3B) K28M ++ Exon1 HGG KDM6A S54_E2splice Exon2 MB R1351 * Exon28 MB IDH1 R132C/H Exon4 MB, HGG, LGG Bevacizumab and Sunitinib (B) R222C/H Exon6 HGG, EWS RELA Fusion EPD, HGG STAG2 R216 * STAG domain exon8 EWS R259 * STAG domain exon9 MB, HGG E1209Q Exon33 OS FLI1 EWSR1::FLI1 EWS ERG EWSR1::ERG EWS + Germline, ++ Relapse, # Reduce treatment activity, * Termination codon. Abbreviations: ACT, adrenocortical carcinoma; CAD, Catalytic domain; ECD, extracellular domain; DBD, DNA binding domain; EPD, ependymoma; EWS, Ewing sarcoma; HB, hepatoblastoma; HD, Helicase domain; HGG, high grade glioma; LGG, low grade glioma; MB, medulloblastoma; NBL, neuroblastoma; OS, osteosarcoma; PA, pilocytic astrocytoma; PKD, Protein kinase domain; RB, retinoblastoma; RBM, RNA binding motif; RHB, rhabdosarcoma; SBD, Substrate binding domain; WLM, Wilms' tumor; Level of evidence: A, validated association; B, clinical evidence; C, case study; D, preclinical evidence; E, inferential association. cancers-15-01418-t005_Table 5 Table 5 Precision study designs for pediatric cancer: Single-arm design. Gene Involved in Trial Design NCT (Recruitment Status) Phase Specification Intervention(s) Cancer Type(s) Eligibility Enrollment (Number) ALK NCT01742286 (D) I ALK alterations Ceritinib ALK-activated Tumors 1-17 years 83 NCT02465528 (C) II ALK alterations Ceritinib Tumors With Aberrations in ALK, Glioblastoma >=18 years 22 NCT02780128 (A) I ALK mutation Ceritinib + Ribociclib Neuroblastoma 1-21 years 131 NCT03107988 (A) I ALK alterations Lorlatinib + Chemotherapy Neuroblastoma >=1 year 65 NCT03194893 (B) III ALK alterations Alectinib or Crizotinib Neoplasms all 200 NCT04774718 (A) I, II ALK fusion Alectinib ALK Fusion-positive Solid or CNS Tumors <=17 years 42 NCT05384626 (A) I, II ALK alterations NVL-655 Solid Tumor, NSCLC >=12 years 214 BRAF NCT01089101 (B) I, II BRAF V600E mutation or BRAF-KIAA1549 fusion Selumetinib Low Grade Glioma, Recurrent Childhood Pilocytic Astrocytoma, Recurrent Neurofibromatosis Type 1 3-21 years 220 NCT01596140 (D) I BRAF mutation Vemurafenib + Everolimus or Temsirolimus Advanced Cancer, Solid Tumor all 27 NCT01636622 (D) I BRAF mutation Vemurafenib + Chemotherapy Advanced Cancers >=12 years 21 NCT01677741 (D) I, II BRAF V600 mutation Dabrafenib Neoplasms, Brain 1-17 years 85 NCT02124772 (D) I, II BRAF V600 mutation Dabrafenib + Trametinib Solid Tumors, neuroblastoma, low grade glioma, neurofibromatosis Type 1 1 month to 17 years 139 NCT02684058 (B) II BRAF V600 mutation Dabrafenib + Trametinib + Radiation Solid Tumors, CNS Tumors, high grade glioma, low grade glioma 1-17 years 149 NCT03919071 (A) II BRAF V600 mutation Dabrafenib + Trametinib + Radiation Anaplastic Astrocytoma, Glioblastoma, Malignant Glioma 1-21 years 58 NCT04576117 (A) III BRAF rearrangement Selumetinib + Chemotherapy Low Grade Astrocytoma, Glioma 2-25 years 18 EGFR NCT00198159 (C) II EGFR expression Gefitinib Refractory Germ Cell Tumors Expressing EGRF >=15 years 21 NCT00418327 (D) I EGFR mutation Erlotinib + Radiation Malignant Brain Tumor, Glioma 1-21 years 48 NCT01182350 (C) II EGFR overexpression Erlotinib + Bevacizumab + Temozolomide + Radiation Diffuse Intrinsic Pontine Glioma 3-18 years 53 NCT01962896 (C) II EGFR/mTOR pathway activation Erlotinib + Sirolimus Relapsed/Recurrent Germ Cell Tumors 1-50 years 4 EWSR1 NCT03709680 (A) II EWSR1-ETS or FUS-ETS rearrangement Palbociclib + Chemotherapy Ewing Sarcoma, Rhabdomyosarcoma, Neuroblastoma, Medulloblastoma, Diffuse Intrinsic Pontine Glioma 2-20 years 184 NCT04129151 (B) II EWSR1 or FUS translocation Palbociclib + Ganitumab Ewing Sarcoma 12-50 years 18 FGFR NCT04083976 (A) II FGFR alteration Erdafitinib Advanced Solid Tumor >=6 years 336 NCT05180825 (A) II FGFR1 and MYB/MYBL1 alterations, 7q34 duplication Trametinib or Vinblastine Grade 1 Glioma, Mixed Glio-neuronal Tumors, Pleomorphic Xanthoastrocytoma 1 month to 25 years 134 H3 NCT02525692 (B) II H3 K27M mutation ONC201 Glioblastoma, Glioma >=16 years 89 NCT03416530 (A) I H3 K27M mutation ONC201 Diffuse Intrinsic Pontine Glioma, Glioma, Malignant 2-18 years 130 NCT05009992 (A) II H3 K27M mutation ONC201 + Paxalisib or Radiation Diffuse Intrinsic Pontine Glioma, Diffuse Midline Glioma, H3 K27M-Mutant 2-39 years 216 IDH NCT03749187 (A) I IDH1/2 mutation PARP Inhibitor BGB-290 + Chemotherapy Glioblastoma, Glioma 13-39 years 78 MYCN NCT02559778 (A) II MYCN amplification Ceritinib, Dasatinib, Sorafenib or Vorinostat + Chemotherapy Neuroblastoma <=22 years 500 NCT03126916 (A) III MYCN amplification Lorlatinib + Standard therapy Ganglioneuroblastoma, Neuroblastoma 1-30 years 658 NF NCT01158651 (D) II NF1 mutation Everolimus Glioma 1-21 years 23 NCT03095248 (A) II NF2 mutation Selumetinib Neurofibromatosis 2, Vestibular Schwannoma, Meningioma, Ependymoma, Glioma 3-45 years 34 NCT03326388 (A) I, II NF1 positive Selumetinib Neurofibromatosis Type 1, Plexiform Neurofibroma, Optic Nerve Glioma 3-18 years 30 NCT03871257 (A) III NF1 positive Selumetinib + Chemotherapy Low Grade Glioma, Neurofibromatosis Type 1, Visual Pathway Glioma 2-21 years 290 NTRK NCT02637687 (A) I, II NTRK-fusion Larotrectinib Solid Tumors Harboring NTRK Fusion <=21 years 155 NCT03834961 (A) II NTRK-fusion Larotrectinib Solid Tumor, CNS Tumor <=30 years 70 NCT04879121 (A) II NTRK amplification Larotrectinib Solid Neoplasm >=16 years 13 PDGFR NCT00417807 (D) I, II PDGFR expression Imatinib Refractory Desmoplastic Small Round Cell Tumors >=16 years 9 NCT03352427 (C) II PDGFR alteration Dasatinib + Everolimus Glioma, High Grade Glioma, Pontine Tumors 1-50 years 3 Rb1 NCT02255461 (C) I Rb1 positive Palbociclib CNS Tumors, Solid Tumors 4-21 years 35 NCT03355794 (B) I Rb1 positive Everolimus + Ribociclib Diffuse Intrinsic Pontine Glioma, Malignant Glioma of Brain, High Grade Glioma, Glioblastoma, Anaplastic Astrocytoma 1-30 years 24 NCT03387020 (D) I Rb1 positive Everolimus + Ribociclib CNS Tumors 1-21 years 22 ALK c-MET ROS NCT00939770 (D) I, II ALK or MET alterations Crizotinib Recurrent Neuroblastoma 1-21 years 122 NCT01524926 (B) II ALK or MET pathway activation Crizotinib Lymphoma, Sarcoma, Rhabdomyosarcoma >=1 year 582 NCT02034981 (B) II ALK, MET or ROS1 alterations Crizotinib Solid Tumors >=1 year 246 NCT02650401 (A) I, II ALK, ROS1, or NTRK1-3 Rearrangements Entrectinib Solid Tumors, CNS Tumors, Neuroblastoma <=18 years 68 NCT03093116 (A) I, II ALK, ROS1, or NTRK1-3 Rearrangements Repotrectinib Solid tumor, CNS tumor >=12 years 500 RAS RAF MEK ERK NF1 NCT02285439 (B) I, II BRAF truncated fusion or NF1 mutation MEK162 Low-Grade Gliomas, Brain, Soft Tissue Neoplasms 1-18 years 105 NCT02639546 (D) I, II RAS/RAF/MEK/ERK pathway activation Cobimetinib Solid Tumors 6 months to 30 years 56 NCT03363217 (A) II BRAF-KIAA1549 fusion, NF1 mutation, MAPK/ERK pathway activation Trametinib Low-grade Glioma, Plexiform Neurofibroma, Central Nervous System Glioma 1 month to 25 years 150 NCT04201457 (A) I, II BRAF V600 mutation or truncated fusion, NF1 mutation Dabrafenib + Trametinib + hydroxychloroquine Low Grade Glioma, High Grade Glioma 1-30 years 75 NCT04216953 (A) I, II MAPK pathway status and Tumor Mutational Burden Cobimetinib + Atezolizumab Sarcoma, Soft Tissue >=6 months 120 SHH WNT NCT00822458 (D) I SHH or WNT signaling activation Vismodegib Recurrent Childhood Medulloblastoma 3-21 years 34 NCT01239316 (D) II SHH signaling activation Vismodegib Recurrent Childhood Medulloblastoma 3-21 years 12 NCT01878617 (A) II SHH or WNT signaling activation Vismodegib + chemotherapy Medulloblastoma 3-39 years 660 Others NCT01396408 (B) II Mutations in sunitinib targets such as VEGFR, PDGFR, KIT, RET or mutations in mTOR pathway such as PTEN, TS1/2, LKB1, NF1/2 Sunitinib or temsirolimus Advanced Rare Tumors >=16 years 137 NCT03654716 (A) I MDM2, MDMX, PPM1D or TET2 amplification ALRN-6924 Solid Tumor, CNS Tumor 1-21 years 69 Recruitment status: (A) Recruiting, (B) Active, not recruiting, (C) Terminated, (D) Completed. cancers-15-01418-t006_Table 6 Table 6 Precision study designs for pediatric cancer: Multiple-arm design. Gene Involved in Trial Design NCT (Recruitment Status) Phase Specification Intervention(s) Cancer Type(s) Eligibility Enrollment (Number) Testing the Use of Food and Drug Administration (FDA)-Approved Drugs (TAPUR) NCT02693535 (A) II ALK, ROS1, MET Crizotinib Advanced Solid Tumors >=12 years 3581 CDKN2A, CDK4, CDK6 Palbociclib or Abemaciclib CSF1R, PDGFR, VEGFR Sunitinib mTOR, TSC Temsirolimus BRAF V600E/D/K/R Vemurafenib and Cobimetinib RET, VEGFR1/2/3, KIT, PDGFRb, RAF-1, BRAF Regorafenib BRCA1/2, ATM Olaparib NRG1 Afatinib BRCA1/2, PALB2 Talazoparib ROS1 fusion Entrectinib NTRK amplification Larotrectinib NCI-COG Pediatric MATCH Screening NCT03155620 (A) II NTRK1, NTRK2, or NTRK3 gene fusion Larotrectinib Refractory or Recurrent Advanced Solid Tumors 1-21 years 2316 FGFR1, FGFR2, FGFR3, or FGFR4 gene mutation Erdafitinib EZH2, SMARCB1, or SMARCA4 gene mutation Tazemetostat TSC1, TSC2, or PI3K/mTOR gene mutation Samotolisib activating MAPK pathway gene mutation Selumetinib ALK or ROS1 gene alteration Ensartinib BRAF V600 gene mutation Vemurafenib ATM, BRCA1, BRCA2, RAD51C, RAD51D mutations Olaparib Rb positive, alterations in cell cycle genes Palbociclib MAPK pathway mutations Ulixertinib HRAS gene alterations Tipifarnib RET activating mutations Selpercatinib TAPISTRY Platform Study NCT04589845 (A) II ROS1 fusion Entrectinib Solid Tumor all 770 NTRK1/2/3 fusion Entrectinib ALK fusion Alectinib AKT1/2/3 mutation Ipatasertib PIK3CA multiple mutation Inavolisib BRAF mutation or fusion-positive Belvarafenib RET fusion-positive Pralsetinib Recruitment status: (A) Recruiting. 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PMC10000496 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050695 cells-12-00695 Article Real-Time Visualization of Cytosolic and Mitochondrial ATP Dynamics in Response to Metabolic Stress in Cultured Cells White Donnell III Conceptualization Methodology Software Validation Investigation Data curation Writing - original draft Writing - review & editing Project administration 123 Lauterboeck Lothar Conceptualization Methodology Software Validation Formal analysis Investigation Resources Data curation Visualization 124 Mobasheran Parnia Methodology Formal analysis 12 Kitaguchi Tetsuya Conceptualization Validation Investigation Resources 5 Chaanine Antoine H. 6 Yang Qinglin Conceptualization Methodology Investigation Resources Data curation Writing - original draft Writing - review & editing Visualization Supervision Project administration Funding acquisition 12* Tiso Natascia Academic Editor 1 Cardiovascular Center of Excellence, Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA 2 Department of Pharmacology and Experimental Therapeutics, School of Graduate Studies, Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA 3 School of Medicine, Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA 4 Cell Biology, Life Science Solutions, Thermo Fisher Scientific, Frederick, MD 21702, USA 5 Laboratory for Chemistry and Life Science, Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8503, Kanagawa, Japan 6 HealthPartners Group, Regions Hospital, Saint Paul, MN 55101, USA * Correspondence: [email protected] 22 2 2023 3 2023 12 5 69528 11 2022 13 2 2023 16 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Adenosine 5' triphosphate (ATP) is the energy currency of life, which is produced in mitochondria (~90%) and cytosol (less than 10%). Real-time effects of metabolic changes on cellular ATP dynamics remain indeterminate. Here we report the design and validation of a genetically encoded fluorescent ATP indicator that allows for real-time, simultaneous visualization of cytosolic and mitochondrial ATP in cultured cells. This dual-ATP indicator, called smacATPi (simultaneous mitochondrial and cytosolic ATP indicator), combines previously described individual cytosolic and mitochondrial ATP indicators. The use of smacATPi can help answer biological questions regarding ATP contents and dynamics in living cells. As expected, 2-deoxyglucose (2-DG, a glycolytic inhibitor) led to substantially decreased cytosolic ATP, and oligomycin (a complex V inhibitor) markedly decreased mitochondrial ATP in cultured HEK293T cells transfected with smacATPi. With the use of smacATPi, we can also observe that 2-DG treatment modestly attenuates mitochondrial ATP and oligomycin reduces cytosolic ATP, indicating the subsequent changes of compartmental ATP. To evaluate the role of ATP/ADP carrier (AAC) in ATP trafficking, we treated HEK293T cells with an AAC inhibitor, Atractyloside (ATR). ATR treatment attenuated cytosolic and mitochondrial ATP in normoxia, suggesting AAC inhibition reduces ADP import from the cytosol to mitochondria and ATP export from mitochondria to cytosol. In HEK293T cells subjected to hypoxia, ATR treatment increased mitochondrial ATP along with decreased cytosolic ATP, implicating that ACC inhibition during hypoxia sustains mitochondrial ATP but may not inhibit the reversed ATP import from the cytosol. Furthermore, both mitochondrial and cytosolic signals decrease when ATR is given in conjunction with 2-DG in hypoxia. Thus, real-time visualization of spatiotemporal ATP dynamics using smacATPi provides novel insights into how cytosolic and mitochondrial ATP signals respond to metabolic changes, providing a better understanding of cellular metabolism in health and disease. mitochondria ATP biosensor fluorescence metabolism National Institute of Health (NIH)R01HL135336 R01HL160969 American Diabetes Association (ADA)#1-17-IBS-184 This work was supported by NIH R01HL135336, R01HL160969 and ADA (#1-17-IBS-184) to Q.Y. pmc1. Introduction ATP is the "energy currency" of all living organisms. Consistent cellular ATP is vital in maintaining and regulating normal mammalian cells. Under typical conditions, mitochondrial oxidative phosphorylation (OXPHOS) produces over 90% of ATP, while cytosolic glycolysis yields the remaining portion. Cellular ATP deficit has been well recognized as a cause of numerous diseases . When cells are proliferating, stressed, or have a limited oxygen supply, glycolysis emerges as the primary source of ATP. This metabolic flexibility serves the purpose of maintaining stable cellular ATP. Under hypoxic conditions, mitochondria consume ATP, presumably from cytosolic glycolysis, to keep the mitochondrial membrane potential through the reverse pumping of ATP synthase with ATP hydrolysis. However, the cytosolic and mitochondrial ATP transportation and dynamics in response to metabolic changes and hypoxia remain obscure. With ATP production and consumption being an essential aspect of understanding the basics of metabolic pathologies, imaging of real-time cytosolic and mitochondrial ATP changes within single cells provides crucial insights into regulatory mechanisms by which cells survive metabolic disturbances. Recent development has shown improvement in ATP imaging technology by utilizing various starting materials, such as small organic indicators, nanoparticles, and fluorescent probes . Numerous methodologies have been developed to visualize ATP in cells using fluorescence resonance energy-transfer-based genetically encoded indicators. These assess ATP dynamics in mitochondria, the cytosol, and the endoplasmic reticulum . Measuring total ATP levels within cellular compartmental pools in real time is a newer and more innovative approach to qualitatively analyzing ATP. This method is semi-quantitative and can help determine changes in ATP concentrations in one region of a cell compared to another in various disease states. The currently developed technologies that utilize this approach to ATP quantification are mainly genetically encoded biosensors . Many of these genetically encoded biosensors are based on the ATP-dependent conformational change of the B. subtilis e subunit . The B. subtilis e subunit is linked with various forms of fluorescent proteins. ATP binding alters the conformation and the environment surrounding the fluorescent protein chromophore , leading to illumination, indicating the presence of ATP. While this strategy has a proven record of success in indicating cellular ATP, it remains unclear if the existence of a B. subtilis e subunit in mammalian cells would interfere with cellular respiration, which may lead to misinterpretation. Furthermore, dual or triple ATP sensors that simultaneously detect ATP in different cellular compartments with a single transfection are desirable to gain in-depth insights into energetic cellular activities. This study demonstrates the feasibility of a novel genetically encoded ATP biosensor that renders the spatiotemporal evaluation of ATP changes in mitochondria and the cytosol. By utilizing this dual ATP biosensor, smacATPi (simultaneous mitochondrial and cytosolic ATP indicator), we explore previously unanswered questions regarding the spatiotemporal ATP transportation and dynamics in response to various metabolic stresses. 2. Materials and Methods 2.1. Design and Validation of an In Vitro Dual-ATP Indicator (smacATPi) Individual ATP indicators that allow for the evaluation of cytosolic and mitochondrial ATP were created by inserting the ATP-binding region of the epsilon subunit of bacterial F1Fo-ATP synthase into the GFP citrine variant and the red fluorescent mApple protein . These single indicators were created by the Kitaguchi lab and were entitled Monitoring ATP Level intensity-based turn-on indications, or MaLions . When ATP binds to the epsilon subunit, the ATP-dependent conformation of the subunit allows for the tertiary formation of the fluorophore to occur, indicating that ATP is present. To evaluate mitochondrial ATP, a mitochondrial signaling sequence (MSS) of the subunit VIII of human cytochrome c oxidase (COXVIII) was added to the red MaLion (MaLionR), and the green MaLion indicates ATP levels in the cytosol (MaLionG). In this study, we designed and validated a dual-fluorophore ATP indicator that monitors cytosolic and mitochondrial ATP in real-time. Our lab combined these two individual indicators previously discussed into one vector, calling this dual indicator system smacATPi (simultaneous mitochondrial and cytosolic ATP indicator). The plasmid we designed contains the two single indicator sequences (hereon called mito-smacATPi and cyto-smacATPi) separated by P2A, a self-cleaving peptide, ensuring proper translation and separation of the fluorophores. 2.2. Generation and Validation of neg-smacATPi Two point mutations were induced in the plasmid at the regions where the proteins are linked. This was done to validate that the fluorescence seen by smacATPi is not due to autofluorescence. Two small mutations were induced into the smacATPi plasmid using the Q5(r) Site-Directed Mutagenesis Kit (New England BioLabs, Ipswich, MA, USA). The recommended website, (accessed on 3 May 2021), was used to design the best primers for SDM (site-directed mutation) deletions to create neg-smacATPi. A 21-nucleotide sequence (5' CAAGGAGGACGGCAACATCCT 3') was designed to be removed from the plasmid region that codes for the citrine protein. Additionally, a 15-nucleotide sequence (5' CGGCGCCCTGAAGAG 3') was designed to be removed from the mApple region of the plasmid. After inducing these deletions within the plasmid, the fluorescent proteins were expected not to maintain their structure and conformation to fluoresce. The primers that induced SDM in the cyto-smacATPi linker region of the plasmid were F: GGGGCACAAGCTGGAGTA and R: AAGTCGATGCCCTTCAGC. The primers used to induce SDM in the mito-smacATPi linker region of the plasmid were F: CGAGATCAAGAAGGGGCTGAG and R: TCCTCGGGGTACATCCGC. The mutations were confirmed via Sanger Sequencing and transfection . 2.3. Cell Culture HEK293T cells were obtained from ATCC. The cells were maintained at 37 degC, 5% CO2 environment, and cultured in Dulbecco's Modified Eagle Medium + Glutamax (Gibco, Billings, MA, USA), supplemented with filtered 10% Fetal Bovine Serum (Atlanta Biologics, Flowery Branch, GA, USA) and 1% penicillin/streptomycin (Gibco, MA, USA). The cells were detached using 0.25% Trypsin-EDTA (1X) (Gibco, MA, USA), and plated in 96-well black/clear bottom plates (Thermo Fisher, Waltham, MA, USA) at a density where the cells reach ~70% for transfection 24 h later. 2.4. HEK293T Cell Transfection Transfection was optimized in HEK293T cells using Fugene 6 transfection reagent (Promega, Madison, WI, USA). HEK293T cells were cultured to a density of ~70% on the day of transfection. Our smacATPi and neg-smacATPi plasmids were transfected into HEK293T cells using Fugene6 transfection reagent (Promega, WI, USA) following the manufacturer's instructions. At 24 h post-transfection, cells were imaged during drug trial runs and analysis. The transfection efficiency of the smacATPi indicator for HEK293T cells was ~80-90%. 2.5. Mouse Embryonic Fibroblast (MEF) Isolation Embryos were harvested from female C57/BJ mice 12.5-14 days after the appearance of the copulation plug. The pregnant female was euthanized according to protocol, then under a sterile hood, cut with scissors to expose the abdominal wall. The uterine horns were cut away from the uterus. The uterus was placed into a petri dish with PBS, and the embryos were removed by slicing through the uterus in the region between each embryo. The embryos were transferred into a new fresh PBS petri dish to remove blood. The head was cut off above the eyes to remove neural tissues. The red tissues were removed, and the embryo was washed again in PBS and placed into Trypsin/EDTA. They were placed into a cell culture incubator for 10 min. The cells were then moved to a conical tube, and MEF medium was added. The cells were allowed to settle, and then the supernatant consisting of single cells and cell clusters was transferred to a 10 cm culture dish. The following morning, the media was replaced. Cells were used for electroporation once they reached confluence. All experimental mouse procedures were approved by the Institutional Animal Care and Use Committee of Louisiana State University Health Science Center-New Orleans. 2.6. Electroporation of MEF Cells Around 200,000 MEF cells were suspended in 300 mL of OptiMem (Gibco, MA, USA) and placed into a 4 mm Gene Pulser cuvette (Bio-Rad, Hercules, CA, USA). The electroporation conditions were: 250 V, two pulses, each 10 ms in length, and 10 s intervals in a 4 mm cuvette. This was done at room temperature with 10 mg smacATPi DNA. After the electroporation, cells were plated in a 96-well plate with growth media for maximum cellular survival. The cells were checked 24 h post-electroporation to determine transfection efficiency. 2.7. Isolation and Culture of Adult Rat Cardiomyocytes (ARCM) Male and female Sprague-Dawley rats weighing 250-300 g are given sodium heparin (200 U, Sigma Aldrich, St. Louis, MO, USA) intraperitoneally. Twenty min later, the animal was anesthetized with 30% isoflurane via a nose cone until breathing cessation. Once the animal was anesthetized (no evidence of reflex with toe pinch), the cervical spine was dislocated, the chest was opened, and the heart was immediately removed and placed into ice-cold PBS (Gibco, MA, USA). The heart was attached quickly to a cannula of a Langendorff apparatus. The heart was perfused with perfusion buffer (Krebs-Henseleit Buffer, KHB) for 4 min and then perfused with a digestion buffer consisting of KHB, collagenase type II, and trypsin. After digested for 15-20 min, the heart was removed from the cannula, the atria were removed, and scissors and forceps were used to cut and shake the ventricles in the digestion solution. After 1-2 min, a stop solution was added to inhibit further digestion. The cardiomyocytes were filtered into a 50 mL tube, and then CaCl2 (Sigma Aldrich, MO, USA) was reintroduced for 20 min. After calcium reintroduction, the cells were re-suspended in growth media and plated for lentivirus transduction on 96-well black/clear bottom plates (Thermo Fisher, MA, USA) plates coated with 40 mg/mL laminin (Invitrogen, Thermo Fisher, USA). All rat procedures were approved by the Institutional Animal Care and Use Committee of Louisiana State University Health Science Center-New Orleans. 2.8. Generation of Adenovirus for smacATPi An adenovirus was made with smacATPi by VectorBuilder (Chicago, IL, USA) to apply this technique in hard-to-transfect cell lines other than HEK293T. To start, 20,000 adult rat cardiomyocytes were seeded onto a 6-well plate coated with 40 mg/mL of laminin (Invitrogen, Thermo Fischer, USA) and incubated at 37 degC and 5% CO2 for one hour to allow adherence of the cells. The adenovirus (200 multiplicity of infection) was added directly to the cell media. The fluorescence intensity of the cells was evaluated every 24 h, and the maximum transduction efficiency was observed 72 h post-infection. 2.9. Drug Selection To investigate cytosolic and mitochondrial ATP dynamics in response to cellular metabolic activation and inhibition, we treated cultured HEK293T cells with metabolic effectors. Various concentrations of the drugs used were tested . 2-Deoxy-d-glucose (2-DG, Sigma Aldrich, MO, USA) is a glycolysis inhibitor, and it was given at a concentration of 25 mm. Oligomycin (Sigma Aldrich, MO, USA), an electron transport chain (ETC) complex V inhibitor, was given at a concentration of 100 mM and decreased the ability of live cells to produce adequate ATP needed for cellular metabolism. To determine how inhibiting the ADP/ATP exchange between cytosol and mitochondria will affect ATP dynamics and trafficking within the cell, we treated cultured HEK293T cells with Atractyloside (ATR, Cayman Chemical, Ann Arbor, MI, USA), an inhibitor of the ATP/ADP carrier within the inner mitochondrial membrane. ATR was given at a concentration of 100 mM, and cell imaging was continuous before and after treatment. These same concentrations were used in hypoxia experiments. Oligomycin stock solution was prepared in ethanol and then diluted in PBS for working solution. 2-DG and ATR were dissolved in water for their respective stock solutions, then diluted in PBS for their final drug concentrations. 2.10. Evaluation of Mitochondrial Membrane Potential Tetramethylrhodamine (TMRM), a mitochondrial membrane potential indicator, was used alone and in conjunction with certain drugs to evaluate their effects on the membrane potential. The cells were plated at a density of 30,000 cells per well in a 96-well plate and allowed to grow overnight until ~90% confluency. A concentration of 50 nm TMRM (Image-IT TMRM Reagent, Thermo Fischer Scientific, Waltham, MA, USA) was added to each well, and the plate was incubated in the dark for 30 min. The Cytation5 Cell Imaging Multi-Mode Reader (BioTek, Winooski, VA, USA) was used to monitor the mitochondrial membrane potential in both hypoxic and normoxic environments to validate that the conditions within Cytation5 are hypoxic . In order to confirm that TMRM was working correctly, FCCP (15 mM) was used to verify that mitochondrial membrane depolarization shows a decrease in TMRM fluorescence. Our chosen drugs (ATR and 2-DG) were used to investigate the mitochondrial membrane potential after drug administration. TMRM has an absorbance peak of 584 nm, and its emission peak is 574 nm. Imaging conditions were the same as culture conditions, as they were maintained at normoxia at 37 degC in 5% CO2, or hypoxia at 37 degC, 2% O2, and 5% CO2. 2.11. Evaluation of Mitochondrial pH Change A mito-pH indicator was used to investigate mitochondrial pH fluctuations that may interact with our biosensor sensitivity. The pH indicator used was GW1-Mito-pHRed, a gift from Gary Yellen via Addgene (Addgene plasmid #31474, accessed 6 June 2022). A control experiment in normoxia was run post-transfection of HEK293T cells with mito-pH tracker for 2 h, and then an additional run was run in hypoxic conditions for the same time . 2.12. Image Acquisition The transfected cells were imaged using Cytation5 Cell Imaging Multi-Mode Reader (BioTek, VA, USA). Images and cell runs were recorded at 20x magnification. Imaging conditions were the same as culture conditions, maintained at 37 degC with 5% CO2 unless hypoxic conditions were implemented. For green fluorescence, the wavelength used was 488 nm, red was 650 nm, and blue was 461 nm. Supplemental movies are provided, allowing for visualization of real-time change over time. Surface plots were obtained by converting raw fluorescent images into 8-bit, applying FIRE LUT colorization, and then plotting these converted images in ImageJ (National Institutes of Health, Bethesda, MD, USA). 2.13. Hypoxic Conditions for HEK293T Cells For hypoxia experiments, HEK293T cells were allowed to incubate and were imaged using Cytation5 Cell Imaging Multi-Mode Reader (BioTek, VA, USA) with an environment of 5% CO2, 93% N2, and 2% O2. 2.14. Statistical Analysis The collected image stacks were obtained from Cytation5 Cell Imaging Multi-Mode Reader (BioTek, VA, USA), and imaging analysis was done via software within Cytation5 to analyze and extract fluorescent data. The total intensities were taken from 20x imaging fields of each 96-well, as the variability between cells is too great to measure individually. Each cell field contains a minimum of 10 cells for analysis, and each drug trial/control was done 3-9 times. Therefore, 30-90 cells were analyzed for each experiment. Raw fluorescence intensity values for each run are shown in Figure S5. Change in fluorescence was determined as a ratio of fluorescence intensity over time (F/F0). Each drug trial was normalized to its respective PBS vehicle control. Hypoxia experiments were normalized to the 4-h normoxia control in conjunction with mito-pH to account for both fluorescent variability and pH changes . The normalized F/F0 values were plotted with GraphPad Prism 9 statistical software (La Jolla, CA, USA). The endpoint/initial fluorescent intensities were also determined and indicated in bar graphs. All data points on graphs are expressed as mean +- SEM. An unpaired t-test was done to determine a significant difference between the end fluorescent value and the initial value in the fluorescent bar graphs, and 2-way ANOVA was done for experiments with three or more variables. The highlighted portions of the graphs indicate the standard errors of the mean. p-value indicators are as follows: ns = p > 0.05, * = p <= 0.05, ** = p <= 0.01, *** = p <= 0.001, and **** = p <= 0.0001. 3. Results 3.1. Design, Generation, and Validation of smacATPi (Simultaneous Mitochondrial and Cytosolic ATP Indicator) To spatiotemporally visualize cytosolic and mitochondrial ATP dynamics simultaneously within a single cell with a single transfection, we generated a fluorescence-based dual-ATP indicator called simultaneous mitochondrial and cytosolic ATP indicator, hereon called smacATPi. We designed this biosensor by combining two previously described cytosolic and mitochondrial ATP indicators, previously named MaLionG and mitoMaLionR , which, respectively, fused the ATP-binding region of the e subunit of F1Fo-ATP synthase (B. subtilis) with green fluorescent protein (GFP) Citrine variant and mApple. A mitochondrial targeting sequence (MTS) from COX II was included in the mitoMaLionR for mitochondrial targeting . These two fusion proteins were cloned into a single plasmid separated by a short P2A self-cleaving peptide, ensuring the appropriate separation of the proteins . Once bound to ATP, the protein undergoes a conformational change and emits fluorescence . When the above plasmid is transfected in cultured cells, the ATP indicators become localized to the cytosol and mitochondria with different colors (green and red, respectively) . Furthermore, the co-expression of both proteins is high, as out of all transfected cells, 85% are co-transfected, 88% express cyto-smacATPi, and 96% express mito-smacATPi . The smacATPi were transfected in cultured HEK293T, adult rat cardiomyocytes, and mouse embryonic fibroblasts. Fluorescent imaging validated that dynamic cytosolic and mitochondrial ATP signals were green and red colors within the respective cellular compartments in both cell types . These results validate the feasibility and utility of smacATPi in proliferative and post-differentiated cells. HEK293T cells and adult rat cardiomyocytes with smacATPi expression are broadly comparable to those without smacATPi expression in their growth, morphology, and cell survival. To ascertain that smacATPi expression does not interfere with basal cellular metabolism, we conducted a Cell Mito Stress Test on cultured HEK293T cells using an Extracellular Flux Analyzer (Seahorse, XFe24, Agilent, Santa Clara, CA, USA) to assess critical mitochondrial function . Cultured HEK293T cells with smacATPi expression did not perturb mitochondrial function. Basal respiration (oxygen consumption rate), ATP production, maximal respiration, spare capacity, coupling efficiency, non-mitochondrial oxygen consumption, and protein leak were unchanged . Furthermore, as previously described, a plasmid containing a mutated form of the fluorescent proteins was used to exclude the possibility that the red and green fluorescent signals are derived from autofluorescence. We confirmed that the mutated form of the indicator showed no fluorescence . 3.2. Cytosolic and Mitochondrial ATP Dynamics and Trafficking in Response to Glycolytic and Mitochondrial Inhibitions under Normoxic Conditions To define how mitochondrial and cytosolic ATP production processes adapt within cells for optimal function and survival, we treated cultured HEK293T cells with drugs that inhibit cytosolic glycolysis and mitochondrial ATP synthesis by investigating how ATP dynamics change in real time. Real-time fluorescent changes were recorded to monitor the flux of dynamic ATP signals in cytosol and mitochondria. The changes in fluorescent intensity of cyto-smacATPi and mito-smacATPi in cultured HEK293T cells treated with the inhibitors were normalized to a PBS vehicle control . The drugs used were 2-deoxyglucose (2-DG), a glycolysis inhibitor, and oligomycin, a complex V inhibitor . When treated with 2-deoxyglucose (2-DG), cytosolic ATP signals were significantly decreased within 15 min and plateaued at 30 min post-injection . After normalization to the PBS vehicle control, cytosolic ATP signal decline post-2-DG treatment was substantial, dropping by 30% . Additionally, there was also a decrease seen in mitochondrial ATP post-2-DG administration . When treated with oligomycin (100 mM), an ATP synthase (complex V) inhibitor, mitochondrial ATP declined by around 10%. After normalization, the cytosolic ATP signal increased post-oligomycin by 10% . The increase in cyto-smacATPi indicates a compensatory increase in glycolysis to compensate for mitochondrial ATP levels being suboptimal post-oligo administration. These results demonstrate how smacATPi monitors real-time ATP change in two crucial cellular compartments of ATP production and consumption. 3.3. ATP Regulation and Cellular Response in Hypoxia Utilizing this novel technique, we further investigated a long-puzzling question in the field to investigate cellular ATP distribution in cells under hypoxic conditions and whether reversed ATP transportation is occurring via ADP/ATP Carrier (AAC). AAC is located in the inner mitochondrial membrane and allows for the exchange of free ATP and ADP across the inner mitochondrial membrane . Cytosolic-free ADP is transported via the intermembrane space to the mitochondrial matrix. In contrast, ATP produced from OXPHOS is transported from the mitochondrial matrix to the intermembrane space, then to the cytoplasm via voltage-dependent anion channel 1 (VDAC1) . Under hypoxic conditions, cytosolic glycolysis is upregulated to generate ATP, and cytosolic ATP is thought to reverse-transfer to mitochondrial matrix, while further being hydrolyzed by F1Fo-ATP synthase to pump proton back to the mitochondrial intermembrane to maintain membrane potential and prevent cell death . We first tested the effects of AAC inhibition in cultured HEK293T cells under normoxia. Atractyloside (ATR) is a glycoside inhibiting ADP and ATP exchange . After normalization, it was seen that ATR treatment in normoxic conditions attenuated both cytosolic and mitochondrial ATP signals in cultured HEK293T cells . These results indicate that although there is inhibition of ADP/ATP exchange between the cytosol and mitochondrial compartments, the mitochondrial production does not waiver. Next, we investigate how cellular ATP changes under hypoxic conditions to determine how energy balance is maintained in the mitochondria and cytosol compartments under hypoxia conditions. HEK293T cells were imaged in hypoxia using a Cytation5 Cell Imaging Multi-Mode Reader (BioTek, VA, US) with 5% CO2 and 2% O2. Each hypoxic treatment was conducted for 4 h, and a normoxic control run was used to normalize hypoxia experiments . The MaLion indicators were selected, showing minimal fluorescent damping due to the hypoxia-related intracellular acidity . To further evaluate the effects of pH due to hypoxia on fluorescent variability, a mito-pHRed indicator was used to determine if pH played a role in the fluorescent sensitivity . After normalization to the normoxic mito-pH, pH showed negligible effects on smacATPi fluorescence . When smacATPi-expressing cells were subjected to hypoxia, mitochondrial ATP signal was profoundly increased (40%) with cytosolic ATP downregulation (25%) . Furthermore, mitochondrial potential decreased in hypoxia conditions, ensuring that the cells were experiencing hypoxic effects . For hypoxia experiments with drug administration, the cells were allowed to acclimate to the hypoxic environment for 2 h before drug administration, then were monitored for another 2 h . Atractyloside (ATR) (100 mM) was administered to cells 2 h post-hypoxia exposure . The ATR-treated cells in hypoxia showed no statistical difference in mitochondrial ATP levels compared to hypoxia alone . However, after ATR treatment, the decline of cytosolic ATP was reversed and remained at similar levels prior to the initiation of hypoxia, suggesting that ATP transport is not necessarily mediated by AAC in similar situations . The effects of combination therapy, ATR and 2-DG, were also evaluated in hypoxia. In the same way as the previous experiment, ATR (100 mM) and 2-DG (25 mm) were administered to the cells 2 h after initiation of hypoxia exposure . Four hours after hypoxia initiation, mitochondrial ATP levels dropped, leveling out around initial baseline levels . The addition of 2-DG caused a decrease in cytosolic ATP compared to ATR only, yet slightly higher than hypoxia alone. However, this was not significant compared to either . 4. Discussion ATP is a molecule involved in energy storage and transport within cells. Direct monitoring of cellular ATP distribution dynamics is highly desired, to help better understand the biochemical mechanisms underpinning cellular function in both standard and diseased states. In this report, we demonstrate the feasibility and utilization of a novel fluorescence-based genetic indicator of ATP, simultaneously monitoring real-time ATP changes in the cytosol and mitochondrial compartments of cells. 4.1. Feasibility of the Dual ATP Indicator for Real-Time ATP Visualization within the Cytosol and Mitochondria of Cultured Cells Our current understanding of ATP status in different cellular compartments is mainly based on indirect measurement of ATP on homogenates of cells and tissues using luciferase-based chemiluminescent assays, liquid chromatography, imaging phosphorous-31 (31P) (MRS/MRI), mass spectrometry, or magnesium green . These assays are effective in quantitatively measuring total ATP in samples, but not for visualization of compartmental ATP changes in real time within an individual living cell. Luciferase-based ATP imaging has been developed and is feasible for visualizing cellular ATP . However, this technique is unsuitable for hypoxia-related investigations because the Luciferase-based reaction requires O2. Genetically encoded biosensors are a relatively inexpensive approach to providing direct visualization of ATP changes . Numerous fluorescent ATP indicators have been developed . However, these techniques often suffer from high signal-to-noise ratios or require specialized equipment to determine the spatiotemporal dynamics of ATP within cells (see review ). MaLions are intensiometric biosensors that fluoresce brighter as more ATP is bound and have been designed to target specific cellular organelles, thus making ATP levels visible across multiple compartments . In the current study, we test the feasibility of a dual ATP indicator to visualize ATP in the cytosolic and mitochondrial compartments of cultured cells. Our results further support the feasibility of revealing mitochondrial and cytosolic ATP abundances and dynamic changes using fluorescent biosensors. Moreover, we further modified these sensors and packed them into a single transfection vector with high efficiency for the expression in both proliferative and differentiated cells, such as HEK293T, MEF, and rat adult cardiomyocytes. The majority of transfected cells (85%) co-express our dual-indicators, while 15% of cells are expressing one (11% mito-smacATPi only and 4% cyto-smacATPi only) . This is somewhat of a limitation, although the fluorescent trends seen via each indicator should remain representative of the biological actions occurring. More importantly, we excluded potential non-specific metabolic and growth effects on cells with high-level expression of the smacATPi. Additionally, ATP signals we observe in HEK293T cells are independent of off-target or background effects of smacATPi expression. Therefore, results from this study support the feasibility of the dual ATP indicator for the study of spatiotemporal dynamics of ATP in cytosol and mitochondria of cultured cells. 4.2. Real-Time Spatiotemporal Cellular ATP Dynamics in the Presence of Mitochondrial and Metabolic Inhibitors Due to the constraints of currently available and affordable technology, the real-time effects of metabolic changes on cellular ATP dynamics remain ill-defined. The use of smacATPi may help solve some of these puzzles. We here demonstrated how cytosolic and mitochondrial ATP are altered in response to inhibitors of cytosolic glycolysis and mitochondrial ATP synthesis, at least in cultured HEK293T cells. Cytosolic ATP dramatically plummeted as expected in response to 2-DG under normoxic conditions. Interestingly, mitochondrial ATP also decreased by about 15%, suggesting that the inhibition of cytosolic glycolysis limits pyruvate production and its further oxidation in mitochondria. Additionally, our discoveries show that seemingly high concentrations of drugs are required to produce a response, which might be due to the instrumentation used or the sensitivity of smacATPi. Consequently, mitochondrial ATP becomes the primary but declined ATP source. As expected, mitochondrial ATP decreased significantly under oligomycin treatment. These results suggest that glycolytic activity in the cytosol may be increased to produce ATP that replenishes the mitochondrial pool via reversed transportation, as previously proposed . These results indicate that ATP pools within these two cellular compartments are tightly coordinated, potentially via cross-compartment trafficking. 4.3. ATP Regulation under Hypoxic Conditions Oxygen is an essential element in OXPHOS . Hypoxia triggers dramatic cellular reprogramming to gain ATP and maintain metabolic function and survival . Hypoxia increases glycolytic ATP production via the enzymatic activity of phosphofructokinase-1 and pyruvate kinase. When oxygen concentrations are low for extended amounts of time, cells activate hypoxia-inducible factors (HIFs) , which bind to hypoxia-responsive elements (HREs), activating gene transcription of glycolysis . However, exact changes in ATP dynamic and trafficking in real time between the cytosol and mitochondria in cells subjected to hypoxia remain vague . Real-time evaluation of ATP dynamics in hypoxic conditions can help further define how the upregulation of cytosolic glycolysis maintains cell survival in hypoxia. Our finding is unexpected in that mitochondrial ATP increases and cytosolic ATP decreases in cells subjected to hypoxia. It appears that under hypoxic conditions, cells are highly adaptive and prioritize sustaining and increasing the mitochondrial ATP content, at least during the initiated two-hour window. This may occur via reverse transportation from the cytosolic ATP pool . This observation appears to support the conclusions from early studies based on mitochondrial membrane potential changes suggesting that mitochondria become ATP consumers under hypoxic conditions . Cytosolic ATP enters mitochondria, where complex V hydrolyzes ATP to reversely pump proton from the matrix to the intermembrane space, preventing the membrane potential collapse and the subsequent cell death. However, it remains a mystery how the cytosolic ATP is imported from the cytosol to the mitochondria. It is well-recognized that the ATP/ADP carrier (AAC) is critical in transferring ADP to mitochondria for ATP synthesis and ensuring that the cytosol receives adequate ATP from mitochondria to supply energy to the rest of the cell . In the IMM, AAC is responsible for the uniport-style shuttling of ATP from the mitochondrial matrix to the intermembrane space and ADP from the intermembrane space to the mitochondrial matrix . When inhibited, the carrier protein can no longer transport ADP/ATP appropriately. Atractyloside (ATR), a toxic glycoside, locks AAC in the c-state, where the substrate-binding site is accessible to the intermembrane space . This inhibition allows ADP to enter the carrier protein and bind but does not allow for its transportation into the matrix from the cytosol . Our results show that ATR treatment in normoxic cells attenuates mitochondrial and, to a less extent, cytosolic ATP, suggesting that ATR-related inhibition contributes to mitochondrial ATP decline . Our finding largely supports the previously proposed equimolar ADP-ATP exchange model . Inhibition of AAC may increase cytosolic [ADP] and activate glycolysis, leading to slightly elevated cytosolic ATP. We unexpectedly found that cells in hypoxia showed elevated mitochondrial ATP and decreased cytosolic ATP. We suspect that hypoxia triggers the reversed ATP transportation into mitochondria, at least at the initial stage. The exact pathways mediating the reverse ATP transportation remain elusive. It has been suggested that AAC could reversely translocate ATP from the cytosol to mitochondria in hypoxia to sustain mitochondrial membrane potential via proton replenishing from the matrix, driven by ATP synthase-mediated ATP hydrolysis . However, the treatment of ATR to inhibit AAC seems to exert little effect on mitochondrial ATP but slightly increased cytosolic ATP in hypoxia, suggesting that ATP may be derived more from the upregulated cytosolic glycolysis and somehow replenish the mitochondria via AAC-independent mechanisms. When 2-DG was added in addition to ATR in hypoxia, the cytosolic rescue seen with ATR alone was gone, leaving cytosolic values lower. Interestingly, the addition of 2-DG decreased the hypoxic-induced mitochondrial ATP increase, thus bringing the mitochondrial ATP levels down to baseline. This is probably due to glycolysis inhibition--the primary ATP source in hypoxia. Without this additional ATP source, the mitochondrial ATP stores cannot be "rescued". A recent study on mitochondrial assessment suggests that mitochondrial import of glycolytic ATP is independent of AAC, at least in cultured cancer cells . However, results from the current investigation suggest that AAC at least partially mediated the reversed ATP transportation. Other AAC-independent pathways should also contribute to the reversed ATP transportation in hypoxia. Further studies are required to identify these pathways. The use of our novel dual ATP biosensor should help facilitate the exploration. 5. Conclusions In summary, our study demonstrates that smacATPi allows spatiotemporal recording of ATP dynamics simultaneously in mitochondria and cytosol of cultured cells, enabling real-time monitoring of cellular ATP dynamics in cytosol and mitochondria in response to metabolic changes under normoxia and hypoxia. This innovative technology will enable in-depth investigations to define cellular energetic regulations and gain further mechanistic insights into cellular energy metabolism in health and disease. Supplementary Materials The following supporting information can be downloaded at: Figure S1: A mutated form of smacATPi (neg-smacATPi), where small deletions were introduced into the linker regions of the fluorescent proteins to exclude the possibility that the fluorescent signals are derived from autofluorescence. The rate of efficiency for co-transfection of both smacATPi indicators (mito and cyto) is high; Figure S2: Mitochondrial membrane potential assays in HEK293T cells subjected to hypoxia; Figure S3: Mitochondrial pH changes during hypoxia; Figure S4: ATP movement between mitochondria and cytosol under normoxic and hypoxic conditions in the presence of ATR; Figure S5: Raw fluorescent intensities from Cytation5; Movie S1: A vehicle control (PBS) was added to cells for normalization of drug trials; Movie S2: 2DG was added to smacATPi-expressing HEK293T cells; Movie S3: smacATPi-expressing HEK293T cells were treated with Oligomycin; Movie S4: ATR was added to smacATPi-expressing HEK293T cells; Movie S5: A control 4-hour run was done for normalization of hypoxic conditions; Movie S6: smacATPi-expressing HEK293T cells were subjected to 4-h of hypoxic conditions (5% CO2 and 2% O2); Movie S7: ATR was added to smacATPi-expressing HEK293T cells 2 h post-exposure to hypoxic conditions (5% CO2 and 2% O2) Click here for additional data file. Author Contributions Conceptualization, D.W.III, L.L., T.K. and Q.Y.; methodology, D.W.III, L.L. and A.H.C.; software, L.L. and D.W.III; validation, D.W.III, P.M. and T.K.; formal analysis, D.W.III and P.M.; investigation, D.W.III, L.L., T.K. and Q.Y.; resources, D.W.III; data curation, D.W.III and P.M.; writing--original draft preparation, D.W.III and Q.Y.; writing--review and editing, D.W.III and Q.Y.; visualization, D.W.III; supervision, Q.Y.; project administration, D.W.III and Q.Y.; funding acquisition, Q.Y. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data can be made available via contacting corresponding author. Conflicts of Interest The authors declare no conflict of interest. Abbreviations 2-DG 2-Deoxy-D-glucose AA Antimycin A ADP Adenosine diphosphate ATP Adenosine triphosphate ATR Atractyloside FBS Fetal bovine serum IMM Inner mitochondrial membrane OCR Oxygen consumption rate OMM Outer mitochondrial membrane OXPHOS Oxidative phosphorylation PBS Phosphate buffered saline smacATPi simultaneous mitochondrial and cytosolic ATP indicator VDAC1 voltage-dependent anion channel 1 Figure 1 Dual-ATP indicator (smacATPi) design, testing, and confirmation of viability. (A) The simultaneous mitochondrial and cytosolic ATP indicator (smacATPi) was initially based on the previously described individual cytosolic (cyto-smacATPi) and mitochondrial (mito-smacATPi) ATP indicators, with a mitochondrial signaling sequence (MS) included for mitochondrial localization. smacATPi contains the polycistronic arrangement of sequences coding for these two MaLion fluorescent fusion proteins, along with a P2A region allowing for proper protein cleavage. (B) When smacATPi is expressed, the cytosolic indicator (cyto-smacATPi) indicates cytosolic ATP. (C) The mitochondrial indicator (mito-smacATPi) indicates mitochondrial-specific ATP. (D) When the indicators' fluorescence is overlapped in living cells, ATP production and dynamic flux can be evaluated between both cellular compartments in vitro. (E) ATP binds to the epsilon subunit of F1Fo-ATP synthase, triggering a conformational change in the connected protein, causing fluorescence. (F) The two indicators expressed from a single vector allow for the dual-compartmental visualization of ATP. (G,H) Representative images of ATP in adult rat cardiomyocytes (ARCM) and in mouse embryonic fibroblasts (MEF). Figure 2 The expression of smacATPi does not interfere with cellular respiration. (A) Cellular bioenergetics was assessed in HEK293T cells with smacATPi expression. The oxygen consumption rate (OCR) of the cells transfected with smacATPi showed no change compared to non-transfected cells, indicating no adverse effects of smacATPi on cellular metabolism. (A) Overall OCR in response to inhibitors of oxidative phosphorylation. (B) Basal respiration (OCR) rate. (C) ATP-linked respiration (ATP production rate). (D) Maximal respiration. (E) Spare respiratory capacity. (F) Coupling efficiency. (G) Non-mitochondrial oxygen consumption. (H) Proton leak respiration. No change of the above parameters between the non-transfected HEK293T cells and those transfected with smacATPi could be detected (n > 6; error bars are SEM). Figure 3 Spatiotemporal ATP dynamics in mitochondria and cytosol can be evaluated in real time using smacATPi after treatment with glycolytic and ATP synthase inhibitors. (A) Illustration of the inhibitory effect of 2-deoxyglucose (2-DG) on glycolysis in the cytosol and oligomycin on Complex V of the electron transport chain within the inner mitochondrial membrane. (B,C) The effect of 2-DG on the fluorescent intensity of ATP in mitochondria (red) and cytosol (green) on cultured HEK293T cells was graphed over time, post-drug administration. (C) Maximal changes of mitochondrial and cytosolic fluorescent intensity in response to 2-DG treatment. (D-K) The HEK293T cell images are from a respective 25 mm 2-DG drug treatment experimental run. The image below each fluorescent image is a FIRE LUT version of the respective image, allowing for the investigation of pixel intensity via surface plot. (L,M) Oligomycin (100 mM) was also used to inhibit mitochondrial ATP production in the HEK293T cells. (N) The fluorescent intensity was plotted over time and normalized to PBS treatment (n = 3 or more fields, with 30-90 cells analyzed in total; error bars are SEM; * p <= 0.05, *** p <= 0.001). Figure 4 Effects of ADP/ATP Carrier (AAC) inhibition on spatiotemporal ATP dynamics in cultured HEK293T cells under normoxic and hypoxic conditions. (A) Under normoxic conditions, AAC facilitates the movement of ATP out of the matrix, while also bringing ADP to feed the ATP synthesis. (B,C) smacATPi-transfected HEK293T cells were treated with atractyloside (ATR), an AAC inhibitor, under normoxia. (D) A 4-h normoxic control run was used to normalize the hypoxia cell runs. (E) The protocol for hypoxia experiments involves 2 h of hypoxia exposure (2% O2, 5% CO2), drug administration, then an additional 2 h in hypoxia. (F) The previously proposed function of AAC in the reverse ATP transportation in hypoxia. (G,H) smacATPi-transfected cells were subjected to 4 h of hypoxia. 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PMC10000497 | (1) Background: Mild hyperthermia (mHT, 39-42 degC) is a potent cancer treatment modality when delivered in conjunction with radiotherapy. mHT triggers a series of therapeutically relevant biological mechanisms, e.g., it can act as a radiosensitizer by improving tumor oxygenation, the latter generally believed to be the commensurate result of increased blood flow, and it can positively modulate protective anticancer immune responses. However, the extent and kinetics of tumor blood flow (TBF) changes and tumor oxygenation are variable during and after the application of mHT. The interpretation of these spatiotemporal heterogeneities is currently not yet fully clarified. (2) Aim and methods: We have undertaken a systematic literature review and herein provide a comprehensive insight into the potential impact of mHT on the clinical benefits of therapeutic modalities such as immuno-therapy. (3) Results: mHT-induced increases in TBF are multifactorial and differ both spatially and with time. In the short term, changes are preferentially caused by vasodilation of co-opted vessels and of upstream normal tissue vessels as well as by improved hemorheology. Sustained TBF increases are thought to result from a drastic reduction of interstitial pressure, thus restoring adequate perfusion pressures and/or HIF- VEGF-mediated activation of angiogenesis. The enhanced oxygenation is not only the result of mHT-increased TBF and, thus, oxygen availability but also of heat-induced higher O2 diffusivities, heat-related enhanced O2 unloading from red blood cells. (4) Conclusions: Enhancement of tumor oxygenation achieved by mHT cannot be fully explained by TBF changes alone. Instead, a series of additional, complexly linked physiological mechanisms are crucial for enhancing tumor oxygenation, almost doubling the initial O2 tensions in tumors. radio-oncology mild hyperthermia immuno-oncology enhanced tumor blood flow improved tumor oxygenation physiological responses transient changes sustained effects pleiotropic hyperthermia effects This research received no external funding. pmc1. Introduction Physiological responses of malignant tumors upon mild hyperthermia (mHT, i.e., therapeutically heating malignant tumors at a (preferred) temperature range of 39-42 degC for 30-60 min ) have been reviewed during the last two decades with different focuses and perspectives (e.g., ). Preclinical hyperthermia (HT) studies published since the late 1970s and into the early 1980s are unfortunately limited in terms of their relevance for the clinical setting, e.g., due to the (i) use of impractical heating techniques, (ii) tissue temperature levels >43 degC (combined with long exposure times) which are cytotoxic per se and not achievable in clinical settings, (iii) bulky, fast-growing rodent tumors exhibiting very low blood flow rates do not reflect the clinical situation, (iv) incorrect and misguided conclusions from in vitro experiments, and (v) incorrect and misguided interpretation of biological responses upon mHT . As a multifaceted adjuvant cancer treatment modality, mHT triggers a series of therapeutically relevant biological mechanisms at this temperature level without direct cytotoxicity. Localized mHT is usually administered as an adjuvant modality to primarily improve the therapeutic efficacy of "concurrent" /or chemotherapy and in heavily pretreated patients with recurrent cancers . Delivered within a close time frame before external radiation (RT) and/or chemotherapy (CT), mHT has unequivocally shown distinct beneficial effects in numerous clinical studies (e.g., ). mHT is a proven potent chemosensitizer exerting pleiotropic effects in solid tumors. mHT can be considered as a "general sensitizer" to therapeutic modalities and is a strong modulator of the anticancer immune system:Hyperthermic radio-sensitization: This condition is generally believed to be the result of a "physiological vasodilation", which increases tumor blood flow ("reperfusion"), and oxygen levels ("reoxygenation"), occasionally lasting up to 24-48 h post-HT . Hyperthermia enhances cytotoxicity of anticancer drugs: Besides direct sensitization to a series of anticancer agents (e.g., Cisplatin, Carboplatin, Oxaliplatin, Bleomycin, Doxorubicin), HT can improve the blood-borne delivery (via an increase in heat-induced tumor perfusion and/or a homogenization of blood flow), and enhanced extravasation in the leaky microvasculature of malignant tumors or a temperature-triggered drug release from thermo-sensitive liposomes for localized thermo-chemotherapy. Hyperthermia inhibits DNA repair enzymes: In the upper range of mHT (41-43 degC), several DNA damage repair enzymes responsible for the repair of potentially lethal or sublethal DNA damage have been reported, thus increasing the efficacy of radiotherapy and some chemotherapeutic drugs . Hyperthermia affects radio-immuno-oncology: It is known that hypoxia compromises anticancer immune responses such as reducing the survival, cytolytic, and migratory activity of key effector cells such as natural killer (NK) cells and NK-like T cells, as well as CD4+ helper and CD8+ cytotoxic T cells, reduces the production of essential "effector" cytokines, as well as fostering an immunosuppressive environment by supporting immunoregulatory Treg cells, myeloid-derived suppressor cells (MDSCs) and inducing the expression of immune checkpoint inhibitors (reviewed in ). HT-induced improvements of tumor oxygenation status ("reversal of tumor hypoxia") and the increased perfusion triggered by mild HT enhances the trafficking of immune cells, and intra-tumoral access to crucial immune regulators such as antibodies and cytokines, all of which are needed to generate effective antitumor immune responses. Hyperthermia is also known to be an effective immune modulator that has multiple effects on the innate and adaptive immune systems (reviewed in ). Hyperthermia and the innate immune system: With respect to the innate immune system, hyperthermia increases the expression of activation receptors such as NKG2D and MHC class I-related chain A (MICA) on the surface of natural killer (NK) cells, thereby enhancing their antitumor potential . This is confirmed by findings that NK cells are important mediators of antitumor immunity after radiotherapy and hyperthermia and that cells of the innate immune system in patients recover faster when hyperthermia and radio-chemotherapy are combined . Hyperthermia and the adaptive immune system: With regards to the adaptive immune system, hyperthermia influences all aspects of adaptive antitumor immunity, from the function and antigen presentation capacity of antigen-presenting cells (APCs) to the responsiveness of CD4+ and CD8+ T-cell populations . Combining hyperthermia with radiotherapy promotes the infiltration of dendritic cells--crucial antigen-presenting cells and initiators of adaptive immune cells--into solid tumors , as well as inducing the maturation of DCs and the release of pro-inflammatory cytokines from DCs and macrophages . In addition to direct effects on cellular immunity, combining hyperthermia and radiotherapy has also been shown to mediate immune effects via multiple mechanisms, including the release of Danger Associated Molecular Pattern (DAMP) signals such as heat shock proteins (HSPs) and HMGB1 . Taken together, these findings and observations demonstrate and support the concept that combining hyperthermia, radiotherapy and immunotherapy with next-generation cellular and antibody-based approaches such as checkpoint inhibition has great therapeutic potential. However, before this approach can be fully exploited, it is crucial to fully understand the physiological consequences of hyperthermia on the tumor microenvironment and identify the optimal doses for achieving the optimal therapeutic conditions. Based on experimental preclinical and clinical data, it is often concluded that heat-induced increases in TBF are the principal (or even exclusive) drivers of concurrent ("secondary") changes in the oxygenation status and are principally involved in most of the heat-induced sensitizing mechanisms described above. However, when analyzing the heat-induced changes of tumor blood flow in more detail, it is evident that there are some enigmas (or even deficits) in the interpretation of the results, especially with respect to (i) the genesis of HT-induced flow increases, and (ii) the interpretation of "exclusively flow-related enhancements" of tumor oxygenation status. A more detailed analysis of the functional background clearly shows that mHT-induced secondary effects cannot be fully explained by blood flow improvements alone. Instead, these effects are the result of complex interactions of a multitude of processes. Furthermore, partly dependent on hyperthermia levels and durations, inconsistent directions, as well as highly variable individual extents and kinetics of blood flow changes upon mHT, have also to be considered. In addition, taking into account the pathogenesis-related classification and different timeframes of tumor hypoxia , it is rather unlikely that enhancements of the oxygenation status upon mHT closely reflect the improvements in TBF. 2. Methods, Search Strategies and Sources of Information A systematic literature search of relevant research articles and reviews published between 1 January 1980 and 15 November 2022 provided an updated, comprehensive data review (PubMed, Web of Science). Values presented in this condensed article are averaged means. Search items were as follows: tumor hyperthermia, tumor blood flow, tumor perfusion, tumor oxygenation status, tumor oxygen supply, physiological mechanisms, oxygen-dependent radio-sensitization, HT-dependent radio-sensitization, HT-induced immune modulation (and combinations of these terms). This review is also based on one author's expertise in this research area since the late 1970s (PV). Exclusion criteria were as follows: (i) preclinical data obtained in fast-growing, bulky rodent tumors (>1% of body weight!), (ii) heating above 43 degC for more than 60 min because information obtained is clinically not translatable or can only be translated to a limited extent, and (iii) immersion of tumors into heated water baths, because the latter can be accompanied by severe edema formation due to osmotic water shifts upon treatment, thus probably concealing HT-related effects . This osmotic water shift adds to the HT-induced edema, thus further expanding the extracellular space . In addition, the whole leg is at elevated temperatures, a condition which might impact blood flow and the temperature distribution within the tumor to be treated (i.e., through "steal phenomena"). 3. Results: Assessment of Reliable Experimental and Clinical Data 3.1. Transiently Improved Tumor Blood Flow upon Localized Mild Hyperthermia: Potential Mechanisms Involved 3.1.1. Tumor Vascularization and Blood Flow Are Decisive Parameters Critically Affecting Efficacy of Localized Hyperthermia The vascular physiology of tumors is uniquely different from that of the corresponding normal tissues . When considering the continuous and indiscriminate formation of a vascular network in a growing tumor, five different pathophysiological mechanisms have to be taken into consideration: (i) co-option (accessing or "hijacking") of (pre-)existing vessels at the site of tumor growth, (ii) angiogenesis by endothelial sprouting from existing venules, (iii) vasculo-genesis, i.e., de novo vessel formation through the incorporation of circulating endothelial precursor cells), (iv) intussusception (i.e., splitting of the lumen of an existing vessel into two), and (v) formation of pseudo-vascular channels, lined by tumor cells rather than endothelial cells ("vascular mimicry") . The tumor (micro-)vasculature is characterized by vigorous proliferation, which leads to immature, structurally defective, and in terms of perfusion, ineffective microcirculation . This occurs partly due to missing functional innervation and a lack of pharmacological receptors of contractile elements (smooth muscle cells, pericytes). Relevant thermoregulatory vascular responsiveness and flow regulation within malignant tumors can, therefore, only take place in/via co-opted vessels. Blood flow rates in malignant tumors vary considerably, ranging from 0.01 to 1.0 mL g-1 min-1. In squamous cell carcinomas of the head and neck, as well as in colorectal cancers, flow rates up to 2 mL g-1 min-1 have been found, whereas, in prostate cancers, flow rates even up to 3 mL g-1 min-1 have been described . In addition, variability of TBF flow within an individual tumor (i.e., within different tumor sub-volumes, "intra-tumor heterogeneity") can be in the same flow range as described above for different tumor histologies, stages, and growth sites ("inter-tumor heterogeneity") . 3.1.2. Prime Role of Tumor Blood Flow in Hyperthermia Treatments Considering the major role of TBF in HT treatments, since the early 1980s, it has mistakenly been postulated that malignant tumors generally have lower blood flow rates than the adjacent normal tissue, thus, favoring quasi-selective heating of solid malignancies due to (i) compromised heat dissipation via convective heat transfer and (ii) the ability for "selective" heat deposition. Using electromagnetic irradiation, this latter notion completely disregards the role of tumor hyperhydration responsible for higher specific heat capacities ("heat storage capacities") and thermal conductivities . Besides its seminal impact on the heating properties of tumors, the efficacy of TBF can greatly impact parameters of the tumor microenvironment (TME), e.g., the tumor hypoxia and depletion of the bioenergetic status as well as tumor acidity (pH-distribution), i.e., parameters that substantially enhance the cytotoxic effect of HT at 43-45 degC. As shown in Figure 1A-E, which summarizes own preclinical data published since 1980 (using various heating techniques and detection methods, subtle control of key parameters of the cardiovascular and respiratory system, and of body core temperature), temperature-controlled, local mHT at 39.5-40.5 degC for 30-60 min, regardless of the heating technique (immersion into heated water not included), leads, on average, to transient (during heating and shortly after terminating mHT) and significant increases in TBF with concurrent significant improvements in the oxygenation status during the heating period . Usually, both enhancements are no longer evident 1 h after heating . At tumor tissue temperatures >=43 degC for 60 min, a shutdown of TBF is often observed upon heating due to a wide range of mechanisms, including a series of intravascular events, vessel wall alterations, extravascular events, and opposing host tissue/tumor mechanisms (extensively summarized in ) . Using water-filtered infrared-A- (wIRA-)heating for 60 min, mild hyperthermia significantly increased TBF by 30-80% above baseline throughout the observation period, with elevations remaining until the end of the treatment period of the tumors (with wet weights <= 0.5% of body weight). Upon mHT treatment, pO2 values increased by 50% on average. These favorable conditions were no longer evident 1 h post-heat . HT-induced changes of TBF are often equivocal in that they can change in non-predictable directions and to different extents and durations. In addition, localized divergent changes of blood flow in neighboring tissue sub-volumes have been observed , again indicating great variability . Note: The preclinical data presented in Figure 1D contradict the notion proposed earlier that the improvement of the tumor oxygenation (pO2) upon mHT might be due to a decreased O2 consumption rate (VO2) . Compared to the 35 degC data, TBF at 40 degC increased by 30%, the O2 supply by 26%, the O2 consumption VO2 by 47%, the O2 extraction rate by 17%, and the tumor tissue pO2 by 50%. Our own data are indicative of a significantly reduced O2 consumption rate of tumors in situ only at temperatures >=43.5 degC for >30 min . Due to equivalent ("proportionate") increases in microcirculatory blood flow (red blood cell flux) and in O2-consumption rates during mHT, no changes in the mitochondrial redox status were reported . Mechanisms most probably involved in transient blood flow improvements during mHT (and <= 1 h post-heat) are shown in Figure 2. In this flowchart, mHT-induced (patho-)physiological mechanisms contributing to a short-term increase in TBF and, thereby, to a more efficient convective (i.e., blood-borne) transport are summarized. Short term mechanisms include:Primary dilation of co-opted vessels within tumors; Thermoregulatory dilation of upstream blood vessels in the normal tissue adjacent to the growing tumor, a regulation that leads to secondary flow increases ("re-perfusion") through downstream tumor vessels in series with the normal tissue vascular bed ; Distinct reduction of viscous resistance to flow due to significant improvements in the key rheological parameters that determine blood flow behavior . In vitro, a temperature rise of 1 K significantly decreases the blood viscosity by 3.5% and the plasma viscosity by 2.5% . The relative kinematic viscosity of blood (at different hematocrit values) and of plasma as a function of temperature is shown in Figure 3 . Taken together, these mHT-induced changes in key parameters clearly improve the blood flow behaviour. Note: Together with the fall in the geometric resistance due to vasodilation observed in mHT, it may be expected that the above-mentioned reduction in viscous resistance may also result in a drop of total resistance to flow (mmHgminmL-1) in tumors in vivo. During hyperthermic perfusion of tumors in situ, a rise in tissue temperature from 37 degC up to 39.5 degC caused a drop of total resistance to the flow of 16%, i.e., 6.5%/K . This result may--at least partly--be explained by a significant loss of red blood cell deformability in severely acidic tumors in vivo . Sustained "re-perfusion" up to 24-48 h after heating has been attributed to a strong ( 80%) reduction of interstitial fluid pressure (IFP in normal tissues: -2 to 0 mmHg vs. IFP in tumors: up to +10-30 mmHg, "interstitial hypertension") . Increased blood flow in the latter case is the result of restoring effective perfusion pressures in the tumor microcirculation . The therapeutically relevant increases in TBF upon mHT, which are sustained up to 48 h post-HT, most probably result from a series of (plausible and/or experimentally proven) mechanisms, as shown in Figure 2. Besides (i) mHT-induced lowering of IFP, followed by subsequent restoration of adequate perfusion pressure (see above), another mechanism for sustained blood flow increases for 24-48 h is based on (ii) the mHT-induced activation of ERK-/Akt-pathways followed by HIF-1a activation with subsequent increased VEGF-secretion, the latter leading to robust tumor angiogenesis and rise in TBF . 3.2. Enhanced Tumor Oxygenation Status upon Localized Mild Hyperthermia 3.2.1. A Multifactorial, Complex Scenario Is Involved in the Transient Improvement of Tumor Oxygenation upon Mild Hyperthermia In general, an adequate O2 supply in malignant tumors (primaries and metastases) is spatially and temporally restricted by (i) inadequate perfusion (convective transport) and (ii) limited diffusion (diffusive transport), both leading to heterogeneously distributed hypoxia (i.e., pO2 < 10 mmHg; severe hypoxia: pO2 < 1 mmHg). diffusion-limited hypoxia is detectable even in early growth stages. A major goal of localized mHT in the combined treatment setting is the improvement of the tumor oxygenation status, which critically impacts inter alia radio-sensitivity, the efficacy of a series of anticancer drugs, protective antitumor immune responses, tumor progression (tumor aggressiveness), and finally patient outcome. As shown in Figure 4, localized mHT can improve the tumor oxygenation status via several mechanisms: Role of oxygen availability: As outlined above, mHT can lead to transient improvements of TBF. In most normal tissues, increases in nutritive blood flow usually result in concurrent increases in the O2 availability (O2 supply = blood flow x arterial O2 concentration) to a comparable extent, assuming a constant O2 concentration in the arterial blood ( 20 mL O2/dL blood). In patient tumors, a significant fraction of arterial blood (up to 25-30% ) can be shunted to the venous side without participating in the microvascular exchange processes. This fraction may significantly increase during mHT, thus excluding the assumption of a straightforward proportionality between TBF and O2 availability (at constant arterial O2 content). Note: During the HT treatment of anemic cancer patients (cHb < 12 g/dL), a special situation regarding the O2 supply conditions has to be taken into consideration. In this situation, two counteracting mechanisms determining the O2 supply of tumors have to be discussed. On the one hand, the O2 availability is reduced due to the lower O2 concentration in the arterial blood; on the other hand, the oxygen release from oxyhemoglobin (HbO2) into the surrounding tissue is enhanced in anemic patients due to increased concentrations of hemoglobin-bound 2,3-bisphosphoglycerate (2,3-BPG), which leads to a right-shift of the HbO2 dissociation curve (see below). However, the latter adaptation can only partially compensate for anemic hypoxemia. Role of oxygen diffusivity: On average, in situ tumors have a 15% higher water content than their tissues of origin ("tumor hyperhydration") . As a consequence of this hyperhydration, heat deposition upon electromagnetic irradiation is higher in tumors than in their corresponding normal tissues. Additionally, hyperhydration causes a distinctly higher O2 diffusivity (Fick's oxygen diffusion coefficient, DO2). DO2 values (O2 diffusivities) for tumors are increased by a factor of 1.9 compared to the tissues of origin . Additional edema formation is often seen upon HT , thus increasing hyperhydration and--as a result--further improving O2 diffusivity, finally supporting re-oxygenation of the tumor upon mHT. O2 diffusivity is also increased by mHT per se. Heating a tissue/tumor to 43 degC increases DO2 by 2.1-4.6%/K . Role of intensified tumor acidosis: Tissue exposure to mHT triggers a series of events that aggravate tumor tissue acidosis (pH|), finally reaching extracellular pH values of 6.20:Besides anaerobic glycolysis (because of tumor hypoxia), cancer cells rely on aerobic glycolysis (due to metabolic reprogramming, a core hallmark of cancer ). Both pathways produce high amounts of lactate and protons H+ ("lactic acid"), which are exported into the extracellular space, leading to extracellular acidosis (mean pHe 6.75). Aerobic glycolysis is stimulated by mHT-induced activation of HIF-1a, leading to an intensified Warburg effect for 24-48 h . In addition, tissue heating intensifies ATP hydrolysis with proton production as well as inhibiting the Na+/H+ antiport of the cell membrane . mHT per se intensifies tissue acidosis due to changes in chemical equilibria of the extracellular buffer systems: DpH/DT = -0.016 pH units/K . Upon mHT, pHe values steadily decrease, finally reaching 6.20 . This effect is temporary, i.e., it is observed only during mHT-application and until <= 6 h post-heat, leading to parallel effects only in this period. Intensified acidosis per se leads to a right shift of the HbO2-dissociation curve, regardless of the mechanisms causing acidosis (pH-Bohr effect) . As shown in Figure 6A, the respective difference in the pO2 values is 9 mmHg at 50% HbO2 saturation, which is comparable to the right shift when considering the fetal (HbF) and the maternal (HbA) blood at term. mHT per se also leads to a temperature-dependent right shift of the HbO2-dissociation curve . Both mechanisms (i.e., intensified acidosis and temperature rise) result in an enhanced O2 release from oxyhemoglobin into the surrounding tissue, thus supporting tumor tissue "reoxygenation". During mHT, a significant rise (+30%) of the CO2 partial pressures in the tumor-venous blood was found, paralleled by the pH drop mentioned above, thus amplifying the right-shift of the HbO2-dissociation curve (CO2-Bohr effect) . Role of hyperthermia-activated ERK/Akt-signaling pathways: In clinical settings, improvements in oxygenation status have occasionally been observed up to 24-48 h post-heating, most probably accompanying longer-lasting increases in TBF upon VEGF-driven forced angiogenesis , and--less likely--by HIF-1a-mediated inhibition of mitochondrial functions . As already mentioned above, changes in the mitochondrial redox status were not detected shortly after finishing mHT . As shown in Figure 1D, the O2 extraction steadily increases with temperature, clearly speaking against the notion of impaired OXPHOS upon mHT. This latter finding agrees with the basic results of Gullino et al. , who investigated the relationship between temperature and blood supply, and consumption of oxygen in rat mammary carcinomas. 3.2.2. Experimental and Clinical Evidence for Improved Tumor Oxygenation upon Localized Mild Hyperthermia: Updated Data Analysis Considering relevant data describing the tumor oxygenation status upon clinical mHT, the relationship between mean baseline (pre-HT) tissue pO2 (NT-pO2) and post-HT pO2 values (PT-pO2) can be linearly fitted for experimental and patient tumors upon mHT . These data suggest an equivalency of the HT techniques used in preclinical and clinical experiments to achieve this effect. Considering additional measurements of subcutaneous pO2 values in the clinical setting (red dot ), steady state mHT leads to a 1.64-fold increase in the mean pO2 values. Considering only experimental rodent tumors , primary canine , and human tumors (breast cancers, soft tissue sarcomas with baseline values between 1 and 10 mmHg (i.e., hypoxic tumors), mHT for 30-60 min almost doubles the pre-heat pO2 values , again irrespective of the heating technique (e.g., hyperthermic perfusion of tumors in situ, microwaves, radiofrequencies, water-filtered Infrared A), even if data of reasonably reliable experiments with water bath immersion at 38.5-41.5 degC were included . In these experiments, the mean pO2 before mHT was 7 mmHg (hypoxic fraction HF < 10 mmHg: 67%); during mHT, the average pO2 was 17 mmHg (HF: 46%), with a rapid return (within 10 min) to the pre-HT oxygenation status. Significant improvements in the tumor oxygenation status described above are fully comparable with data from preclinical experiments upon short-term spontaneous breathing pure oxygen (100% O2). In these experiments, steady state hyperoxic pO2 values of 400-450 mmHg within the arterial blood were reached. In contrast to mHT, an immediate, rapid drop of tumor pO2 to baseline values was observed upon return to room air breathing (<= 1-2 min) . Exposure of severely hypoxic tumors (average NT-pO2 1 mmHg) to mHT for 30-60 min increases the HT-pO2 to a mean of 3 mmHg. As shown in Figure 8, this small improvement in the oxygenation status increases the relative radiosensitivity (oxygen enhancement ratio, OER) from 1.32 to 1.84 (DOER = 0.52) due to the relatively steep slope of this section of the OER curve (blue range, A). In hypoxic tumors (e.g., locally advanced or recurrent breast cancers) with mean baseline pO2 values of 5 mmHg, mHT can cause a rise up to 10 mmHg, which is accompanied by an increase in OER from 2.10 to 2.39 (DOER = 0.29), caused by a less steep course of the OER curve (green range, B). In less hypoxic tumors (NT-pO2 17 mmHg), mHT leads to an increment up to a mean HT-pO2 of 32 mmHg, yielding an increase in OER from 2.53 to 2.79 (DOER = 0.26; red range, C). From these data, it may be concluded that the mHT-related gain in relative OER is greatest in the very hypoxic tumors. Note: As mentioned above, tumor oxygenation is considered as the key factor to substantially increase radiosensitivity. Therefore, mHT should be applied immediately/as close as possible before radiotherapy (RT). Using this schedule for recurrent breast cancers, re-RT doses could be significantly reduced compared to RT doses reported earlier . 4. Conclusions and Outlook Localized mHT can lead to transient (and occasionally sustained) improvements in TBF, both conditions being caused by a variety of different mechanisms. Increased O2 levels upon mHT are roughly equivalent to changes in TBF and O2 availabilities. However, a series of mechanisms, in addition to the improved TBF, significantly contribute to the increased oxygenation observed upon mHT, such as (i) increased diffusivities and (ii) intensified tumor acidosis and mHT per se, both leading to a right-shift of the HbO2 dissociation curve, thus enhancing O2 release from HbO2, and contingently (iii) HIF1-a-mediated inhibition of mitochondrial functions, a condition sometimes proposed. Whether mHT-induced suppression of cell proliferation and apoptosis of "aerobic" tumor cells (e.g., ), eventually reducing oxygen consumption and thus improving the oxygenation status, can be considered valid is the subject of current investigations, especially when translating this observation into clinical settings. Summarizing the result of mHT application, it can be stated that the transient reduction of tumor tissue hypoxia is--most probably--the result of a reduction of both perfusion-limited and diffusion-limited hypoxia. Localized mHT (39-42 degC for 30-60 min) leads to an almost doubling of initial O2 levels in tumors, independent of the heating technique used. In essence, we recommend considering the provided data in treatment protocols comprising mHT, particularly when sequences and time intervals in combined treatment modalities (e.g., thermo-radio-immuno-oncology) are discussed. Acknowledgments The authors thank Anett Lange for her technical support in the preparation of this review article. Author Contributions Conceptualization, original draft preparation, and draft of figures: P.V. Finalizing of figures: P.V., H.P. and M.N. Review and editing: P.V., A.G.P., G.M., F.S., H.P., M.N., A.R.T. and A.-L.G. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflicts of interest. Figure 1 Changes of relevant physiological parameters upon localized mHT as a function of tumor temperature. Results show tumor blood flow (TBF) and oxygen (O2) supply (=TBF x arterial O2 concentration, panel (A)), microvascular oxyhemoglobin (HbO2) saturation, and tumor tissue O2 partial pressure (pO2, panel (B)), in situ O2 consumption (VO2) and--completely independent of blood flow--the O2 consumption rate of isolated tumor cells in vitro (MRO2), panel (C)). There is clear evidence that TBF and the directly flow-dependent parameters have a maximum between 39.5 degC and 40.5 degC, whereas--at maintained, unrestricted O2 supply under in vitro conditions--MRO2 values have a distinct maximum at 42 degC with a decline at temperatures >= 43 degC (at maintained, adequate O2 supply under in vitro conditions). The oxygen extraction rate (= O2 uptake/O2 supply), a measure of the adequacy of the O2 supply to the tissue, increases with rising temperature (panel (D)). Oxygen diffusivity (DO2) increases linearly with temperature (panel (E)). Based on data provided in . Values are averaged means. Figure 2 Mild hyperthermia leads to transient increases in tumor blood flow through primary dilation of co-opted pre-existing blood vessels (left pathway) and secondary flow increase ("re-perfusion") through tumor blood vessels following thermoregulatory "upstream-vasodilation" in the normal tissue adjacent to the "downstream" tumor vessels (central pathway). More sustained improvements may be due to "resumptions" of blood flow due to drastic reduction in interstitial hypertension (i.e., lowering of interstitial fluid pressure, right pathway) and activation of molecular pathways that stimulate VEGF-secretion and thus forced tumor angiogenesis . Figure 3 Relative kinematic blood viscosity and plasma viscosity as a function of temperature at physiological pH (based on data provided in ). Additional information: At 37 degC, plasma viscosity is 1.3 cPoise (cP), and apparent viscosity of whole blood is 3.5 cP (shear rate: 150 s-1). Figure 4 Mechanisms responsible for the improvement of the O2 status upon localized mHT through enhancement of the O2 availability (central pathway), increased O2 diffusivity due to hyperhydration of tumor tissues and direct mHT-impact (left pathway), and intensified tumor acidosis leading to a right-shift of the HbO2-dissociation curve, thus facilitating the O2 release from the blood into the tissue (right pathway). Most probably, the mHT-induced increment in the O2 consumption is compensated by a comparable increase in the O2-extraction (left pathway). Figure 5 Heat-sensitive ERK/Akt-pathways (central pathway), metabolic reprogramming (right pathway), and VEGF-triggered robust angiogenesis (left pathway) and their putative role in sustained (up to 24-48 h) improvement of the tumor oxygenation status. Figure 6 Right-shift of the HbO2-dissociation curve resulting from intensified tumor acidosis (A) and hyperthermic tumor tissue temperatures (B), both facilitating the O2 release from oxyhemoglobin (HbO2), i.e., enhancing O2 unloading from red blood cells into the surrounding tissue. Figure 7 Linear relationship between mean baseline (pre-HT) tumor tissue pO2 (NT-pO2) and mean post-HT pO2 values (HT-pO2) in experimental and patient tumors using various heating techniques. In (A), the relationship includes normal tissue (dermis) measurements upon heating with water-filtered infrared-A irradiation (wIRA), red dot ). Data clearly demonstrate the equivalence of the various heating techniques chosen (blue triangles: microwave heating of rodent tumors; purple dots: microwave heating of patient tumors; red diamonds: wIRA-induced heating of experimental tumors; green square: mean pO2 value of all data presented). In general, the use of mHT for 30-60 min leads to a 1.6-fold increase in mean pO2. In (B) only data of hypoxic tumors (mean pO2 < 10 mmHg) are shown. Here, post-mHT pO2 values almost doubled. Figure 8 In severely hypoxic tumors (mean pretreatment pO2 1 mmHg) exposed to mHT for 30-60 min, the mean post-HT pO2 was 3 mmHg, resulting in a rise in the Oxygen Enhancement Ratio (OER, relative radiosensitivity) from 1.32 to 1.84 (blue range, A). In hypoxic tumors (mean pre-HT pO2 = 5 mmHg), HT caused a rise to 10 mmHg, which was accompanied by an increase in OER from 2.10 to 2.39 (green range, B). In less hypoxic tumors (mean pre-HT pO2 = 17 mmHg), mHT led to a pO2 increment up to 32 mmHg, resulting in an increase in OER from 2.53 to 2.79 (red range, C). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000498 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051011 foods-12-01011 Article Investigating the Potential of Full-Fat Soy as an Alternative Ingredient in the Manufacture of High-Moisture Meat Analogs Jeon Yung-Hee Formal analysis Investigation Writing - original draft Visualization + Gu Bon-Jae Methodology Writing - review & editing Supervision + Ryu Gi-Hyung Conceptualization Methodology Resources Project administration Funding acquisition * Ruiz-Capillas Claudia Academic Editor Kang Zhuangli Academic Editor Department of Food Science and Technology, Food and Feed Extrusion Research Center, Kongju National University, Yesan 32439, Republic of Korea * Correspondence: [email protected]; Tel.: +82-41-330-1484 + These authors contributed equally to this work. 27 2 2023 3 2023 12 5 101110 12 2022 13 2 2023 16 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The increase in meat consumption could adversely affect the environment. Thus, there is growing interest in meat analogs. Soy protein isolate is the most common primary material to produce high-moisture meat analogs (LMMA and HMMA), and full-fat soy (FFS) is another promising ingredient for LMMA and HMMA. Therefore, in this study, LMMA and HMMA with FFS were manufactured, and then their physicochemical properties were investigated. The water holding capacity, springiness, and cohesiveness of LMMA decreased with increasing FFS contents, whereas the integrity index, chewiness, cutting strength, degree of texturization, DPPH free radical scavenging activity, and total phenolic content of LMMA increased when FFS contents increased. While the physical properties of HMMA decreased with the increasing FFS content, its DPPH free radical scavenging activity and total phenolic contents increased. In conclusion, when full-fat soy content increased from 0% to 30%, there was a positive influence on the fibrous structure of LMMA. On the other hand, the HMMA process requires additional research to improve the fibrous structure with FFS. extrusion meat analogue meat alternative plant-based meat extruded protein high-moisture meat analog textured vegetable protein whole soy Cooperative Research Program for Agriculture Science and Technology DevelopmentPJ016188012022 Rural Development Administration, Republic of KoreaKongju National UniversityThis work was carried out with the support of the "Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ016188012022)," Rural Development Administration, Republic of Korea. This work was supported by a research grant from Kongju National University in 2022. pmc1. Introduction The Food and Agriculture Organization of the United Nations (FAO) estimates that by 2030, per capita annual meat consumption will be 100 kg in industrialized countries . Mass meat production induces ethical issues for animals, low land utilization, water usage, adverse environmental effects, etc . Specifically, increasing meat products can boost carbon dioxide levels, increasing greenhouse gas formation . Thus, consumers are starting to embrace plant-based meat analogs as an alternative source of real meat products because they are more environmentally-friendly and sustainable as a nutrient of protein as well as an aspect of animal welfare and animal rights . At present, there are many technologies for producing meat analogs, such as extrusion cooking , freeze structuring , electrospinning , mechanical elongation , in vitro cultured meat , and the shear-cell technique . Among the technologies, extrusion cooking is one of the most representative methods for the manufacture of meat analogs by using high temperatures, shear, and pressure . Extrusion cooking is widely used for manufacturing many food products, such as puffed snacks, pasta products, noodles, breakfast cereals, meat analogs, gelatinized starch, dough, baby food, and others, because of its benefits of flexibility, low cost, high output, and quality control . Extrusion cooking is classified into high-moisture processing types, according to the degree of addition of moisture content into the extruder and the presence of a cooling die at the end of barrels. The low-moisture extrusion process for manufacturing meat analogs produces expanded meat analogs, and the expansion phenomenon causes sponge-like structures for the meat analogs . Low-moisture meat analog (LMMA) requires hydration prior to making patties, chunks, and nuggets . On the other hand, high-moisture extrusion cooking can produce non-expanded meat analogs that have denser and highly fibrous structures by using a cooling die . More complex formulations are possible with high-moisture extrusion cooking, and it is not necessary to use highly soluble ingredients, making it a more economical technology . Meat analogs, produced by extrusion cooking, are mainly composed of 50-95% (dry basis) plant-based proteins . The most widely used plant-based protein in producing meat analogs using extrusion processing is soy protein due to its gelation, functional, and nutritional properties . There are many types of soy protein in the meat analog market based on protein contents and extract processes, such as soy protein isolate (SPI), soy protein concentrate (SPC), full-fat soy (FFS), defatted soy flour (DSF), etc. . Among them, SPI is the one mainly used in many research projects and industries for manufacturing plant-based meat analogs. In the extraction step for SPI, many steps are required to obtain concentrated and purified proteins, which cause environmental pollution and are expensive. In contrast, full-fat soy (FFS) is not only rich in nutrients such as complex carbohydrates, soluble fibers, and isoflavones but it is also easily accessible and cost-effective due to its minimal processing requirements . Most research on extruded meat analogs (LMMA and HMMA) has centered around the use of SPI-based formulas due to their functional properties and smooth extrusion process for manufacturing . Conversely, the impact of the manufacturing process on the texturization of FFS has not been explored, despite its potential as a substitute for SPI, due to the difficulties associated with its extrusion process. In this study, we aimed to fill this gap by investigating the texturization of FFS using two types of extrusion methods and examining the physical and antioxidant properties of LMMA and HMMA. 2. Materials and Methods 2.1. Materials Soy protein isolate (SPI), full-fat soy (FFS), wheat gluten (WG), and corn starch (CS) were purchased from Plant Albumen Co., Ltd. (Pingdingshan, China), Korea Seed & Variety Service (Jecheon, Republic of Korea), Roquette Freres (Lestrem, France), and Samyang Co. (Ulsan, Republic of Korea), respectively. The crude protein and fat contents of SPI (84.87 +- 0.1% and 1.84 +- 0.2%), FFS (38.60 +- 0.3% and 20.07 +- 0.1%), and WG (77.81 +- 0.3% and 0.24 +- 0.2%) were measured using the Dumas method and Danlami et al. , respectively. The formulation of raw materials for producing LMMA and HMMA is shown in Table 1. 2.2. Manufacturing of Meat Analogs by High-Moisture Extrusion Cooking high-moisture extrusion cookings were performed using a co-rotating intermeshing twin screw extruder (THK31T-No.5, Incheon Machinery Co., Incheon, Republic of Korea) with a 3 cm screw diameter and a 69 cm length (L/D: 23:1). The extrusion conditions--40% feed moisture, 160 degC barrel temperature, 250 rpm screw speed, and a slit die with dimensions of 1 cm (W) x 0.45 cm (H) x 8 cm (L)--were set for the low-moisture extrusion process to manufacture LMMA . High-moisture extrusion cooking for HMMA was performed with 60% feed moisture, 160 degC barrel temperature, 150 rpm screw speed, and a long cooling die (dimensions of 7 cm (W) x 1 cm (H) x 50 cm (L)) cooled by 20 degC water with a water circulator (Duksan Cotran Co., Ltd., Daegu, Republic of Korea) . At least 30 extrudates were collected for each sample after the condition was stable. The extrusion process for LMMA was performed until 30% of the FFS inclusion level because of the collapse of the texturized structure at the FFS level above 40%. After the extrusion cooking process, the extruded samples were cut into 1 cm x 1 cm pieces for subsequent texture profile analysis and to determine the cutting strength of both low-moisture meat analogs (LMMA) and high-moisture meat analogs (HMMA). The cut LMMAs were dried at 50 degC for 12 h and stored at room temperature, and the cut HMMAs were stored in a -18 degC freezer and thawed in a 4 degC refrigerator for 24 h (FR-S690FXB, Klasse Auto Co., Ltd., Seoul, Republic of Korea) before the following analysis. Chemical properties were measured by using the dried LMMA and freeze-dried HMMA samples as ground samples (50-70 mesh particles). 2.3. Texture Profile Analysis and Cutting Strength Texture profile analysis (TPA) was performed with a texture analyzer (Compac-100, Sun Science Co., Ltd., Tokyo, Japan) using a 2.5 cm diameter cylinder probe with a 10 kg maximum peak stress. The cutting strength (CS) was determined using a cutting probe (0.75 x 3.83 cm) with a 2 kg maximum peak stress. The LMMA sample was hydrated in a water bath at 70 degC for 1 h and then equilibrated at room temperature, and the HMMA sample was equilibrated at room temperature before the determination of the TPA and CS. The meat analogs for CS were cut along the vertical direction (transversal strength, Fv) and parallel direction (longitudinal strength, Fp) of the samples' flow direction. The calculation of springiness, cohesiveness, chewiness, and CS was expressed according to the equation below . The results were averaged from 6 measurements. Springiness (%) = D2/D1 x 100(1) D1: distance reached for the first maximum stress D2: distance reached for the second maximum stress Cohesiveness (%) = A2/A1 x 100(2) A1: area underneath the first compression curve A2: area underneath the second compression curve Chewiness (g) = cohesiveness x springiness x highest peak force (g)(3) Cutting strength (g/cm2) = highest peak force (g)/cross-sectional area (cm2)(4) 2.4. Water Holding Capacity The water holding capacity (WHC) of LMMA and HMMA was determined by the modified methods of Gu and Ryu and Diaz et al. , respectively. Approximately 5 g (on a dry basis) of samples were weighed. The LMMA was hydrated at 70 degC in a water bath for 1 h as per Gu and Ryu , and the HMMA was hydrated at 50 degC for 16 h as per Diaz et al. . After that, the samples were drained for 15 min. WHC was expressed as grams of water retained per gram of dried sample using Equation (5). Water holding capacity (g/g) = (weight of wet sample - weight of dry sample)/(weight of dry sample) x 100(5) 2.5. Degree of Texturization Degree of texturization was calculated by Equation (6) . Degree of texturization = Fv/Fp(6) where Fv is the transversal strength, and Fp is the longitudinal strength. 2.6. Integrity Index The integrity index was determined by a modified method of Gu and Ryu . A 5 g (dry basis) sample that was sunk in 100 mL of distilled water was autoclaved at 121 degC for 15 min, and then the sample was cooled and drained for 30 s. 100 mL of distilled water was added into the sample and homogenized at 17,450 rpm for 1 min, and then they were dried on a 20-mesh sieve at 105 degC for 12 h. The integrity index was calculated according to Equation (7). Integrity index (%) = (weight of dry residue on sieve)/(weight of sample) x 100(7) 2.7. DPPH Free Radical Scavenging Activity DPPH free radical scavenging activity was determined as per Brand-Williams et al. with some modifications. A 2 g sample was extracted at room temperature by ethanol (80%) for 2 h, and then the extracted sample was centrifuged at 3000 rpm for 0.5 h. 3.9 mL of DPPH solution (0.0024 g DPPH reagent/100 mL of methanol) was mixed with the supernatant (0.1 mL). The absorbance (at 515 nm) of the solution was read after the mixture was incubated at room temperature in a dark room for 0.5 h. The DPPH free radical scavenging was calculated by Equation (8). DPPH free radical scavenging activity (%) = (A0 - A)/A0 x 100(8) where A0 is the absorbance of the blank, and A is the absorbance of the sample. 2.8. Total Phenolic Contents Total phenolic contents (TPC) were determined as per Slinkard and Singleton's method . A 2 g sample was extracted with 10 mL of ethanol (80%) for 2 h, and then the extract was centrifuged at 3000 rpm for 0.5 h. A 1.5 mL of 10% (v/v) Folin-Ciocalteu reagent was mixed with 0.3 mL supernatant for 5 min with a vortexer, and then the mixture was mixed with another solution (1.5 mL of Na2CO3 (60 g/L)) and incubated at room temperature for 2 h. After incubation, a wavelength of 765 nm was utilized to measure the absorbance of the solution. TPC was calculated as mg/g of gallic acid equivalents in milligrams per gram of dried sample (mg GAE/g). 2.9. Macrostructure The macrostructure of cross-sectional LMMA and HMMA was observed after the samples were cut into 1 cm (W) x 1 cm (D). For the fibrous structure of LMMA and HMMA, the extruded samples (LMMA and HMMA) were cut into 3 cm (W) x 5 cm (D) and 5 cm (W) x 7 cm (D), respectively. The cut samples were opened in the longitudinal direction and then photographed for observation of the fibrous structure. 2.10. Statistical Analysis All experiments were performed in triplicate unless otherwise stated and analyzed using SPSS (version 27.0, IBM-SPSS, Thornwood, NY, USA). Analysis of variance (ANOVA) and comparison of means were performed using Duncan's multiple range tests at p < 0.05. Correlation coefficients among the data were determined using Pearson's correlation coefficient (r). 3. Results and Discussion 3.1. Texture Profile Analysis, Cutting Strength, and Water Holding Capacity The textural properties (springiness, cohesiveness, and chewiness) and cutting strength of the vertical (V-CS) and parallel (P-CS) directions of LMMA and HMMA are summarized in Table 2. Springiness means how quickly an extruded meat analog is recovered after deformation by a probe; cohesiveness indicates the internal strength of bonds; and chewiness shows the energy requirement for masticating the food . Significant differences in the springiness and cohesiveness of both LMMA and HMMA were observed, showing that higher FFS content in LMMA and HMMA caused a decrease in springiness and cohesiveness. Springiness is connected to protein content, and the addition of FFS decreases protein content comparatively, resulting in a decrease in protein cross-linking strength . Ma and Ryu also reported that the springiness and cohesiveness of meat analogs were mainly affected by cross-linking formation in the internal structure. The springiness of both LMMA and HMMA showed a positive correlation with cohesiveness (r = 0.987 and 0.990, respectively, p < 0.01) (Table 3 and Table 4), and the FFS caused a more negative effect on the springiness of LMMA than that of HMMA, resulting in 97.43 +- 3.4 (FFS 0%) to 79.32 +- 5.1% (FFS 30%) for LMMA and 93.03 +- 0.8 (FFS 0%) to 88.58 +- 1.2% (FFS 30%) for HMMA. The result could be due to the fact that high-moisture extrusion cooking is a more effective method of making fibrous structures compared to low-moisture extrusion cooking, maintaining molecular interactions in spite of higher FFS content . The intermolecular protein cross-linking occurs in the cooling die, resulting in high-fibrous structures . Additionally, increasing moisture content can increase the interactions between hydrogen bonds-disulfide bonds, and hydrophobic interactions-disulfide bonds . The chewiness and cutting strength (in both vertical and parallel directions) of LMMA and HMMA had contrary results, showing that, with an increase in FFS content, those of LMMA were increased but those of HMMA were decreased. The increase in LMMA's texture properties could be due to the interaction of lipids and proteins during the extrusion cooking process . The reason for this is due to the reduction of the expansion ratio of LMMA with increasing FFS content due to the lubricant behavior of the lipids in FFS in the extruder barrel. Then, the behavior resulted in a decrease in the buildup of pressure for the vaporization of water, increasing both non-covalent and covalent interactions to build protein networks with suitable fibrous structures . A water-phase change that causes the expansion phenomenon by the vaporization of water in the mixture of raw materials can increase the distance between the substances, resulting in weak structures in meat analogs . On the other hand, the HMMA process, in general, did not involve the expansion phenomenon, and thus the vaporization of water by pressure drop did not occur during the process that extends between the protein, starch, and lipid molecules. Lipids are expected to interact with proteins with a saturation limit determined by the number of hydrophobic sites , but the decrease in the texture properties of HMMA might be due to the excessive lipid content that disturbs the molecular bonds during the extrusion cooking. According to Van Hoan et al. , a high moisture content can reduce the die pressure, thus reducing the amount of lipid lost during the extrusion. In other words, high-moisture extrusion cooking, which has a higher moisture content than low-moisture extrusion cooking with a low die pressure, could cause excessive lipid content that hinders molecular bonding. Alzagtat and Alli reported that lipids might be coated on the surface of the protein aggregates, which prevented the protein molecules from cross-linking. The water holding capacity (WHC) of LMMA and HMMA is shown in Figure 2. As shown, the lowest WHCs of 2.55 +- 0.1 g/g at FFS 30% for LMMA and 2.48 +- 0.0 g/g at FFS 50% for HMMA were observed, while the highest WHCs were 5.09 +- 0.21 g/g for LMMA and 3.16 +- 0.19 g/g for HMMA at FFS 0%. This is because the WHC is directly affected by the porosity of the meat analogs . The empty spaces are filled by water that builds inter-hydrogen bonds caused by hydroxyl groups . On the other hand, the reduction of porous structure could be due to the increase in lipid contents from FFS. Ottoboni et al. reported that high lipid content might lead to a decrease in back-pressure during extrusion cooking, resulting in poor expansion. WHC had positive correlations with springiness (r = 0.934, p < 0.01) and cohesiveness (r = 0.950, p < 0.01) of LMMA and negative correlations with chewiness (r = -0.910, p < 0.01), V-CS (r = -0.972, p < 0.01), and P-CS (r = -0.911, p < 0.01) (Table 3). It was consistent with the results of Gu and Ryu that the WHC of LMMA is positively correlated with springiness and cohesiveness. In contrast, those of HMMA had positive correlations, springiness (r = 0.778, p < 0.01), cohesiveness (r = 0.764, p < 0.01), chewiness (r = 0.821, p < 0.01), V-CS (r = 0.807, p < 0.01), and P-CS (r = 0.767, p < 0.01) (Table 4). 3.2. Degree of Texturization and Integrity Index The degree of texturization (DT) can be used as an indicator for fibrous structure formation , and the integrity index indicates the residue of meat analogs after hydrating, autoclaving, homogenizing, and drying . The higher integrity index means the better the texturization, the higher the integrity index, since the meat analogs' texture remained strong and unweakened after the harsh process steps . Therefore, the DT and integrity index of LMMA and HMMA generally showed a positive correlation (r = 0.955 and r = 0.768, respectively) (p < 0.01) (Table 3 and Table 4) . With increasing FFS content from 0% to 30%, the DT and integrity index of LMMA increased, but those of HMMA decreased up to 50% of FFS content . The highest DT and integrity index were observed at LMMA with 30% FFS content (3.04 +- 0.1 and 70.28 +- 1.6%, respectively), and the lowest DT and integrity index were determined at HMMA with 50% FFS content (1.09 +- 0.0 and 74.46 +- 1.4%, respectively). The increase in DT and integrity index of LMMA could be a result of the interactions among phenolic compounds in FFS, protein, starch, and lipid molecules. Polyphenols and protein molecules are known to interact with each other reversibly (hydrogen bonding, hydrophobic bonding, and van der Waals forces) and irreversibly (covalent bonds) . Alzagtat and Alli also reported that lipids play a role as a plasticizer by forming complexes with starch, protein, and lipid during the extrusion cooking process, which can contribute to the stabilized fibrous structure. Conversely, the reason for the decrease in DT and integrity index of HMMA could be because an excessive amount of lipid hindered protein-protein, protein-starch, protein-lipid, and protein-polyphenol interactions during extrusion cooking. 3.3. DPPH Free Radical Scavenging Activity and Total Phenolic Contents DPPH free radical scavenging activity and total phenolic contents (TPC) were conducted to find out the antioxidant properties of meat analogs with FFS. A significant change in DPPH free radical scavenging activity and TPC of LMMA and HMMA was observed when FFS was added. The lowest values of DPPH free radical scavenging activity and TPC for both LMMA and HMMA were observed at FFS 0%, and DPPH free radical scavenging and TPC were increased by increasing FFS content from 0 to 30% for LMMA and 0 to 50% for HMMA . FFS content had a significant positive effect on the values of DPPH free radical scavenging activity and TPC that are related to antioxidant activity, showing the highest values of DPPH free radical scavenging activity were 18.14 +- 0.4% for LMMA and 28.99 +- 0.8% for HMMA . This could be because FFS originally contained more phenolic compounds such as tannins, polyphenols, flavonoids, and phenolic terpenes compared to SPI . Aludatt et al. also reported that the phenolic content of the full-fat meal was higher than that of defatted ones, showing higher antioxidant activity. 3.4. Macrostructure Digital photographs of LMMAs and HMMAs with different FFS content are shown in Table 5. The LMMA was not texturized when the FFS content was higher than 40%. In contrast, the HMMA was texturized to 50% FFS content. The fibrous structure is one of the key factors in judging whether meat analogs have a meat-like texture . The fibrous structure of LMMA increased as the FFS content increased, and LMMA with a FFS content of 30% had the most fibrous structure and well-arranged layers than other LMMAs. The fibrous structure of HMMA was decreased by increasing the FFS content, but HMMA with an FFS of 50% did not exhibit definite layers or fibrous structure. The sponge-like structure of LMMA decreased with an increase in the FFS content, but HMMA showed a dense and layered structure. The structure of LMMA is due to the many pores caused by the expansion phenomenon that resulted from the pressure drop caused by the pressure difference between the inside and outside of the extruder. However, the HMMA was formed with a dense and fibrous structure because of the aggregation effect in the cooling die . 4. Conclusions Overall, FFS was determined to be a promising ingredient for manufacturing meat analogs as an alternative source to SPI in this study. FFS content had a significant effect on the physical and antioxidant properties of LMMA and HMMA (p < 0.05). In addition, LMMA with 30% FFS content showed the most fibrous structures and the highest texture properties (chewiness, cutting strength, integrity index, and degree of texturization). However, texturization was not possible with over 40% FFS content in the LMMA process, but the HMMA process could manufacture texturized proteins with up to 50% FFS content, which completely replaced SPI in this study. The antioxidant properties of LMMA and HMMA increased as the FFS content increased. Further research is needed to increase FFS content for the LMMA process and enhance the texture properties of the HMMA by optimizing the independent process variables of the extrusion process. This study will contribute to enhancing the quality of meat analogs in terms of nutrition and texture aspects and removing the complex extraction steps for producing soy protein isolate, resulting in a reduction in cost and environmental pollution for the manufacture of meat analogs. Author Contributions Conceptualization, G.-H.R. and B.-J.G.; methodology, G.-H.R.; formal analysis, Y.-H.J.; investigation, Y.-H.J.; resources, G.-H.R.; writing--original draft preparation, Y.-H.J. and B.-J.G.; writing--review and editing, B.-J.G.; visualization, Y.-H.J.; supervision, B.-J.G.; project administration, G.-H.R.; funding acquisition, G.-H.R. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Data is contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Low- (A) and high-moisture (B) extrusion processes and screw configurations used in this experiment. Figure 2 Water holding capacity of meat analogs with various full-fat soy (FFS) contents. LMMA: low-moisture meat analog; HMMA: high-moisture meat analog. Different letters (a-d) above the bars indicate the significantly different for each extrusion type (LMMA and HMMA) (p <= 0.05) by Duncan's multiple range tests. Figure 3 Degree of texturization (A) and integrity index (B) of extruded high-moisture meat analogs with different full-fat soy (FFS) content. LMMA: low-moisture meat analog; HMMA: high-moisture meat analog. Different letters (a-e) above the bars indicate the significantly different for each extrusion type (LMMA and HMMA) (p <= 0.05) by Duncan's multiple range tests. Figure 4 DPPH free radical scavenging activity (A) and total phenolic contents (B) of meat analogs with various by full-fat soy (FFS) contents. LMMA: low-moisture meat analog; HMMA: high-moisture meat analog. Different letters (a-e) above the bars indicate the significantly different for each extrusion type (LMMA and HMMA) (p <= 0.05) by Duncan's multiple range tests. foods-12-01011-t001_Table 1 Table 1 Formulation of extruded high-moisture meat analog with different full-fat soy content. Extrusion Type Full-Fat Soy (%) Soy Protein Isolate (%) Wheat Gluten (%) Corn Starch (%) LMMA 0 50 40 10 10 40 40 10 20 30 40 10 30 20 40 10 HMMA 0 50 40 10 10 40 40 10 20 30 40 10 30 20 40 10 40 10 40 10 50 0 40 10 foods-12-01011-t002_Table 2 Table 2 Texture profile analysis and cutting strength (vertical and parallel) of meat analogs with various full-fat soy contents. Extrusion Type FFS Content (%) Springiness (%) Cohesiveness (%) Chewiness (g) Cutting Strength (g/cm2) Vertical Parallel LMMA 0 97.43 +- 3.4 a 94.15 +- 3.5 a 263.42 +- 98.6 c 551.3 +- 38.9 d 351.2 +- 30.4 c 10 84.57 +- 1.3 b 79.74 +- 2.3 b 399.16 +- 82.2 b 999.7 +- 69.3 c 403.4 +- 64.7 bc 20 83.87 +- 5.3 bc 74.95 +- 3.5 b 436.72 +- 43.5 b 1193.4 +- 68.2 b 427.5 +- 45.1 b 30 79.32 +- 5.1 c 67.58 +- 6.0 c 537.67 +- 34.5 a 1677.5 +- 66.2 a 552.0 +- 31.1 a HMMA 0 93.03 +- 0.8 a 79.07 +- 1.2 a 4295.64 +- 130.9 a 1236.8 +- 128.8 a 711.7 +- 114.8 a 10 93.78 +- 0.6 a 79.15 +- 0.7 a 3967.45 +- 114.2 b 1020.7 +- 52.8 b 667.9 +- 30.1 ab 20 90.01 +- 1.0 b 74.45 +- 2.0 b 3559.24 +- 175.4 c 977.7 +- 57.5 b 625.5 +- 37.5 bc 30 88.58 +- 1.2 b 73.11 +- 1.8 b 3170.47 +- 172.5 d 947.2 +- 63.8 b 626.0 +- 41.6 bc 40 86.26 +- 1.5 c 69.73 +- 4.1 c 2550.08 +- 206.1 e 821.1 +- 70.6 c 562.3 +- 47.4 c 50 75.09 +- 3.6 d 54.51 +- 2.8 d 1183.40 +- 115.6 f 477.9 +- 35.0 d 438.6 +- 39.3 d Different letters (a-f) in the same column for each extrusion type indicate the significantly different (p <= 0.05) by Duncan's multiple range tests. FFS: Full-fat soy content; LMMA: low-moisture meat analog; HMMA: high-moisture meat analog. foods-12-01011-t003_Table 3 Table 3 Pearson correlation matrix of physical properties for low-moisture meat analogs. WHC Springiness Cohesiveness Chewiness V-CS P-CS DT Integrity Index WHC 1 Springiness 0.934 ** 1 Cohesiveness 0.950 ** 0.987 ** 1 Chewiness -0.910 ** -0.905 ** -0.917 ** 1 V-CS -0.972 ** -0.949 ** -0.961 ** 0.928 ** 1 P-CS -0.911 ** -0.875 ** -0.891 ** 0.917 ** 0.968 ** 1 DT -0.925 ** -0.964 ** -0.957 ** 0.841 ** 0.910 ** 0.790 ** 1 Integrity index -0.962 ** -0.949 ** -0.952 ** 0.866 ** 0.965 ** 0.881 ** 0.955 ** 1 Water holding capacity (WHC); vertical cutting strength (V-CS); parallel cutting strength (P-CS); degree of texturization (DT). Values with ** were significantly different (p < 0.01). foods-12-01011-t004_Table 4 Table 4 Pearson correlation matrix of physical properties for high-moisture meat analogs. WHC Springiness Cohesiveness Chewiness V-CS P-CS DT Integrity Index WHC 1 Springiness 0.778 ** 1 Cohesiveness 0.764 ** 0.990 ** 1 Chewiness 0.821 ** 0.976 ** 0.964 ** 1 V-CS 0.807 ** 0.916 ** 0.900 ** 0.950 ** 1 P-CS 0.767 ** 0.864 ** 0.840 ** 0.889 ** 0.958 ** 1 DT 0.715 ** 0.889 ** 0.882 ** 0.907 ** 0.902 ** 0.752 ** 1 Integrity index 0.777 ** 0.749 ** 0.739 ** 0.837 ** 0.809 ** 0.720 ** 0.768 ** 1 Water holding capacity (WHC); vertical cutting strength (V-CS); parallel cutting strength (P-CS); degree of texturization (DT). Values with ** were significantly different (p < 0.01). foods-12-01011-t005_Table 5 Table 5 Fibrous and cross-sectional structures of extruded high-moisture meat analogs with different full-fat soy (FFS) content. Extrusion Types Structure Full-Fat Soy Content (%) 0 10 20 30 40 50 LMMA Cross-sectional Fibrous HMMA Cross-sectional Fibrous LMMA: low-moisture meat analog; HMMA: high-moisture meat analog. 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PMC10000499 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051009 foods-12-01009 Review The Mushroom Glucans: Molecules of High Biological and Medicinal Importance Vetter Janos Michaud Philippe Academic Editor Department of Botany, University of Veterinary Medicine Budapest, Rottenbiller 50, 1077 Budapest, Hungary; [email protected] 27 2 2023 3 2023 12 5 100913 1 2023 15 2 2023 22 2 2023 (c) 2023 by the author. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Carbohydrates, including polysaccharide macromolecules, are the main constituents of the fungal cell wall. Among these, the heteropolymeric glucan molecules are decisive, as they not only protect fungal cells but also have broad, positive biological effects on the animal and human bodies. In addition to the beneficial nutritional properties of mushrooms (mineral elements, favorable proteins, low fat and energy content, pleasant aroma, and flavor), they have a high glucan content. Folk medicine (especially in the Far East) used medicinal mushrooms based on previous experience. At the end of the 19th century, but mainly since the middle of the 20th century, progressively more scientific information has been published. Glucans from mushrooms are polysaccharides that contain sugar chains, sometimes of only one kind (glucose), sometimes having several monosaccharide units, and they have two (a and b) anomeric forms (isomers). Their molecular weights range from 104 to 105 Da, and rarely 106 Da. X-ray diffraction studies were the first to determine the triple helix configuration of some glucans. It seems that the existence and integrity of the triple helix structure are criteria for their biological effects. Different glucans can be isolated from different mushroom species, and several glucan fractions can be obtained. The biosynthesis of glucans takes place in the cytoplasm, the processes of initiation and then chain extension take place with the help of the glucan synthase enzyme complex (EC 2.4.1.34), and the sugar units are provided by sugar donor UDPG molecules. The two methods used today for glucan determination are the enzymatic and Congo red methods. True comparisons can only be made using the same method. Congo red dye reacts with the tertiary triple helix structure, and the resulting glucan content better reflects the biological value of glucan molecules. The biological effect of b-glucan molecules is proportional to the integrity of the tertiary structure. The glucan contents of the stipe exceed the values of the caps. The glucan levels of individual fungal taxa (including varieties) differ quantitatively and qualitatively. This review presents in more detail the glucans of lentinan (from Lentinula edodes), pleuran (from Pleurotus ostreatus), grifolan (from Grifola frondose), schizophyllan (from Schizophyllum commune), and krestin (from Trametes versicolor), along with their main biological effects. mushrooms glucans structural properties synthesis glucan determinations glucan content lentinan pleuran grifolan schizophyllan krestin This research received no external funding. pmc1. Introduction More and more research and measurement data are being published on the composition and different constituents of mushrooms. Nowadays, mushrooms (both wild and cultivated taxa) have a dual role, since on the one hand they are increasingly important and valuable foods, and on the other hand, they are sources of active substances of increasing importance (i.e., molecules with biological activity) . The wall is a very important organelle of fungal cells, having different vital functions: it is responsible for mechanical protection, osmotic conditions, protection from dehydration, binding of distinct molecules, etc. . The cell wall has a role in permeability, in the movement of intracellular enzymes into the environment, and in the uptake of hydrolyzed metabolites from nature. The problem of understanding cell wall composition and structure has been an important mycological question for decades. A newer understanding of the systems of the fungal world (according to which fungi and mushroom-like organisms belong to Protista, Chromista, or Eumycota kingdoms) indicates that the cell wall components of each group are typically different (e.g., cellulose is not a component of the cell wall of Eukaryota fungi). The focus of interest is on the cell wall structure of large fungi; the "mushroom" category essentially refers to Ascomycetes and Basidiomycetes (the taxa with fruiting bodies). According to Grun's model , the cell wall contains different glucans ( b-glucans), glycoproteins, and chitin. Based on Fesel and Zuccaro's model , the chitin layer is located in the cell membrane, while the middle position includes the glucan molecules ( b-glucans), and the outermost layer consists of mannoproteins. The cell wall components of fungi can represent a considerable part (up to 40-50%) of their body weight. It seems today that determining the in vivo structure of the cell wall will provide challenges for researchers for a long time to come. Isolation and extraction of the different cell wall constituents clearly involve the destruction of the in vivo structures, so it is difficult to deduce the structure of the original "working" cell wall. In the case of fungi, the existence of the hypha-mycelium-fruiting body relationship is critical (i.e., that a large mushroom fruiting body is made up of a complex network of hyphae). The functional essence of the hyphal structure is the great cell wall surface with which the hyphal system is in contact with the outside world and through which its most important life processes (e.g., nutrition) are realized. The aim of our work is to present and characterize a group of active ingredients, mushroom glucans. The chemical structure and types of this group of molecules, their role in fungi, their distribution, and their measurable amounts in different species are discussed in many scientific publications, the number of which is growing rapidly . The biological effects of glucans are investigated at a variety of research levels and methods (from in vitro studies to the effects of isolated, purified preparations to the ingestion of mushrooms as food). Other biological effects of glucans can be known mainly from folk medicine and medical traditions and partly from a variety of early scientific publications . The main goal of this work is to provide guidance in the growing collection of information and to do it all from a mycological perspective. 2. Chemical Composition of Mushrooms: Carbohydrates Studying the published data series on the composition of mushrooms, two important conclusions can be made regarding the total carbohydrate content:This parameter was calculated with the help of other measured parameters: total carbohydrate content = 100 - (crude protein + crude fat + ash + crude fiber) . The data on the dry matter basis indicate that carbohydrates account for one-half to three-quarters (possibly even more) of the dry weight of mushrooms, so they are the largest component of mushrooms. In the group of carbohydrates, a wide variety of compounds can be found, from simple sugars to complex, high molecular weight polysaccharides. We would like to present the above in Table 1, where partly the data of the most important cultivated taxa and partly the data from Kalac's handbook for wild-growing taxa are summarized. In the cases of the three most important cultivated species, the data for total carbohydrate content vary in the range from 50 to 75-85%, and are rarely higher than 90% (Auricularia auricula-judae) or lower than 50% (Tuber aestivum). The same can be established for the other part of Table 1 presenting data on wild species (genera) , but the data there are somewhat lower. Therefore, carbohydrates are a group of substances that make up most of the dry mass of mushrooms. They are characterized not only by their large quantity but also by their structural diversity. This diversity is true not only in a chemical but also in a biological sense, since a simple sugar molecule can be an energy source, a building unit, and a functional element of the cell wall (chitin or glucans). Many are also characterized by the fact that they can act later as various biologically active molecules in a consuming animal or even in humans. The grouping (overview) of the carbohydrates in mushrooms can be reviewed with the help of Figure 1. The main groups are mono-, oligo-, and polysaccharides, where one, a few, or many sugar units are located, respectively. The monosaccharides of mushrooms are sugars with 5 or 6 C atoms; free glucose, fructose, and arabinose molecules are mostly present. Their concentration is usually low or very low. Glucose, as a substrate for energy-producing processes, has a very low concentration at a given moment, and it should be mentioned that sugars are also often used for various biosynthetic processes. Monosaccharide concentrations detected and measured in large mushroom taxa are highly variable; often, the concentration can barely be detected, or it is only a few percent . Among the sugar derivatives, sugar alcohols are very important, especially mannit (mannitol), whose molecules are synthesized from fructose in a two-step process. Its role in the formation and maturation of fruiting bodies is likely as an osmotic regulator, all of which is confirmed by the tendency that the mycelium < primordium < mature fruiting body indicates an increasing concentration of mannitol. The mannitol content of the mycelium is a few percent, while it rises to 20-40% in the mature fruiting body . In the group of oligosaccharides, sucrose (saccharose) is rarely found. The disaccharide trehalose, consisting of two glucoses in a,a-1,1 linkages is a common component of mushroom carbohydrates, and quantities of a few percent have been measured in cultivated mushroom species (the lowest in Agaricus bisporus, the highest in Pleurotus ostreatus fruiting bodies) . Regarding the function of trehalose, recent studies suggest that it can play a protective role against abiotic stress conditions (i.e., heat stress processes increase trehalose content). There are two main groups of polysaccharides: homopolysaccharides, which have the same building blocks, and heteropolysaccharides, which contain several monomers. The main groups of homopolysaccharides are chitin, glycogen, and glucans . Chemically, the chitin molecule is composed of 1,4-N-acetyl-D-glucosamine monomers. Chitin is a water-insoluble, very resistant component of fungal cell walls (all fungi in the Eukaryota kingdom characteristically have chitin-containing cell walls). Our earlier studies contained data and conclusions on the chitin content of many fungi. The cultivated button white mushroom varieties, for example, have 6-8% dry matter (DM), but the rate of chitin contents in pileus and stipes is less than 1.0% (0.8-0.9%). The oyster mushroom contains a significantly lower chitin content (2.15-5% of DM), but the pileus parts contain significantly more chitin than the stipes (chitin of pileus/chitin of stipes: 1.25-1.30). The actual chitin level of a mushroom fruit body seems to be an important factor in its digestibility because the required chitinase activity in the digestive systems of animals and humans is very low. However, the importance of chitin content in nutritional physiology also has another aspect: it forms an important part of the dietary fiber fraction and thus plays a role in ensuring the fiber requirements of normal digestive processes. Glycogen is an interesting member of the group of homopolysaccharides. These molecules have starch-like properties (they are also called animal starch); in the case of mushrooms, they make up 5-15% of the dry matter. Glycogen contents were estimated to be between 2 and 10% (DM) in Lentinula edodes fruit bodies . The measured concentrations were influenced by the spawn source and the characteristics of the environment during cultivation. The immature fruit bodies have lower content than the mature ones. 3. The Mushroom Glucans 3.1. Historical Background The history of learning about glucans is logically intertwined with the ancient events and traditions of the use of mushrooms for medicinal (folk medicine) purposes. In Egypt, mushrooms are called a "gift from the god Osiris", in Rome they are called "foods of the Gods", and the evaluation comes from the Greek world, "elixir of the life". If we look at the empires of the Far East, we also have to remember their very ancient origins: the Ganoderma lucidum species has perhaps the longest history of medicinal use. Very characteristic mushroom names have been developed and persisted: the G. lucidum is known in Japan as reishi (or manetake: 10,000-year-old mushroom); in China, the same mushroom is called ling zhi (mushroom of immortality) . The use of mushrooms in folk medicine was followed relatively late by scientific studies that met the basic criteria of research. The year 1957, when Lucas first demonstrated the anticancer effect of mushrooms, is very notable. Extracts of Boletus edulis and some other mushrooms inhibited the Sarcoma 180 cancer type in mouse tissue; the extract of the fruiting body of Calvatia (now: Langermannia) gigantea significantly reduced the tissue growth of several types of cancer . The study of the fungi that affect the immune system developed in the 1960s and 1970s . The studies, for example, started and continued in two directions. One direction (mainly in the USA, Europe, and Japan) investigated the effects of polysaccharide mixtures (zymosan) isolated from the cell wall of yeast (Saccharomyces cerevisiae). The second direction, which started in Japan, already demonstrated the nonspecific immunomodulating effect of b-glucans for the first time in the case of shiitake . An important fact of the early studies was that the toxicity of the purified mushroom extracts was very low. 3.2. Structural Properties of Glucans Glucans are the most important and abundant constituents of homopolysaccharides. Their basic unit is glucose, so at first glance, their structure is extremely monotonous; however, in reality, the molecular group is characterized by heterogeneity. This heterogeneity manifests itself, for example, in the types of bonds, the size and conformation of the molecules, the degree of branching, etc. and fundamentally affects the biological properties of the molecules as well. Next, we will review the sources, causes, and consequences of the diversity provided by the structure. 3.2.1. Glycosidic Bonds The monosaccharide units are joined by O-glycosidic linkages. Such linkages are formed from the glycosyl moiety of hemiacetal and the hydroxyl group of another monomer. What causes the diversity of the resulting polysaccharides? One factor is that the linkage of the resulting sugar chain can be (1 - 3), (1 - 4), or (1 - 6), where the numbers indicate the carbon atoms involved in the linkage. Another factor is that the resulting sugar chain can be linear or branched to varying degrees. The existence of stereoisomers (the b-configurations) known from sugar chemistry is also very important. The lowest-numbered ring carbon of a pyranose is the anomeric carbon atom. Isomers that differ only in the configuration of the anomeric carbon atom are called anomers. The a-anomer of a D-glucopyranose has an OH group pointing down axially, while the b-anomer has an OH group pointing up equatorially . The stereochemical difference between the b-anomers--it seems--fundamentally affects the biological effect of the molecules, their nature, and their strength (see later). 3.2.2. Monosaccharide Composition In the case of a homomeric structure, the macromolecule is made up of the same monosaccharides, while in the case of a heteromeric structure, several types of monosaccharides make up the molecule in different proportions. Generally, mushroom polysaccharides are composed of glucose, galactose, and mannose, but other sugars can also be found (e.g., arabinose, xylose, fucose, ribose) . In glucans, the constituents are mostly only glucose units, although in some important glucan types, other monosaccharides are also present (the b-(1 - 3)-(1 - 6) glucan of Grifola frondosa contains xylose and mannose, or the pleuran of Pleurotus ostreatus also contains galactose and mannose). 3.2.3. Backbone, Side Chains, Degree of Branching As we saw earlier, the two main groups are linear (without branches) and branched glucans. The main chain is mostly connected by (1 - 3) (1 - 4) bonds, and the side chain(s) are connected by (1 - 6) bonds. The number of branches is well characterized by an indicator, the degree of branches (DB). For example, the DB value in lentinan is between 0.23-0.33, while it is 0.25 for pleuran, 0.31-0.36 for grifolan (from G. frondosa), and 0.36 for schizophyllan. It seems that for biologically active b-glucans, the DB value varies within narrow limits . 3.2.4. Molecular Weight An important property of glucan molecules is their molecular weight. The available data show a high degree of diversity here as well, and there are several reasons for this phenomenon. One reason is that these macromolecules from different species (types) logically differ (can differ) from each other. The other factor is that the methods of determining the molecular weight are constantly evolving and changing; moreover, the different methods are used after very different preparations (e.g., extraction, purification, etc.). This logic also includes, of course, whether there are any changes in the structure, size, etc. of the macromolecule during the application of different method combinations. Taking all of this into account, we must evaluate the available data, bearing in mind that a realistic comparison is only possible for data obtained with the same method. Based on the work of Du and colleagues , we present the limits (in Da) for the molecular weight of some mushroom glucans (Table 2). The table also contains the methods used for the determinations. The determined molecular weights of the glucans isolated from Ganoderma lucidum are in one case on the order of 104-105 Da, while the values from another study are an order of magnitude higher (105-106 Da) (see Table 2). The high degree of variability experienced during the determination of molecular weights is due to differences in the extraction operation and the methods of determination (i.e., the interaction of several factors). All of these must be considered when evaluating and comparing molecular weight values. However, it is a fact that (see later), according to general experience, the biological effect of glucans with a higher molecular weight is usually greater. 3.2.5. Helical Conformation The question of the possible configuration has long been a problem for glucans as well. Bluhm and Sarko (in the mid-1970s) may have been the first to publish their work on the configuration of mushroom glucans (more precisely, lentinan, which was already known at that time) . The lentinan sample was obtained from Japan and examined using the X-ray diffraction method. With the data obtained in this way and theoretical spatial structure analysis, the possibility of simple and multiple helical structures was investigated. Based on the X-ray diffraction data, a hexagonal unit was revealed, where a = b = 15.8 A and c (fiber repeat) = 6 A. The predicted conformation of the molecule had five structural variants: the single helix, two variants of the double helix, and two forms of the triple helix. The right-handed triple helix model is the probable configuration of the investigated lentinan molecule , but it is likely that other mushroom glucans (e.g., from Armillaria mellea) also have the same conformation's structure. Further research on lentinan has provided new information regarding the configuration of glucans in general. It turned out that various structural transitions and transformations can occur; the triple helix conformation can turn into another structure (e.g., into a single helix). The simple chain structure is transformed into a triple helix when lyophilized after dissolution in an 8 M urea solution and dialyzed against distilled water . Lentinan has a triple helix conformation in aqueous solution, while it shows a random coil structure in dimethyl sulfoxide (DMSO) . These authors used atomic force microscopy (AFM) to determine the shape of the lentinan molecule in an aqueous solution. The lentinan molecule in water exhibits wormlike, linear, circular, and crossover types. The triple helix structure of polysaccharides in water is created and maintained by intracellular hydrogen bridges. It is also important that the distinct glucose-containing side chains cause essential differences in the physical properties of glucans. The role of hydrogen bonds created with the help of water molecules is very important in the connection between the main and side chains and between the side chains. The transformation of the configuration of glucan molecules depends significantly on certain factors, such as solvent, temperature, and pH value. Lentinan shows a triple helix structure in aqueous solution, but it irreversibly transforms into a single strand coil in a solvent mixture where the proportion of water is only 0.15 and DMSO is 0.85 at 25 degC . An irreversible helix-coil transition occurs when the concentration of NaOH is between 0.05 and 0.08 M because here the lentinan molecule is denatured . Under certain experimental conditions, the triple helix structure can be reversibly restored (by dialysis on a regenerated cellulose column at 15 degC for 7 days). With the help of heat treatment (130-145 degC), an irreversible conformation change (helix - coil) can also be achieved. If increasing amounts of water are added to lentinan dissolved in DMSO, the chain collapse and aggregation process can be observed in addition to the helix - coil transition. If the ratio of water is 0.1, the molecule exists as a random coil, if the ratio of water is 0.25, the chain shrinks, and if the ratio of water is >0.25, a connection between the collapsed chains is formed, forming quite large aggregates . More recent studies have indicated that the previously presented spatial conformation (triple helix) can be broken down into smaller parts for various reasons that preserve their native chemical properties and spatial structure . Recently, more and more attention is being paid to the methodological possibilities (chemical, enzymatic, and physical methods) with which glucan molecules can be broken down into smaller parts. Certain conformations of glucan molecules show characteristic reactions with certain dyes; for example, the single helix structure of b-(1 - 3) linked polysaccharides can be detected with aniline blue dye . The triple helix structure forms a complex with Congo red dye in an alkaline solution, whereby the strong interaction between the dye and the polysaccharide molecule stabilizes. The absorption maximum of Congo red consequently shifts from 489 nm to 520 nm, all of which enable spectrophotometric quantification (see Section 3.4). 3.2.6. Solubility The solubility of an active substance is a fundamental property because during its operation and effect, it is included in such basic phenomena as stability, emulsifying ability, transport of the active substance, and membrane-forming properties. Thus, the question is: What properties of molecules affect solubility? The review work of Du and colleagues draws attention to some important phenomena. If the molar mass is higher, the solubility decreases, and conversely, if the molar mass decreases for any reason, the solubility can increase significantly. An example of the latter case is when chemical modification takes place on b-glucan molecules (e.g., sulfation), which introduces ionic groups, and smaller fragments are formed from glucan, which increases solubility. Under the influence of gamma radiation, the molecular mass can also radically decrease, leading to an increase in solubility . 3.2.7. Extraction The extraction of mushroom polysaccharides--including various glucans--is an important issue, both in terms of determining the glucan content and isolating, purifying, and then using the molecules. The objects of glucan extraction can not only be the fruiting bodies (or parts thereof) but also the mycelium or even the nutrient medium of the fungus (cultural broth). Since most mushroom glucans are water-soluble, the main possibility is water extraction. Presently, many techniques can help in extraction procedures (ultrasonic-assisted, microwave-assisted, enzyme-assisted, subcritical water extraction, and others ). Conditions for optimal extraction were 94 degC, 10 h extraction time, and ratio of solid to liquid 1:6 . Classical hot water extraction is a simple and feasible method, but there are several drawbacks (relatively long reaction time, high temperature, high energy demand, and relatively low extraction efficiency). Additional problems with the extraction options are whether they lead to the degradation of glucans or to a change in the conformation of molecules, which is important from the point of view of biological effects. The large amount of literature available suggests that the glucans of a given mushroom species should be examined specifically in light of the effects of different extraction factors (e.g., time, temperature, etc.). 3.3. Synthesis The mechanism of b-glucan synthesis is a question under continuous investigation . The overall process of this synthesis is partly like chitin synthesis:The b-glucan chains (approximately 1500 monomers) are produced in the cytoplasm. Later, these chains are transferred to the periplasmic space with the help of a transmembrane enzyme complex . The chain's structure can be modified in the periplasmic space. For the resistant cell wall structure, b-(1 - 6)-glycosidic side branches are required, the rate of which is approximately 3-10% of the total number of glycosidic linkages. These side chains can connect several b-(1 - 3) glucan chains together . The abovementioned processes are multi-step: the first reaction level is initiation, followed by elongation of the chain and then formation of the branches, which is a crucial step. Among the mentioned phases, the chain extension step is the most well-known, where the sugar donor uridine diphosphoglucose (UDPG) molecules deliver the new sugar unit, and the enzyme is 1,3-glucan synthase (GLS) (EC. 2.4.1.34). The process of glucan synthesis has already been investigated in more detail in the cases of some important large mushroom species (e.g., Pleurotus, Agrocybe/today: Cyclocybe/Lentinula edodes, Auricularia auricula-judae, etc.). During the reaction, the GTP molecules are activated (with the use of UTP and the formation of UDP); then, the UDPG molecules are connected to the already existing glucan chain in the enzyme complex located on the cell membrane. The enzyme complex has a hydrophilic loop responsible for catalyzing the chain extension reaction. The assumed mechanism also includes other catalytic molecules (proteins) . GLS enzymes known from fungi are characterized by variable substrate specificity, with an optimal pH between 5.8 and 7.8, an optimal temperature between 20 and 37 degC, and the fact that mainly divalent cations (Mg2+, Ca2+, Fe2+) can play a role in enzyme activity stimulation or inhibition. The value of the Michaelis constant (KM) of the enzyme complex seems to depend strongly on the species from which the enzyme was isolated. In summary, it can be concluded that GLS, the main enzymatic participant in glucan biosynthesis, is an enzyme that shows a high degree of heterogeneity . 3.4. Determination of Glucan Contents In the first decade of our century--due to the increased interest in beta-glucans--it became increasingly necessary to develop and compare determination methods. 3.4.1. Enzymatic Method Bak and colleagues applied the so-called enzymatic method. The authors used an enzyme kit (Megazyme, Ireland), which consists of exo-1,3-b-glucanase, b-glucosidase, amyloglycosidase, and invertase enzymes, as well as components necessary for glucose determination (glucose-oxidase, peroxidase, and 4-aminoantipyrine). During the measurement of the total glucan content, the mushroom samples were hydrolyzed in 37% HCl for 45 min at 30 degC and then at 100 degC for 2 h. After neutralization, the glucose was hydrolyzed with 1,3-b-glucanase and b-glucosidase in Na-acetate buffer (pH = 5) for 1 h at 40 degC, and then the absorbance of the solution was measured at 510 nm. The alpha-glucan content was determined after hydrochloric acid hydrolysis with other enzymes: amyloglucosidase and invertase. The b-glucan content was calculated: b-glucan = total glucan-a-glucan content. The authors performed the enzyme method combination on mushroom mycelium, fruiting body cap, and stipe samples in 10 shiitake varieties. Sari and his workgroup analyzed many cultivated and wild mushrooms, mainly in fractionated form for caps and stipes. Their method was the enzymatic analysis described above, but the a-glucan content was measured after hydrolysis in 2 N KOH solution (based on the advice of the enzyme manufacturer). 3.4.2. Congo Red Method In 2011, Molleken developed a method that is based on the reaction between Congo red dye and glucans with a triple helix structure, so it is specific for b-1,3-1,6 glucans, which have a spatial structure that is suitable for determining their quantity in each mushroom or in mushroom preparations . The enzymatic (Megazyme) and Congo red methods were used in parallel to compare the b-glucan content of 18 wild and three cultivated mushroom species, which is also suitable for comparing the methods . The meta-analysis of their data points out (Table 3) that there is a significant difference between the data sets of the two methods; the b-glucan content obtained using enzymatic analysis is on average two and a half times higher than the data obtained using the Congo red method. If the samples of wild mushrooms are compared separately, the smallest difference is found in Lactarius deliciosus (1.61 times), while the largest is defined in Cantharellus cibarius (the data obtained using the enzyme method is 27.6% of DM, while the data obtained using the Congo red method is only 1.94%, i.e., the difference is 13.3 times based on the data of ). For the three cultivated mushroom species (Table 4), the enzyme method indicates a more than three times higher amount of glucan (for Agaricus bisporus, Pleurotus ostreatus, and Lentinula edodes, the differences are 3.64, 3.25, and 3.12 times higher, respectively) . The above data emphatically underline that the comparison of the glucan content of mushrooms is only possible with data sets obtained by the same method. The importance of the question and the interpretation of the data are also great because the real comparison and standardization of mushrooms, mushroom preparations, and food supplements require a uniform methodological background. 3.5. Glucan Contents of Mushrooms The data on the a-, b-, and total glucan contents of mushrooms are quite limited (compare with what was explained in Section 3.4), so their evaluation requires attention. Data from Sari provide an opportunity to evaluate and meta-analyze the glucan contents of the caps and stems of the studied wild and cultivated species (Table 5 and Table 6). According to the summary of the data from the wild species, the total glucan content of the caps was lower than that measured in the stipes (cap average: 22.07% DM, stipe average: 29.50% DM), while the a-glucan content showed no clear difference between the caps and the stipes. The minimum and maximum values of the glucan content showed a very wide range, which is especially true for the values measured in the stipes. If we examine the original data table, according to the examined species, we also find one or two outstanding and interesting data. For example, the very low glucan content of Xerocomellus chrysentheron or the fact that the stipe of Boletus edulis has very high glucan parameters (total glucan: 63.3% DM, b-glucan: 57.3% DM). We worked out (based on ) the proportion of the glucan fractions of caps and stipes (Table 7). The a-glucan fractions occurred in essentially the same amount in the stipe and the cap (ratio: 0.91 and 0.98); for total glucan contents, the stipes contained approximately 30-40% more glucans than the caps. The fruiting bodies of the wild taxa and the three cultivated mushrooms had essentially the same proportions. A recent publication from Ciric examined the b-glucan content of food supplements containing different mushrooms, using the previously mentioned and presented enzymatic method . The average b-glucan content of the 10 tested types of food supplement capsules was 18.45% DM; the lowest measured value was 5.5%, and the highest glucan content was 37.5% DM (the latter capsule contained Ganoderma lucidum powder and shiitake extract powder). In the previously cited work by Bak , the a-, b-, and total glucan content of 10 varieties of Lentinula edodes (shiitake) were examined in the mycelia, cap, and stipe of the varieties using the already presented enzymatic (Megazyme) method. On average, shiitake varieties contain a significant amount of total and b-glucan in the cap (39.1% and 35.9%, respectively). The mycelia of the varieties have a significantly lower glucan content, but here, the amount of a-glucan is relatively the highest (total: 27.4%; b-glucan: 22.2%). The reported data are also interesting because they indicate that not only the two parts of the fruiting body--the cap and the stipe--but also the parts of the mycelium and fruiting body are significantly different. It seems that the amount of glucan increases significantly during the development of the fruiting body, since the ratio of total glucan contents for mycelium:cap:stipe = 100:161.7:199.6. The b-glucan contents of mushrooms can be influenced by different factors, such as the drying and blanching processes. The fruiting bodies of shiitake mushrooms were dried at 35, 45, and 55 degC, and drying at 60 degC already reduced the amount of the soluble fraction. The drying temperature of 55 degC was found to be optimal because it had the shortest drying time . The process of blanching is important among preservation treatments, as it inactivates decomposing enzymes, pre-shrinks, removes air, reduces oxidative changes, differentiates microbial populations, reduces cooking time, etc. . During an examination of 11 Thai mushroom species, the authors concluded that the blanching process generally decreased a-glucan while increasing b-glucan. 3.6. Presentation of the Most Important Glucans 3.6.1. Lentinan The source of lentinan is the fruiting body and mycelium of the Lentinula edodes (shiitake) mushroom. It was first isolated by Chihara's group in 1970 . The sugar chain of glucan consists of (1 - 3)-b-D-glucopyranoside units, and two (1 - 6)-b-D-glucopyranoside side chains are attached to every five such sugar units . The degree of branching (DB) value of the molecule is between 0.33 and 0.5. The molecular weight of lentinan was initially measured as 9.5-10.5 x 105, and then with another method, it was found to be lower, in the range of 3-8 x 105 . The molecular weight of the glucan fractions from shiitake--according to recent data--varies between 300 and 800 kDa, with an average of 500 kDa. The configuration of the molecule is as follows: in aqueous solution, the H-bridges form a triple helix structure, while the configuration is a random coil when dissolved in DMSO . Among the diverse and multifaceted biological effects of lentinan, the anticarcinogenic (antitumor) and immune system stimulating and activating effects are decisive. The first scientific document about its anticarcinogenic effect was published on the effect against Sarcoma 180 (although a series of folk medicine and historical records indicated the possibility of an antitumor effect, especially in Far Eastern societies). The literature of the last few decades has reported somewhat incomprehensive detail and investigation (not only of lentinan but also of other mushroom glucans). postoperative therapy with lentinan can be effective against cancer recurrence and metastases after surgical treatment . The variety of data and observations logically raises questions about the mechanism of the effect. The discussion of the question focuses on several possibilities:Does direct inhibition of the growth of cancer cells occur (i.e., is there a direct anticarcinogenic effect)? Does the molecule exert its effect indirectly, through stimulation of the immune system? Is there a preventive effect in relation to the spread and migration of cancer in the body? In general, the activation of immune cells is the most important step in the indirect effect of lentinan. Studies indicate that under the influence of lentinan, cells release cytokines that serve as signal messengers. The increase in cytokine production by immune cells has been investigated in animals and humans . Data suggest that lentinan can increase the ability of certain immune cells to slow down or destroy cancer cells in humans. As a result of lentinan treatment, more nitric oxide is produced, which stimulates the immune system. Immune activation capacity can also be related to regulation by hormonal factors. In summary, lentinan can suppress the growth of cancer cells or even kill cells directly through various pathways of immune system activation . In the literature, several authors have created complex models of the antitumor effects of lentinan (see the relevant literature ). In the case of lentinan (and other mushroom polysaccharides), much attention has been paid for a long time to the possibility and nature of the correlations between the physico-chemical properties and biological effects of the molecules. If, for example, the triple helix configuration of the lentinan changes or collapses, the molecule partially denatures, and the anticarcinogenic effect decreases. In general, there is a connection between the biological effects and the integrity of the molecular structure. Substances with higher molecular weights are generally more effective than smaller ones. Beta-glucans entering the human gastrointestinal tract (including lentinan) show good resistance to gastric juice. They enter the small intestine unchanged, where they bind to macrophage receptors in the intestinal wall and are then transported to the spleen, lymph nodes, and bone marrow . In macrophages, the large b-glucans are broken down into smaller molecules, which can bind to the complement receptors of immune cells. This ultimately strengthens the immune response against tumor cells. The interactions between b-glucans and immune cells are very complicated, and not all connections are known. However, it is known that the common receptor Dectin-1 is activated and then the amount of reactive oxygen species (ROS), which acts against pathogenic microorganisms, increases. The receptor stimulates the production of various cytokines . The mechanism of action of glucans includes additional receptors (TLRs/Toll-like receptors), complement receptor type 3 (CR3), and the scavenger receptor (Src). The essence of the effect of glucans can therefore be described by the fact that they activate cellular and humoral responses of the immune system through different receptors. Regarding the antitumor and cytotoxic effects of glucans, the mechanism remains partially unexplored. According to the latest literature and sources , it has not been proven that glucans exert a direct cytotoxic or apoptotic effect against cancer cells. Although one publication refers to the direct cytotoxic activity of some glucans (e.g., in the case of liver cells ), recently the more likely assumption is that glucans exert their antitumor (usually anticancer) effect through the immune system. 3.6.2. Pleuran This molecule was isolated in the early 1990s from Pleurotus ostreatus (oyster mushroom), noting that bioactive glucans have also been isolated from many other species of the Pleurotus genus (P. eryngii, P. florida, P. pulmonarius, P. tuber-regium, P. sajor-caju, and P. ostreatoroseus) . Glucose molecules are bound with (1 - 3)-b-bonds in the chain, and every four molecules are connected to glucose with a (1 - 6)-b-bond. The molecular weight of pleuran ranges between 600 and 700 kDa . Among the biological effects of pleuran are the antitumor effect, the reduction of blood lipid level, and the stabilization of carbohydrate homeostasis. It has also been shown to have antifungal properties, an increase in antioxidant potential, and an anti-inflammatory effect . The clinical and immunomodulatory effects of pleuran were investigated by Urbancikova and co-workers . Active treatment with pleuran caused a significantly shorter duration of herpes simplex virus (HSV-1) symptoms. The severity and length of respiratory symptoms were lowered in the treated patient group compared to the placebo group. No side effects were observed during the clinical experiments. The results suggest that pleuran is a suitable molecule for the treatment of acute HSV-1 infection. The respiratory tract symptoms changed very favorably. In recent work by the above-mentioned authors , it has been confirmed that pleuran application is effective in preventing respiratory infections (recurrent respiratory tract infections/RRTIs). This method is suitable as a strategy for improving immune functions in young populations. 3.6.3. Bioactive Molecules from Grifola frondosa (Maitake) The habitats of this mushroom are the temperate forests of Europe, Asia, and North America. This species has different English names: hen-of-the-woods, king of mushrooms, sheep's head, etc. Grifola frondosa is a delicious mushroom, with a pleasant, sweet smell, which can be explained mainly by the high content of trehalose, glutamine, aspartic acid, and 5'-nucleotides. In addition to its nutritional value, the mushroom also has a variety of pharmacological effects. The antitumor effect of extracts made from the fruiting body with hot water was already demonstrated in the 1980s, and the b-glucans of the mushroom are the main factors in this effect. In the last 30 years, 47 bioactive polysaccharide fractions have been isolated and purified from the fruiting body, mycelium, or cultivation medium of this mushroom . The mushroom contains 3.8% water-soluble polysaccharides, of which 13% is (1 - 3) (1 - 6)-b-D-glucan. In addition, heteroglucans and heteroglucan-protein complexes are also present. The so-called D (or its purified version is MD) fraction and grifolan are perhaps the most well-known fractions, but Wu's work draws attention to the tabular presentation of nearly 31 different bioactive molecules. b-glucan from fraction D contains (1 - 6) chains with (1 - 3) side chains and (1 - 3) chains with (1 - 6) side chains. Gel-forming grifolan (GRN) molecules have immunomodulatory effects. The antitumor effect of the mushroom was first described by Miyazaki and his colleagues forty years ago against the Sarcoma 180 cancer type in mice . The experiences of the past 30 years have led to the fact that the main possibilities of the mushroom's anticancer effect can be formulated as follows: protection of healthy cells, protection against tumor metastases, and inhibition of tumor growth. In other words, the direct and indirect effects of the mushroom against tumors occur through the stimulation of the immune system. Today, it is also known that the D-glucan fraction of maitake can be used orally, intravenously, and intraperitoneally (many other antitumor polysaccharides are ineffective when used orally). According to experiments conducted with the D-fraction of maitake , it is effective in cases of breast, liver, and lung cancers but less effective in other cancers. According to a recent summary by Wu , the immune-modifying effect of maitake was confirmed by several tests. The mushroom's bioactive substances act on macrophages, cytotoxic T cells, and natural killer (NK) cells and stimulate cytokines and other signaling molecules (interferons (IFN), interleukins (IL), and tumor necrosis factors (TNF)). Biological influences include antiviral and antibacterial effects (hepatitis B, enterovirus 71, the herpes simplex virus (HSV-1), and the HIV virus). In connection with the almost epidemic spread of diabetes, it is worth drawing attention to the effects of maitake on sugar metabolism. This effect is partly related to the activity of insulin and partly to the inhibition of a-glycosidase activity; the latter process slows down the hydrolysis of starch and thus lowers the blood sugar level . 3.6.4. Schizophyllan (from Schizophyllum commune) This glucan was first isolated from a non-edible, plant-parasitic fungus, Schizophyllum commune (split-gill mushroom), by Kikumoto and co-workers . This white-rot mushroom grows on dead or decaying wood and is distributed on all continents (except Antarctica). The main chain of the glucan monomer consists of three (1 - 3) linked glucoses, and a glucose unit is connected to the middle sugar by (1 - 6) bonds . The molecular mass is between 100 and 200 kDa, although some sources mention a significantly higher molecular weight (4300 kDa) . The molecule shows a triple helix conformation in aqueous solution, similar to lentinan . Schizophyllan is a water-soluble and extracellular polysaccharide. For its production, different strains of Schizophyllum commune are used that have different wastes of lignocellulose character, such as rice hull hydrolysate, corn fiber, date syrup, carboxymethyl-cellulose, and different sugars (e.g., glucose, sucrose, etc.) . Schizophyllan was found to control the growth of Sarcoma 180 tumors. It was tested and used (mainly in Japan) against head and neck cancer, resulting in improved patient survival . Different clinical trials have been performed in Japan. These studies combined schizophyllan with conventional chemotherapy (tegafur, 5-fluoroacid, and other molecules) and were applied to 367 patients with recurrent, inoperable gastric cancer. An increase in the survival rate was demonstrated . In other studies, longer overall survival rates of head and neck cancer-related patients were achieved and documented . Positive results were reported in another randomized, clinical trial (following surgery, radiotherapy, chemotherapy, and schizophyllan in various combinations) . The above results indicate that the anticancer effect of schizophyllan exoglucan appears to be achieved in "synergism" with traditional, classic treatments. The biological activity of schizophyllan can be changed and improved by ultrasonic treatment of the molecule . Ultrasonic-treated schizophyllan caused an increase in nitric oxide production by macrophages and enhancement of the proliferation rate of lymphocytes. This represents a completely new and different application of schizophyllan when recently a composite of the molecule and silver nanoparticles was prepared . This composite has been found to be a new potential possibility for certain biomedical applications (mainly for wound healing). The silver nanoparticles, binding with schizophyllan (through a non-covalent but strong linkage), can lead to good dispersion of silver particles within the matrix of the biopolymer . 3.6.5. Krestin (Crestin, Polysaccharide-K, PSK) The krestin heteroglucan was isolated from the fruiting body of Trametes (Coriolus) versicolor (turkey tail). Since the glucan structure is connected to proteins, it is a proteoglucan (protein content between 25 and 38%) . Its molecular weight is approximately 100 kDa. Its main sugar component is glucose, but it also contains small amounts of mannose, fucose, galactose, and xylose . There are (1 - 3) bonds between the units of the glucan backbone, a side chain is connected to every fourth glucose unit by (1 - 6) bonds, and the protein parts are covalently linked to (1 - 6) side chains. The mushroom was discovered for modern science and medicine in 1965. PSK (Poly-Saccharide-Kurahe = krestin) was discovered and patented in 1969 and commercialized in Japan in 1977. Chemical tests measured a high glucan content (61%) in the mushroom, 99.3% of which was b-glucan . The effects of Trametes glucans: According to in vitro studies, the extracts of the mushroom, PSK and PSP (another isolated proteoglucan: Poly Saccharo Peptide), have cytotoxic effects against tumor cell lines. The mortality of patients suffering from various types of cancer improved significantly, and a relationship between survival without deterioration and Trametes preparations was found. PSK, for example, has been proven to be effective in the treatment of stomach, esophageal, colon, rectal, and lung cancer in doses of 3-6 g per day for 1 year, according to clinical trials . PSK is usually added to chemotherapy after surgery; a comprehensive scientific overview was given by Kidd . The proteoglycan isolated from Trametes (PSP) significantly reduced various side effects in cancer patients (e.g., loss of appetite, weakness, dry mouth, strong heartbeat, insomnia, short, rapid breathing, malaise, vomiting, and night sweats). In other words, the number of patients with no side effects increased significantly . Krestin has also successfully been used in veterinary science for adenosarcoma, fibrosarcoma, mastocytoma, melanoma, mammary cancer, colon cancer, and lung cancer . 3.7. Relationships between Structure and Biological Effects Glucans are physiologically active compounds; they are called biological response modifiers (BRMs). Thanks to the properties of BRMs, they can often act as remedies or adjuvants, for example, in bacterial or viral infections, or they can also be effective against tumors . The structure of effective b-glucans usually means a (1 - 3)-b-D-glucose chain molecule in which some glucose units are randomly connected with (1 - 6) b-bonds. Molecules with significant antitumor activity have a degree of branching (DB) value between 0.2-0.3 (lentinan, schizophyllan), while molecules with a lower or higher DB value are less effective. In the case of native b-D-glucans, the sugar chain has a triple helix structure, parts of which can be combined with simple or double chains. The antitumor effect of schizophyllan is characterized by a triplex helix structure and a molecular weight greater than 100 kDa. The triple helix (created by three H bonds at the C-2 position) configuration appears to exist only in glucans of a higher molecular weight. Around and below 25-40 kDa, the molecule exists only as simple fibers (chains) in aqueous solution . There are also contrary opinions on the relationship between structure and effect. Some data, for example, also describe a significant antitumor effect in the case of glucans with a small molecule and a non-branched structure . Therefore, the question of structure-effect correlations can still be considered open today, which clearly warrants further research. 4. Conclusions This review summarizes the mycological, chemical, and biological aspects of mushroom glucans. The glucans (the heteroglucans) are significant components of the fungal cell wall. They are composed of sugar (mostly glucose) chains, where typical glycosidic bonds form the linear or even branched structure. The special configuration of b-glucans and the integrity of this triple helix structure seem essential for the molecule's biological effects. Among the main biological impacts of glucans are antitumor (anticarcinogenic) and immune-stimulating effects. Some types of glucans can also be associated with other groups of effects (e.g., antidiabetic, antioxidant properties, etc.). From a mycological point of view, it is important that not only the fruiting bodies but also the mycelium and even the growing medium containing the fungus can be utilized and can be sources of glucans. Effective glucan content is (can be) present not only in edible species but also in inedible taxa (Ganoderma lucidum, Schizophyllum commune) as well, and they can also be used and even cultivated as raw materials to produce glucans. In several fields of medicine (e.g., oncology and immunology), the importance and possibilities of mushroom glucans are very promising. What tasks can be set for researchers in the field for the future? It would be necessary to clarify, develop, and standardize the determination methods available today (measuring the glucan content of existing preparations using a clear method and, at the same time, standardizing the preparations). Laboratory and then industrial application methods for the extraction and purification of different glucan types should be investigated. The produced molecules can be used in laboratories and then in clinical experiments. Most glucans can also be involved in the prevention of diseases, which, of course, also requires an attitude toward development. The solution of all these tasks requires cooperative interdisciplinary research. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement This publication is a review article. Conflicts of Interest The author declare no conflict of interest. Figure 1 The groups of mushroom polysaccharides. Figure 2 The structures of the b-D-glucopyranose isomers (anomers). Figure 3 Structure of lentinan, the main glucan of Lentinula edodes (shiitake). Figure 4 The schizophyllan glucan from Schizophyllum commune (split gill mushroom). foods-12-01009-t001_Table 1 Table 1 Total carbohydrate contents of some cultivated and wild-growing mushroom taxa . Cultivated Mushrooms Carbohydrate Content (% of DM) * Wild Growing Taxa Carbohydrate Content (% of DM) Agaricus bisporus white button mushroom 50.9-74.0 Agaricus species 37.5-65.0 Agaricus subrufescens almond mushroom 39.0-64.0 Amanita species 49.1-72.0 Pleurotus ostreatus oyster mushroom 51.9-85.2 Armillaria mellea honey fungus 63.0-80.2 Pleurotus eryngii king trumpet mushroom 70.5-81.4 Boletus edulis penny bun 55.0-70.9 Lentinula edodes shiitake 67.1-87.0 Cantharellus cibarius golden chantarelle 31.3-72.0 Flammulina velutipes golden needle mushroom 56.6-86.2 Coprinus comatus shaggy ink cap 49.4-76.3 Coprinus comatus shaggy ink cap 76.5 Flammulina velutipes golden needle mushroom 70.9 Auricularia auricula-judae jelly ear 77.2-91.0 Lactarius deliciosus saffron milk cap 61.0-77.2 Volvariella volvacea straw mushroom 52.3 Lepista (Clitocybe) nuda wood blewit 65.9-71.0 Ganoderma lucidum reishi, lingzhi, lacquered bracket fungus 82.3 Macrolepiota procera parasol mushroom 70.3-81.0 Tuber aestivum summer truffle 48.9 Pleurotus ostreatus oyster mushroom 65.4-70.6 * Dry matter = DM. foods-12-01009-t002_Table 2 Table 2 Molecular weights of different glucans determined by several methods (or by a combination of methods) . Source of b-Glucan Methods of Determination * Molecular Weight (Da) Saccharomyces cerevisiae SEC-RI 2.79 x 104-21.75 x 105 Schizophyllum commune HPLC-MALLS-RI 8.8 x 105-2.4 x 106 Schizophyllum commune HPLC-RI 1.97 x 105-2.9 x 106 Schizophyllum commune HPLC-RI 2.9 x 106 Ganoderma lucidum HPSEC-MALLS-RI-VS 2.9 x 105-2.42 x 106 Ganoderma lucidum SEC-LLS-RI 5.7 x 104-4.45 x 105 Lentinus velutinus HPGPC 3.36 x 105 Pleurotus ostreatus GPC 3.3 x 104 Pleurotus djamor NMR 1.61 x 105 Agaricus bisporus HPGPC 7.84 x 105 * HPLC: high performance liquid chromatography; MALLS: multiangle laser light scattering method; RI: refractive index detector; SEC: size-exclusion chromatography; HPSEC: high performance size exclusion chromatography; HPGPC: high performance gel permeation chromatography; GPV: gel permeation chromatography; NMR: nuclear magnetic resonance; LLS: laser light scattering; VS: viscosity detector. foods-12-01009-t003_Table 3 Table 3 b-glucan contents of 18 wild-growing mushrooms determined using the Megazyme and Congo red methods . Analyzed Samples and Method of Analyses Arithmetical Mean % of DM +- SD Min-Max Value % of DM b-glucan content of 18 wild-growing mushrooms assayed using the Megazyme method 24.81 +- 5.98 10.50-34.97 b-glucan content of 18 wild-growing mushrooms assayed using the Congo red method 10.03 +- 4.47 1.95-17.10 foods-12-01009-t004_Table 4 Table 4 b-glucan contents of three commercial cultivated mushrooms species analyzed by two methods . Mushroom b-Glucan with Megazyme Method (% DM) b-Glucan with Congo Red Method (% DM) The Rate of the Found Glucan Contents Agaricus bisporus white button mushroom 11.36 +- 2.85 3.11 +- 0.10 3.64 Pleurotus ostreatus oyster mushroom 40.34 +- 3.23 12.39 +- 1.10 3.25 Lentinula edodes shiitake 26.26 +- 3.23 8.42 +- 0.63 3.12 foods-12-01009-t005_Table 5 Table 5 Average glucan (all, a, and b) contents in caps and stipes of 23 mushroom samples and the distribution of data (minimum and maximum values based on data of ). Mushroom Samples (n = 23) Arithmetical Mean (% of DM +- SD) Min.-Max. Values (% of DM) Cap--All glucan content (Pileus)--a-glucan content b-glucan content 22.07 +- 6.60 3.35 +- 3.26 18.29 +- 6.09 9.90-34.1 0.65-14.9 7.08-33.5 Stipe--All glucan content a-glucan content b-glucan content 29.50 +- 11.78 3.05 +- 2.68 26.38 +- 11.30 14.33-63.31 0.45-12.1 13.09-57.90 foods-12-01009-t006_Table 6 Table 6 Average glucan (all, a, and b) contents in caps and stipes of three cultivated taxa (in % of DM) . Cultivated Species All Glucans a-Glucan Content b-Glucan Content Cap Stipe Cap Stipe Cap Stipe Agaricus bisporus--white--average +- SD 10.05 +- 2.22 14.96 +- 4.9 1.54 +- 0.38 2.66 +- 1.22 8.68 +- 2.37 12.29 +- 4.07 Agaricus bisporus--brown--average +- SD 12.34 +- 4.5 14.64 +- 4.87 3.51 +- 2.38 4.15 +- 2.84 8.83 +- 3.04 10.07 +- 2.23 Lentinula edodes--shiitake--average +- SD 20.5 +- 5.95 26.74 +- 3.95 0.76 +- 0.40 1.44 +- 0.85 19.77 +- 6.23 25.30 +- 4.38 All cultivated taxa--average +- SD 14.40 +- 5.32 18.78 +- 6.89 2.79 +- 2.05 2.75 +- 1.35 12.42 +- 6.35 15.88 +- 8.22 foods-12-01009-t007_Table 7 Table 7 Glucan rates from stipes and caps in wild-growing (n = 23) and three cultivated mushrooms, analyzed on data of . 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PMC10000500 | Background: The total marrow and lymph node irradiation (TMLI) target includes the bones, spleen, and lymph node chains, with the latter being the most challenging structures to contour. We evaluated the impact of introducing internal contour guidelines to reduce the intraobserver lymph node delineation variability in TMLI treatments. Methods: A total of 10 patients were randomly selected from our database of 104 TMLI patients so as to evaluate the guidelines' efficacy. The lymph node clinical target volume (CTV_LN) was recontoured according to the guidelines (CTV_LN_GL_RO1) and compared to the historical guidelines (CTV_LN_Old). Both topological (i.e., Dice similarity coefficient (DSC)) and dosimetric (i.e., V95 (the volume receiving 95% of the prescription dose) metrics were calculated for all paired contours. Results: The mean DSCs were 0.82 +- 0.09, 0.97 +- 0.01, and 0.98 +- 0.02, respectively, for CTV_LN_Old vs. CTV_LN_GL_RO1, and between the intraobserver contours following the guidelines. Correspondingly, the mean CTV_LN-V95 dose differences were 4.8 +- 4.7%, 0.03 +- 0.5%, and 0.1 +- 0.1%. Conclusions: The guidelines reduced the CTV_LN contour variability. The high target coverage agreement revealed that historical CTV-to-planning-target-volume margins were safe, even if a relatively low DSC was observed. TMLI guidelines radiotherapy interobserver variability contour definition clinical target volume conditioning regimen leukemia Italian Ministry of HealthGR-2019-12370739 This work was supported by grant AuToMI (GR-2019-12370739, funded by the Italian Ministry of Health). pmc1. Introduction Total body irradiation (TBI) is a radiotherapy (RT) treatment that was developed in the late 1950s with the aim of increasing engraftment in bone marrow transplantation and facilitating the eradication of leukemic cells in acute myeloid leukemia, acute lymphoblastic leukemia, and in other hematologic malignancies . The target of TBI is the whole body, thus exposing the patient to the risk of developing acute and late toxicity in the healthy tissues, especially in pediatric patients and in adult patients with comorbidities . Over the years, the use of TBI has decreased due to (i) the long-term toxicities, (ii) the need for specific medical expertise, and (iii) the technical peculiarities of performing this complex treatment (a dedicated bunker, organ shielding devices, patient positioning, etc.). Furthermore, various therapeutic alternatives have emerged, such as chemotherapy-only myeloablative and reduced-intensity conditioning regimens, due to the discovery of the graft-versus-tumor effect in the context of allogeneic hematopoietic stem cell transplantation . A recent phase III trial demonstrated the significant benefit of radiation in addition to chemotherapy in the pretransplant conditioning regimen, with a better overall survival of 0.91 compared to 0.75 at 2 years for patients who received chemo conditioning alone, as well as a lower incidence of relapse and treatment-related mortality . The introduction of helical tomotherapy, intensity-modulated radiation therapy (IMRT), and later, volumetric modulated arc therapy (VMAT) techniques allowed the increasing of the dose conformity to the target while sparing the dose to the organs at risk (OARs) . Intensity-modulated techniques were evaluated as replacements for standard TBI to irradiate hematopoietic tissue with a potential toxicity reduction to OARs . Such approaches are referred to as total marrow and lymph node irradiation (TMLI) . The TMLI target volume is defined as the patient's bones, spleen, and lymph nodes. The definition of the clinical target volume (CTV) is crucial to performing an adequate treatment with intensity-modulated techniques. In particular, the delineation of the CTV of the lymph node chains (CTV_LN) is extremely complex and time-consuming due to its greater volume compared to standard RT treatments. Moreover, the definition of CTV_LN is more subject to observer variability since, typically, only a small number of patients with TMLI are treated each year in a few reference centers, resulting in a lack of multicenter studies. Currently, there is no globally accepted consensus for the delineation of lymph node chains in TMLI, with studies in the literature usually referring to the inclusion of generic "major lymph node areas". The clinical choice to exclude certain lymph node chains should take into account the expected toxicity for some sites, as already suggested for Waldeyer's ring and the mesenteric lymph nodes . In this study, we contoured the lymph node chains, starting from well-established international guidelines for specific regions, and we evaluated the impact of the introduction of internal contouring guidelines on the reduction of TMLI CTV_LN contour intravariability. 2. Materials and Methods 2.1. TMLI Procedure Since 2010, in our center, 114 patients with pathologically proven hematological malignances, who had been identified as candidates for allogeneic transplantation, were treated with nonmyeloablative conditioning TMLI, with a prescribed dose of 2 Gy (1 fraction) . All TMLI patients were immobilized in the supine position with arms along the body using an in-house, dedicated frame with multiple personalized masks . For each patient, a free-breathing noncontrast computed tomography (CT) scan with a slice thickness of 5 mm was acquired using a BigBore CT system (Philips Healthcare, Best, Netherlands). All TMLI plans were optimized for a VMAT technique and delivered on a TrueBeam LINAC (Varian Medical Systems, Palo Alto, CA, USA) . The VMAT-TMLI plans were generated using either the progressive resolution optimization (PROIII v13) or the photon optimization (PO v15) algorithms (Varian Medical Systems), depending on the version available in the clinic at the time of the treatment. All dose calculations were performed using the Analytical Anisotropic Algorithm (AAA v.11-15). The TMLI CTV included the bone marrow (CTV_BM), the spleen (CTV_Spleen), and all lymph node chains (CTV_LN). In our center, the CTV_BM was considered to be equal to the skeletal bones, adding the chest wall to the ribs to account for breathing motions. The mandible was excluded from the CTV_BM to reduce toxicity to the oral cavity, as were the hands since they have an extremely limited bone marrow presence. The total planning target volume (PTV_Tot) was defined as the Boolean operator "union" of three PTVs, obtained from the isotropic expansion of three corresponding CTVs, specifically: (i) PTV_BM = CTV_BM + 2 mm (+8 mm for arms and legs) to account for setup margin; (ii) PTV_Spleen = CTV_Spleen + 5 mm to account for breathing motions and setup margin; and (iii) PTV_LN = CTV_LN + 5 mm to account for target residual motion and setup margin. Plans were normalized to PTV_Tot-D98% = 98% (i.e., 98% of PTV_Tot should receive 98% of the prescription dose). The lenses, eyes, brain, lungs, heart, kidneys, bowels, stomach, liver, rectum, and bladder were defined as OARs, and doses to these structures were minimized in the optimization process, following the ALARA (as low as reasonably achievable) principle. To adequately cover the PTV_Tot, a multi-isocenter approach was adopted for the plan optimization, using 5 isocenters for a total of 10 full arcs (360deg). The collimator angle was set to 90deg, with an asymmetric jaw aperture in the cranial-caudal direction, and a maximum aperture (~40 cm) in the left-right direction. Each arc overlapped with the adjacent ones for at least 2 cm to minimize the dose distribution uncertainty due to a potential patient misalignment. We refer to other studies for the full description of the protocol . 2.2. Target Definition Guidelines For the first 104 TMLI patients, the CTV_LN was delineated by different radiation oncologists (ROs) using a nonwritten agreement. In March 2022, a group consisting of the referent RO for the hematological diseases, two experienced ROs, an RO in training, and a hematologist, established written internal guidelines for the delineation of CTV_LN. The present study collected several recommendations for each anatomical district. The criteria for CTV_LN delineation strictly followed international guidelines and lymph node CT atlas recommendations, including those from (i) Radiation Therapy Oncology Group (RTOG) ; (ii) International Association for the Study of Lung Cancer ; (iii) Offersen et al. ; (iv) Gregoire et al. ; and (v) Lengele et al. . In the target definition, a few lymph node chains, i.e., the most peripheral, were omitted from the target due to their lower involvement rate and in order to reduce potential toxicities. Due to the lack of consistent studies in the literature, this decision was based on our internal clinical experience and the consideration of a few other experiences as well . The lymph node levels selected for each anatomical site are summarized in Table 1. 2.3. Guideline Evaluation This study was divided into two parts. Initially, the agreement between the historical and the new CTV_LN contours was evaluated. Then, intraobserver variability was assessed for CTV_LN contoured following the guidelines. A total of 10 patients were randomly selected (1 per year) from our internal database. A single expert radiation oncologist (RO1) recontoured the CTV_LN according to the guidelines (CTV_LN_GL_RO1). These new contours were compared to the historical lymph node target delineation (CTV_LN_Old). The guidelines' efficacy in reducing interobserver variability was prospectively assessed in, respectively, four and six patients. In detail, the CTV_LN_GL were re-contoured two times in blind mode, with a minimum interval of 2 months, by the same RO (CTV_LN_GL_RO1a and CTV_LN_GL_RO1b) to evaluate the guidelines' intravariability, and by two independent ROs (CTV_LN_GL_RO1 and CTV_LN_GL_RO2) to evaluate the guidelines' intervariability. Each CTV_LN was split into four regions so as to investigate specific differences, including: H&N, thoracic, abdominal, and pelvic areas. The sample was subdivided into three comparison groups (see Table 2): Group A (before vs. after guidelines' introduction), Group B (interobserver variability), and Group C (intraobserver variability). 2.4. Data Analysis The contours were compared by evaluating topological and dosimetric indexes. 2.4.1. Topological Evaluation The CVT_LN volumes, Dice similarity coefficient (DSC) values, mean distance-to-agreement (Mean DA), and Hausdorff distance (HD) were extracted for each case using an in-house script integrated into the RayStation Doctor (RaySearch Laboratories, Stockholm, Sweden) treatment planning system (TPS). 2.4.2. Dosimetric Evaluation For the retrospective and prospective patients, the VMAT plans were optimized using, respectively, the CTV_LN_Old and CTV_LN_GL_RO1 as part of the PTV_tot used for the optimization (see Section 2.1). Many dose-volume points were analyzed for each CTV_LN contour to assess the target coverage and guidelines' consistency. In particular, the percentage of dose received by a specific percentage of volume (i.e., D90, D80) and the percentage of volume reached by a specific percentage of the prescription dose (i.e., V95, V90) were computed. Data were extracted using an in-house script developed for the Eclipse (Varian Medical System) TPS. 2.4.3. Statistical Tests Comparisons between the contour groups were performed using the Mann-Whitney test, while the Wilcoxon matched-pairs signed-rank test was used to compare dose-volume points between plans for the same patient. The threshold for statistical significance was set to p < 0.05. The analysis was performed using Python v 3.10.4 and the SciPy v 1.8.1 library. 3. Results 3.1. CTV_LN Inter-/Intraobserver Contouring Variability A total of 250 structures were analyzed. An example of target contouring before and after the introduction of the guidelines is shown as a representative case along with axial slices in Figure 1 and with coronal-sagittal views in Figure 2. In Figure S1 of the Supplementary Materials, a case with a partial chain miss in the H&N region is reported. The mean CTV_LN volumes after the guidelines' introduction increased from 2176 +- 600 cm3 to 2370 +- 672 cm3, due to the larger head and neck, gastric, and mediastinal lymph node delineation after the guidelines' introduction (see Table 3). The full topological analysis is reported in Table 4. For the retrospective patients, the CTV_LN mean DSC was 0.82 +- 0.09. The worst DSC result (0.69 +- 0.15) was observed for the H&N district. The thoracic lymph node contours showed a moderate variability, with a DSC of 0.77 +- 0.15, often caused by the sum of small differences in the delineation, especially for the hilum of the lung and between the mediastinal vessels. Finally, the abdominal and pelvic level delineations presented better reproducibility, with DSCs of, respectively, 0.82 +- 0.08 and 0.88 +- 0.09. Nonetheless, an uncertainty in delineating the gastric and bilateral inguinal lymph node regions was observed. In the prospective intraobserver variability analyses, the mean DSCs were, respectively, 0.97 +- 0.01 and 0.98 +- 0.01, demonstrating an overall increase in contour agreement. The H&N region was the most affected by interobserver variability, leading to the lowest mean DSC, 0.88 +- 0.04. Mean DA and HD analyses confirmed the results of the DSC evaluation, with mean values of A being much larger than those of B or C. However, high standard deviations were observed for the mean DA and HD when compared to their respective mean values. 3.2. Target Coverage and Dose Distribution The full dosimetric analysis is reported in Table 5. The V95 for CTV_LN_GL_RO1, CTV_LN_Old, CTV_LN_GL_RO2, and CTV_LN_GL_RO1b were, respectively, 94 +- 5%, 99 +- (<0.5)%, 99 +- 1%, 99 +- (<0.5)%, corresponding to CTV_LN-V95 dose differences of, respectively, 4.8 +- 4.7%, 0.3 +- 0.5%, and 0.1 +- 0.1%. Dose-coverage differences were significant in the Group A comparison, while no significant difference was observed within the intraobserver variability groups (i.e., Groups B and C). Regarding the lymph node subregions, the V95 was >99% in all areas for Groups B and C, revealing the optimal dosimetric agreements after the introduction of the guidelines. On the contrary, the V95 values for Group A presented a large spread, ranging from 99% for the thorax and pelvis regions, to 91% and 89% for the H&N and Abdominal regions. For these two last cases, the V90 values increased by 2%. 4. Discussion Phase I and II trials that included TMLI as part of the conditioning for bone marrow transplantation demonstrated encouraging engraftment, achieving full donor chimerism, a low incidence of graft-versus-host disease, and low extra-hematologic toxicities . A controversial issue regarding TMLI organ sparing is a possible increase in extra-medullary relapses as compared to TBI. According to Kim et al., the only significant predictor of posttransplantation extra-medullary recurrence was the occurrence of this diffusion behavior before the transplantation . Furthermore, the location of the relapse was not dose-dependent and could occur both in-field and out-field. Therefore, according to these findings, TMLI should not be linked to a higher incidence of extra-medullary relapse. Several studies confirmed that RT is fundamental for hematological diseases, and they encouraged further improvements of TMLI treatment. This can be pursued both through technological developments and through the advancement of human knowledge. Particularly within the RT workflow, contouring remains a challenging and time-consuming task. To the best of our knowledge, this is the first study to investigate intraobserver variability in TMLI contouring. TMLI is a highly modulated technique; therefore, target delineation is crucial. The variability in bone and spleen definition could be considered negligible, while CTV_LN delineation is subject to greater uncertainty. For this reason, in our hospital, we adopted a larger margin for the CTV_LN-to-PTV_LN expansion (5 mm), as compared to that of the bones (CTV_BM-to-PTV_BM, 2 mm). These margins were based on an internal analysis of the first patients included in the trial. For the spleen, the expansion of 5 mm in the three directions was performed to preserve lung function. The spleen is, in fact, subject to respiratory movements, which may require margins greater than 5 mm in the cranial-caudal direction. In our experience, the union of the PTVs (which, in addition to the spleen, includes the PTV_LN and the PTV_bones) allowed for complete coverage of the caudal region of the spleen in all of our treated patients, while for the cranial part, our clinical choice was to spare the left lung to limit pulmonary toxicity, accepting a possible limited uncovering of the spleen dome. A potential approach to reducing operator-dependent uncertainty is to introduce an auto-segmentation tool, which has the advantages of harmonizing the contours and reducing manual segmentation variability. In a recent study regarding TMLI auto-segmentation techniques, a DSC of 0.73 +- 0.01 between manual and automatic segmentations for CTV_LN was reported , while in our analysis, the DSC, before and after the introduction of the guidelines, was higher (0.82 +- 0.09). In particular, the H&N district is confirmed to have high observer variability due to its anatomical complexity. Despite the worse agreement with manual contours, auto-segmentation approaches showed lower standard deviations (i.e., lower variability). However, an auto-segmentation tool needs robust contours for its training. To this aim, consensus guidelines could increase the consistency of the approach, potentially facilitating its applicability. Many studies showed that the introduction of guidelines helped to reduce intraobserver variability in CTV delineation in different anatomical regions . In particular, the DAHANCA, EORTC, GORTEC, HKNPCSG, NCIC CTG, NCRI, NRG Oncology, and TROG consensus guidelines highlighted the clinical benefit of reducing interobserver variability through the implementation of training courses, the adoption of guidelines, and the proper use of the imaging examinations . In the historical 3D-conformal planning approach, the target contouring variability had a minor impact on the dosimetric plan consistency due to the low intrinsic conformal dose to a concave target. Therefore, in this case, the introduction of target contouring guidelines would have benefits that were not as clear. New modulated delivery techniques, such as IMRT and VMAT, can irradiate a highly conformal dose distribution to the target volume while sparing neighboring healthy tissues. Lobefalo et al. showed that the introduction of guidelines in rectum cancer (i.e., a concave target) increased the mean PTV-V95 by 9.0% using a VMAT technique, while an increase of only 3.1% was observed for a classical "box" RT . Therefore, modulated techniques applied to complex targets, such as TMLI, should benefit from an accurate and homogeneous definition of the target, reducing the delineation variability and improving the dose coverage. Despite the absence of established international guidelines, the use of our written internal consensus allowed us to reduce CTV_LN intravariability, both in terms of topological and dosimetric indexes. The direct estimation of the CTV_LN contour consistency before the guidelines' introduction was not possible. However, the greater DSC standard deviation for Group A (0.09) compared to Groups B (0.01) and C (0.02) is an indirect confirmation of the lower contour consistency. Furthermore, the DSC was significantly different for the A vs. C (p < 0.01) and A vs. B Groups (p = 0.03), as a possible consequence of low CTV_LN consistency in Group A. On the contrary, no significant difference was observed for Group B vs. Group C, showing low intravariability with the guidelines. The Group A vs. Group B comparison was significant only for the whole CTV_LN volume, while the nonsignificant values for the CTV_LN levels could be caused by the subjectivity in defining the cranial-caudal boundary and by the patients' characteristics. For this reason, a comparison of CTV_LN districts between different patients with relatively different anatomies has a lower level of accuracy and is affected by greater uncertainty. Areas with lower dose coverage were the most affected by the nonhomogeneity of lymph node delineation before the introduction of the guidelines. Specifically, the abdominal region resulted in a poor D90 = 92%, while the D80 = 102%. A possible explanation of the low D90 value could be the delineation of perigastric lymph nodes that were not systematically included before the guidelines' introduction. Furthermore, the greater reproducibility in the delineation of the main lymph node chains is a possible consequence of the clear visualization on CT scans of the aorta, the iliac vessels, and their branches. The dosimetric analysis showed that the retrospective treatment plans were clinically acceptable, despite the significant difference in dose coverage for Group A (the V95 dose difference in Group A was 4.8 +- 4.7%), and it revealed that the low CTV_LN delineation reproducibility (DSC = 0.82 +- 0.09) did not affect the overall plan quality. This is a possible consequence of the CTV-to-PTV expansion, as well as of the composition of the PTV_Tot (union of three overlapping PTVs), which decreases the impact of intravariability. Nonetheless, our data indicate that the use of guidelines can allow a reduction of the CTV_LN-to-PTV_LN margins for TMLI treatments. Finally, the introduction of multi-imaging-based contouring is another possible approach to reducing intravariability . This study was part of the AuToMI project, the aim of which is to spread the use of TMLI by improving clinical practices and introducing new, automated tools . Further investigation will address the impact on workload due to the introduction of these internal guidelines and the application of automated segmentation tools. Moreover, a parallel study is currently underway to further decrease lymph node contouring uncertainty using co-registered, whole-body magnetic resonance imaging to enhance the CTV_LN individuation. A few limitations should be taken into consideration when interpreting the results of this study. First, as this is a monocentric study, the generalizability of our findings to other institutions might be limited. Second, the definition of the lymph node chains was not based on an international consensus specific to TMLI, but on several international guidelines and our internal experience. Therefore, we do not recommend them as the definitive standard. However, our approach could be a useful starting point for specifying which major lymph node areas should be included in TMLI, and we suggest that international efforts should be made to standardize the definition of lymph node chains for this treatment. Finally, we did not use contrast media CT series, which may improve the definition of lymph node chains. Due to the frailty of transplant candidate patients and their susceptibility to radio-related renal toxicity, we preferred to avoid the use of iodine-based agents. 5. Conclusions This study revealed that the CTV_LN-to-PTV_LN historical margins were safe. The introduction of guidelines reduced the interobserver variability in CTV_LN delineation and dose coverage, which could potentially support lymph node margin reduction in future TMLI treatments, thus reducing the dose to healthy tissues. Acknowledgments The authors would like to thank Stefania Zara (Tecnologie Avanzate, Turin, Italy) for helping with the topological data extraction. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Partial chain miss. Click here for additional data file. Author Contributions Conceptualization, D.D. and P.M.; Data curation, D.D., N.L., S.S., V.V., G.R. and P.M.; Funding acquisition, S.T., M.S. and P.M.; Methodology, D.D., N.L. and P.M.; Project administration, P.M.; Resources, G.R., S.T., M.S. and P.M.; Software, N.L., R.C.B., L.C. and D.L.; Supervision, M.S. and P.M.; Visualization, D.D.; Writing--original draft, D.D. and P.M.; Writing--review and editing, D.D., N.L., S.S., V.V., R.C.B., L.C., E.C., L.B., C.D.P., D.L., P.N., G.R., S.B., M.R., S.T., A.C., C.C.-S., M.S. and P.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of IRCCS Humanitas Research Hospital (ID 2928, 26 January 2021). ClinicalTrials.gov identifier: NCT04976205. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Axial view of CTV_LN contouring for every anatomical district, before (green segmentation) and after (red segmentation) the guidelines' introduction. Figure 2 Coronal and sagittal views of CTV_LN contouring, before (green segmentation) and after (red segmentation) the guidelines' introduction. cancers-15-01536-t001_Table 1 Table 1 Lymph nodes included in the CTV_LN, divided per anatomical site. Region Lymph Nodes H&N VIIa + VIIb + II + Ib + V + III + Ia + VIa + VIb + IVa + IVb axilla I + II + III + IV mediastinum 1-8 + 10 abdomen I + II + III pelvis I-VII + superficial and deep groin cancers-15-01536-t002_Table 2 Table 2 Scheme of the comparisons performed in this study. CTV_LN Comparison Comparison Abbreviation Explanation GL_RO1 vs. Old A After-GL vs. before-GL GL_RO1 vs. GL_RO2 B Inter-observer-variability GL_RO1a vs. GL_RO1b C Intra-observer-variability Legend: "GL_RO1": contour performed by an expert RO after the introduction of the guidelines; "Old": contour performed before the guidelines; "GL_RO2": contour performed by a second expert RO after the introduction of the guidelines; "RO1a" and "RO1b": two contours performed by the same expert RO after the introduction of the guidelines. cancers-15-01536-t003_Table 3 Table 3 CTV_LN and lymph node substructure volume analysis, before and after the guidelines' introduction; the minimum and maximum values are reported in parentheses. Before GL [cm3] After GL [cm3] CTV_LN_Tot 2176 +- 600 [1312-3194] 2370 +- 672 [1412-3511] CTV_LN_H&N 332 +- 128 [197-558] 559 +- 111 [180-544] CTV_LN_Thorax 501 +- 178 [254-801] 532 +- 200 [265-853] CTV_LN_Abdominal 710 +- 196 [454-1057] 721 +- 260 [582-1407] CTV_LN_Pelvis 612 +- 175 [350-898] 590 +- 177 [349-871] Legend: CTV_LN: lymph node clinical target volume; GL: Guidelines. cancers-15-01536-t004_Table 4 Table 4 Topological analysis of CTV_LN for each comparison group: (A) before vs. after guidelines' introduction; (B) interobserver variability; (C) intraobserver variability. DSC p-Value (DSC) Mean DA [mm] HD [mm] LN levels A B C A vs. B A vs. C B vs. C A B C A B C Tot 0.82 +- 0.09 0.97 +- 0.01 0.98 +- 0.02 0.03 <0.01 1.00 0.4 +- 0.2 0.1 +- 0.1 0.03 +- 0.02 7 +- 1 2 +- 2 1.9 +- 0.3 H&N 0.69 +- 0.15 0.88 +- 0.04 0.96 +- 0.03 0.27 <0.01 0.13 0.5 +- 0.4 0.1 +- 0.1 0.02 +- 0.01 7 +- 7 2 +- 1 0.9 +- 0.3 Thorax 0.77 +- 0.15 0.97 +- 0.01 0.97 +- 0.02 0.18 0.02 1.00 0.5 +- 0.5 0.1 +- 0.2 0.03 +- 0.01 6 +- 7 2 +- 2 1.4 +- 0.5 Abdomen 0.82 +- 0.08 0.98 +- 0.01 0.97 +- 0.01 0.05 0.02 0.35 0.7 +- 0.4 0.1 +- 0.2 0.03 +- 0.01 8 +- 6 1 +- 2 1.6 +- 0.6 Pelvis 0.88 +- 0.09 0.96 +- 0.01 0.95 +- 0.03 0.27 0.16 0.80 0.2 +- 0.2 0.1 +- 0.2 0.06 +- 0.04 3 +- 2 1 +- 1 1.6 +- 0.5 Legend: CTV_LN: lymph node clinical target volume; DA: distance-to-agreement; DSC: Dice similarity coefficient; HD: Hausdorff distance. Significant p-value results of Mann-Whitney test for DSC comparisons between groups are highlighted in bold. cancers-15-01536-t005_Table 5 Table 5 Dosimetric parameter analysis for each comparison group: (A) before vs. after guidelines, (B) interobserver variability, (C) intraobserver variability. The values reported are normalized to the prescribed dose. D90 D80 CTV_LN A B C A B C RO1 Old RO1 RO2 RO1a RO1b RO1 Old RO1 RO2 RO1a RO1b Tot 1.01 +- 0.11 1.03 +- 0.06 1.04 +- 0.02 1.04 +- 0.02 1.04 +- 0.01 1.04 +- 0.01 1.04 +- 0.06 1.05 +- 0.05 1.06 +- 0.02 1.060.02 1.06 +- 0.01 1.06 +- 0.01 H&N 0.98 +- 0.09 1.03 +- 0.05 1.05 +- 0.02 1.05 +- 0.02 1.04 +- 0.01 1.04 +- 0.01 1.03 +- 0.06 1.05 +- 0.05 1.08 +- 0.02 1.08 +- 0.02 1.06 +- 0.02 1.06 +- 0.02 Thorax 1.03 +- 0.09 1.04 +- 0.07 1.05 +- 0.02 1.05 +- 0.02 1.04 +- 0.02 1.04 +- 0.02 1.05 +- 0.07 1.05 +- 0.07 1.07 +- 0.02 1.07 +- 0.02 1.06 +- 0.02 1.06 +- 0.02 Abdomen 0.92 +- 0.18 1.03 +- 0.07 1.03 +- 0.02 1.03 +- 0.01 1.04 +- 0.01 1.04 +- 0.01 1.02 +- 0.11 1.05 +- 0.07 1.05 +- 0.02 1.06 +- 0.01 1.05 +- 0.01 1.05 +- 0.01 Pelvis 1.04 +- 0.06 1.04 +- 0.06 1.06 +- 0.02 1.06 +- 0.02 1.06 +- 0.02 1.05 +- 0.02 1.05 +- 0.06 1.06 +- 0.06 1.07 +- 0.02 1.07 +- 0.02 1.07 +- 0.02 1.07 +- 0.02 V95 V90 A B C A B C CTV_LN RO1 Old RO1 RO2 RO1 RO1b RO1 Old RO1 RO2 RO1 RO1b Tot 0.94 +- 0.05 0.99 +- (<<) 0.99 +- (<<) 0.99 +- 0.01 1.00 +- (<<) 0.99 +- (<<) 0.96 +- 0.04 1.00 +- (<<) 0.99 +- (<<) 0.99 +- (<<) 1.00 +- (<<) 1.00 +- (<<) H&N 0.91 +- 0.05 0.99 +- 0.01 0.99 +- 0.01 0.99 +- 0.01 0.99 +- (<<) 0.99 +- (<<) 0.93 +- 0.04 1.00 +- (<<) 0.99 +- (<<) 1.00 +- 0.01 1.00 +- (<<) 1.00 +- (<<) Thorax 0.99 +- 0.05 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 0.99 +- (<<) 0.99 +- 0.03 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) Abdomen 0.89 +- 0.09 1.00 +- (<<) 1.00 +- 0.01 1.00 +- 0.01 1.00 +- (<<) 1.00 +- (<<) 0.91 +- 0.08 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) Pelvis 0.99 +- 0.03 1.00 +- (<<) 1.00 +- (<<) 1.00 +- 0.01 1.00 +- (<<) 0.99 +- (<<) 0.99 +- 0.03 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) 1.00 +- (<<) Legend: "+- (<<)": standard deviation <0.005; "GL_RO1": contour performed by an expert RO after the guidelines' introduction; "Old": contour performed before the guidelines; "GL_RO2": contour performed by a second expert RO after the guidelines' introduction; "RO1a" and "RO1b": two contours performed by the same expert RO. In bold are highlighted values for which the Wilcoxon signed-rank test between groups had a p-value < 0.05. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000501 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050983 diagnostics-13-00983 Case Report Multisystem Inflammatory Syndrome in Adults Associated with Recent Infection with COVID-19 Zahornacky Ondrej Porubcin Stefan Rovnakova Alena Jarcuska Pavol * Yehuda Shoenfeld Academic Editor Department of Infectology and Travel Medicine, Faculty of Medicine, Louis Pasteur University Hospital, Pavol Jozef Safarik University, 04190 Kosice, Slovakia * Correspondence: [email protected]; Tel.: +421-55-615-2202 04 3 2023 3 2023 13 5 98331 1 2023 14 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Multisystem inflammatory syndrome in adults (MIS-A) is an uncommon but severe and still understudied post-infectious complication of COVID-19. Clinically, the disease manifests itself most often 2-6 weeks after overcoming the infection. Young and middle-aged patients are especially affected. The clinical picture of the disease is very diverse. The dominant symptoms are mainly fever and myalgia, usually accompanied by various, especially extrapulmonary, manifestations. Cardiac damage (often in the form of cardiogenic shock) and significantly increased inflammatory parameters are often associated with MIS-A, while respiratory symptoms, including hypoxia, are less frequent. Due to the seriousness of the disease and the possibility of rapid progression, the basis of a successful treatment of the patient is early diagnosis, based mainly on anamnesis (overcoming the disease of COVID-19 in the recent past) and clinical symptoms, which often imitate other severe conditions such as, e.g., sepsis, septic shock, or toxic shock syndrome. Because of the danger of missing the treatment, it is necessary to initiate it immediately after the suspicion of MIS-A is expressed, without waiting for the results of microbiological and serological examinations. The cornerstone of pharmacological therapy is the administration of corticosteroids and intravenous immunoglobulins, to which the majority of patients clinically react. In this article, the authors describe the case report of a 21-year-old patient admitted to the Clinic of Infectology and Travel Medicine for febrility up to 40.5 degC, myalgia, arthralgia, headache, vomiting, and diarrhea three weeks after overcoming COVID-19. However, as part of the routine differential diagnosis of fevers (imaging and laboratory examinations), their cause was not clarified. Due to the overall worsening of the condition, the patient was transferred to the ICU with suspicion of developing MIS-A (he met all clinical and laboratory criteria). Given the above, reserve antibiotics, intravenous corticosteroids, and immunoglobulins were added to the treatment due to the risk of missing them, with a good clinical and laboratory effect. After stabilizing the condition and adjusting the laboratory parameters, the patient was transferred to a standard bed and sent home. COVID-19 infection multisystem inflammatory MIS-A This research received no external funding. pmc1. Introduction Multisystem inflammatory syndrome was first described as a nosological entity in 2020, initially mainly in a group of pediatric patients (as MIS-C). Later, the first cases of this disease also began to appear in a group of adult patients (MIS-A). In adults, the clinical course is extremely variable, with primarily febrile, systemic inflammation, often with signs of shock and organ involvement. Therefore, the differentiation from Kawasaki disease is necessary as part of the differential diagnosis, especially in pediatric patients . The pathophysiology of the disease still needs to be precisely discovered. The SARS-CoV-2 coronavirus induced a dysregulated pathological immune response in the host, resulting in systemic vasculitis and multiple acute organ damage . Complement activation with subsequent capillary deposition of immunocomplexes also comes into consideration . Diagnosing the disease is quite challenging due to its varied clinical symptomatology. According to the Centers for Disease Control (CDC), several basic criteria must be met to be diagnosed with MIS-A. MIS-A is defined as a severe illness requiring hospitalization for more than 24 h in persons aged 21 years or older or an illness ending in death based on clinical and laboratory signs. The most important clinical symptom is a fever above 38 degC (subjective or documented fever) for >=24 h prior to a hospitalization or within the first three days of hospitalization; moreover, at least three of the following clinical criteria must occur prior to hospitalization or within the first three days of hospitalization. At least one must be a primary clinical criterion (Table 1) . Primary clinical criteria Serious involvement of the heart: myo-, pericarditis, dilatation or aneurysm of the coronary arteries, or new dysfunction of the right or left ventricle, atrioventricular block II.-III. degree or ventricular tachycardia; rash and nonpurulent conjunctivitis. Secondary clinical criteria Newly developed neurological signs and symptoms: encephalopathy in a patient without previous cognitive deficit, convulsions, meningeal symptoms, peripheral neuropathy; Shock or hypotension not caused by medication (sedation); Abdominal pain, vomiting, diarrhea; Thrombocytopenia. Laboratory evidence: evidence of SARS-CoV-2 infection, elevation of inflammatory markers Elevated value of at least two of the following: C-reactive protein (CRP), ferritin, IL-6, erythrocyte sedimentation rate, procalcitonin (PCT); Positive test for SARS-CoV-2 during illness using RT-PCR, serology, or antigen detection. 2. Case Report A 22-year-old patient, who was not treated for anything prior to testing, was examined at the outpatient department of the infectious disease clinic for fever lasting 3 days with a maximum temperature of up to 40.2 degC, as well as myalgia, arthralgia, headache, a dry cough with dyspnea, and vomiting. The patient reported neutrophilia, lymfophenia, or thrombocytopenia. Neutrophils: 93.2%; Lymphocyte 3.30%; Platelets 51 x 109/L He describes the clinical course of the COVID-19 disease as a mild-subfebrile dry cough. The patient was vaccinated once against COVID-19. The patient had a meningeal skin free of pathological efflorescences, was seized, objectively febrile (40.0 degC), cardiopulmonary compensated (104/70 mmHg), tachycardic (regular heartbeat, frequency 129/min.), without lymphadenopathy, and was otherwise unremarkable at the initial examination (SOFA score 2). The results of the lungs' ultrasonography (USG) test were negative for pathological abnormalities, and there were no further anamnesis or epidemiological results (unprotected sexual contact, including sex with men, contact with an infectious disease, IV drug addiction, tattooing, piercing, stay in nature, source of water and food, a bite of a tick, etc.). Due to the general condition, the patient was admitted to the infectious disease clinic with a fever of unknown origin. The nasopharynx was tested using PCR for COVID-19 at the entry, and the results showed a positive result and a ct cycle of 33.54, which was considered a requirement for recovering from PCR influenza A/B negative. On admission, an electrocardiogram (ECG) assessment was recorded, which described sinus tachycardia without ischemic or other pathological changes. The results of the initial laboratory tests first indicate a viral aetiology of the disease; therefore, complex symptomatic treatment was started. As part of the differential diagnosis of the febrile state, a host of serological examinations were carried out, and blood cultures were taken repeatedly. Regarding influenza PCR A/B negative, the supplemented ultrasound examination of the abdomen describes only mild splenomegaly. After two days of hospitalization, fever persisted, thrombocytopenia worsened, and IL-6 and CRP increased (Table 1). Diarrhea and abdominal pain appeared in the clinical picture. A microbiological examination of the stool did not detect an infectious agent (cultivation, detection of antigen of viruses and Clostridioides difficile toxin). For leukopenia in the differential blood count (3.30 x 109/L), individual subpopulations of lymphocytes were also examined. The number of CD4 + T lymphocytes was critically low (CD4 + 0.10 x 109/L, CD3 + 0.14 x 109/L, CD8 + 0.04 x 109/L, natural killers 0.02 x 109/L), which is why we also considered human immunodeficiency virus (HIV) infection as part of the differential diagnosis. Due to the danger of not receiving therapy, a combination anti-infective regimen that includes the prophylaxis of opportunistic infections (cefotaxime, metronidazole, co-trimoxazole, fluconazole, and azithromycin) is recommended. Over the next 2 days, fevers up to 40 degC persisted, and dyspnea with hyposaturation (sp O2 92%), hypotension, and tachycardia appeared. A maculopapular exanthema appeared on the chest, and eyelid edema and nonpurulent conjunctivitis appeared. Control ultrasonography of the lungs was performed, and it revealed confluent B-lines on both sides, sinus tachycardia and bigeminal ventricular extrasystoles on the ECG, worsening thrombocytopenia in the lab , and an increase in inflammatory markers (CRP, IL-6, PCT), as well as troponin T and NTproBNP (Table 1). Antibodies against HIV are repeatedly negative (ELISA test) (Table 2). An echocardiographic examination was performed acutely based on the suspicion of perimyocarditis, without pathological findings. Due to the deterioration of the clinical condition, the patient was transferred to the intensive care unit to monitor vital functions based on the suspicion of the development of MIS-A (SOFA score 5). After an overall evaluation of the condition, the patient met the criteria necessary for diagnosing MIS-A (primary and secondary). Intravenous immunoglobulins in a cumulative dose of 2 g/kg (130 g in total) and methylprednisolone in a dose of 1 mg/kg (5 days in total) were added to the treatment; due to the impossibility of excluding another etiology of the disease, especially septic shock, the antibiotic treatment was changed to piperacillin/tazobactam with gentamicin. A high-resolution computed tomography (HRCT) examination of the chest was also performed due to the deterioration of the findings on the USG of the lungs, as well as dyspnea and a decrease in saturation. This examination revealed dorsally situated pleural effusions reaching a width of 25 mm in the anteroposterior plane with a predominance on the right, along with discrete subsegmental dyslectases existing on the effusions, fluidopericard of up to 19 mm with and without morphological signs of pneumonia caused by bacteria, viruses, or pneumocystis, without interstitial lung edema, and without cardiac undercompensation in the event of a probable myopericarditis . A hematologist was consulted to facilitate a decrease in the number of platelets, who ruled out hemolytic-uremic syndrome and thrombotic thrombocytopenic purpura. Immunomodulation treatment included consultation with an immunologist, who recommended the continuation of the applied treatment without change. In case of the progression of the condition, he recommended adding biological treatment, i.e., anakinra or infliximab. The patient's condition improved upon receiving the aforementioned treatment: the fever subsided, and laboratory parameters improved . Considering the highly suspicious MIS-A, the favorable clinical and laboratory effect of the administered immunomodulating treatment, and after ruling out a focal bacterial infection (laboratory and imaging methods), we ended the antibiotic treatment. The examination was completed by an internist, who identified a sinus rhythm without ventricular extrasystoles using an electrocardiogram (EKG). He recommended adding colchicine to the treatment due to the use of HRCT on the lungs, as well as fluidopericarde, and suspected myopericarditis (first day 1 mg, then 0.5 mg for a total of 2-3 months, depending on the condition), for which he recommended bisoprolol (5 mg daily); moreover, the magnetic resonance of the heart was supplemented to rule out myocarditis definitively. However, this examination method is not available in our hospital. Therefore, the patient was booked as an outpatient in another city for this examination. After stabilizing the patient's general condition and adjusting laboratory parameters, the patient was discharged to outpatient care after 22 days of hospitalization. He continued oral treatment with methylprednisolone with a gradual dose reduction, as well as with beta-blocker and colchicine. Moreover, he continued to be consulted by a cardiologist, immunologist, and internist. Ambulatory examination of the heart was conducted using magnetic resonance imaging. Morphologically, both ventricles and atria were observed without dilatation and hypertrophy, pericardium without thickening, and a discrete pericardial effusion of up to 5 mm was detected. In the T2 short-TI inversion recovery (STIR) sequence, in midventricular anteroseptal located in segment 8, there was a zone of slightly increased signal-residual inflammatory changes without an evident ventricular kinetics disorder. The appropriate values of the T1 times are shown in the T1 maps. In the T2 maps, in segment 8, T2 times were slightly increased to a maximum of 66 ms (the rest of the myocardium up to 50 ms), at rest perfusion without an observable perfusion disorder, after the administration of a contrast agent (gadolinium) without pathological enhancement in the myocardium, as well as without the presence of scar or fibrosis in the borderline systolic left ventricular function (ejection fraction 52%, end-diastolic volume 169 mL, end-systolic volume 81 mL) . 3. Discussion Multisystem inflammatory syndrome represents a potentially life-threatening complication upon infection with COVID-19, the pathophysiology of which is not yet fully understood. The syndrome was first described in April 2020 in a group of children whose clinical symptoms resembled Kawasaki disease. Later, similar cases began to appear in adult patients, called MIS-A . The interval between viral infection and the development of MIS-A varies in length (2-6 weeks), but it can be clinically manifested already during an acute SARS-CoV-2 infection. That is why it is unclear whether this is a manifestation of an acute infection or a post-infectious syndrome . The clinical symptoms of the disease are diverse. Most of the patients described in the case reports had similar symptoms to the patient from our case report. Patel et al. published a review of 221 patients with MIS-A worldwide. In this group of patients, the disease developed an average of four weeks after acute COVID-19 infection. The median age of patients in the monitored group was 21 years (19-34 years), 70% were men, and 58% had no other comorbidities. The main symptoms of MIS-A were fever (96%), hypotension (60%), cardiac dysfunction (54%), dyspnea (52%), and diarrhea (52%). Moreover, 57% of patients were admitted to the ICU, 47% required respiratory support, and 7% of patients with MIS-A died after hospital admission. Most patients with MIS-A (90%) had increased coagulopathy or inflammatory markers. The authors concluded that MIS-A with extrapulmonary multiorgan involvement was difficult to distinguish from both acute biphasic COVID-19 and the postacute sequelae of SARS-CoV-2 infection . Behzadi et al. reported that men predominate in the case reports, the majority without any comorbidities. Fever and exanthema were among the most common clinical signs, while gastrointestinal clinical signs such as nausea, abdominal pain, and diarrhea were less frequently described . In our case, high temperatures, headaches, myalgia, arthralgia, and a dry cough dominated. During hospitalization, nonpurulent conjunctivitis, maculopapular exanthema on the chest, and elevated laboratory markers of inflammation (CRP, PCT, IL-6) appeared. Diarrhea and abdominal pain in the patient described by us occurred only for 3 days, with spontaneous resolution after symptomatic treatment. The extrapulmonary manifestations of the disease progressed relatively quickly. Tachycardia with hypotension and dyspnea, in the laboratory, increased in TnT, and thrombocytopenia was added to the clinical picture. The clinical symptoms were reminiscent of septic shock, which necessitated the transfer of the patient to the intensive care unit. Mazumder et al. and Kobe et al., in their published case reports, described cases of MIS-A with a severe course that was complicated by the development of disseminated intravascular coagulopathy. In the case described by us, this complication did not develop during hospitalization (despite two positive criteria, namely, D-dimer and platelets, ISTH score: 3) . Based on the clinical symptoms and laboratory results, the diagnostic reliability of our clinical case (Table 3) (according to the Brighton Collaboration definition for MIS-A and MIS-C) is level 1 (definitive case, Table 3) . It is reported in the literature that MIS-A is often associated with cardiovascular damage, the manifestation of which is most often tachycardia, hypotension, and possibly a shocking state with a documented disorder of the ejection fraction of the left ventricle . The same clinical signs of cardiovascular system involvement were also present in the case report described by us. However, the clinical condition did not progress to shock, and treatment with vasopressors was not necessary for an early diagnosis of the disease and the rapid initiation of adequate treatment. Magnetic resonance of the heart is an imaging modality that is often mentioned in the literature and is mainly used for the diagnosis of myocarditis in MIS-A. The examination can confirm the presence of the diffuse inflammation of the myocardium and, at the same time, rule out another cause of its damage, such as ischemic or stress-induced cardiomyopathy . In our case, the MRI examination of the heart was performed only one month after the patient was discharged to outpatient care (due to the unavailability of the examination in our city). Nevertheless, it was possible to capture the midventricular anteroseptal zone of a slightly increased signal as a sign of residual inflammatory changes in the myocardium and the borderline systolic function of the left ventricle. DeCuir et al. reported that inflammatory involvement of the myocardium and a reduction in the left ventricular ejection fraction occurs in up to 66% of patients with MIS-A . Yao et al. reported that most patients with MIS-A had a negative PCR test for the presence of the SARS-CoV-2 virus at the initial examination. They emphasized that it is essential to enquire about recently overcome viruses as part of the differential diagnosis of hyperinflammatory conditions, given that a significant part of COVID-19 infections is either subclinical or asymptomatic. Equally beneficial is the serological examination of antibodies against the SARS-CoV-2 virus . In our case, the patient had a positive PCR test for the presence of SARS-CoV-2 in a high ct cycle during the initial examination. We considered this result a condition after overcoming the disease in the recent past, which the patient also confirmed in their anamnestic response. Therefore, precisely because of PCR positivity has recently been shown as proof of overcoming the infection, we did not perform a serological test for anti-SARS-CoV-2 antibodies. Several treatment options for MIS-A are described in the literature. According to the analysis results by Kunal et al., who investigated the treatment of MIS-A in a total of 79 patients, steroids (60.2%) and intravenous immunoglobulins (37.2%) were most often used in the treatment. Only about 10% of patients required biological treatment . In our case, the patient was initially adequately resuscitated with fluids to maintain adequate perfusion of the tissues. Then, broad-spectrum antibiotics were administered due to the danger of missing the patient, since it was not possible to exclude with certainty another cause of the described condition, especially septic shock (even though it was very unlikely from a clinical point of view, as no focal infection was proven, and the results of the performed microbiological and imaging examinations were negative). Finally, when the condition worsened, and the MIS-A criteria were met, we followed the National Institute of Health's recommendation for the treatment of MIS-C/MIS-A . We added corticosteroids (methylprednisolone), intravenous immunoglobulins, and colchicine to the treatment, as well as a prophylactic dose of low-molecular-weight heparin (to prevent thromboembolic complications), along with broad-spectrum antibiotics and symptomatic treatment. According to the literature, preventing thromboembolism is essential, as most hyperinflammatory syndromes, including MIS-A, are associated with the development of these complications. Therefore, we administered a dose of low-molecular-weight heparin despite the decrease in the number of platelets, as there was no decrease below 50 x 109/L ). The patient's condition improved clinically and in the laboratory after administering corticosteroids and intravenous immunoglobulins. Therefore, the administration of biological treatment was not necessary in our case. 4. Conclusions Multisystem inflammatory syndrome in adults represents a severe complication of COVID-19, whose pathophysiology has not yet been clarified. It likely arises from the dysregulated immune response of the host caused by the SARS-CoV-2 virus. It most often occurs in the postacute period of infection, and the clinical manifestation is heterogeneous, which makes diagnosis considerably more difficult in practice. From a clinical point of view, it is essential to emphasize that unrecognized MIS-A has a high mortality rate, and that, for this very reason, it is necessary to start treatment immediately when the development of this disease is clinically suspected. In the early stage of the disease, the diagnosis of MIS-A is based exclusively on clinical symptoms and the patient's history. Due to the danger of missing it, treatment should not be postponed to wait for the results of microbiological and serological examinations. The prognosis of the disease depends on the early recognition of the condition and the rapid implementation of immunomodulating treatment (steroids, immunoglobulins, biological treatment), which reduces the risk of developing severe and life-threatening complications. In the case of our patient, the development of MIS-A symptoms occurred two weeks after the diagnosis of COVID-19. The clinical picture was characterized by febrility, headache, maculopapular exanthema, myalgia, and arthralgia. The patient also had gastrointestinal symptoms such as diarrhea and abdominal pain for a short time; later, dyspnea and hypotension were added, which resembled a septic shock. Damage to the cardiovascular system was mainly manifested by tachycardia, bigeminal ventricular extrasystoles on the ECG, as well as MRI-verified myocarditis with a decrease in the ejection fraction of the left ventricle and a laboratory elevation of TnT. After the administration of the immunomodulating treatment and the exclusion of focal infection, the clinical condition gradually improved, febrility receded, and laboratory parameters improved. Acknowledgments This publication was created thanks to the support of the Operational Program Integrated Infrastructure for the project: "Analysis of the cardiovascular and immunological response of patients after overcoming COVID-19 with a focus on the research of new diagnostic markers and therapeutic agents", code 313011AUB1. Author Contributions Data curation, O.Z. and S.P.; formal analysis, O.Z. and A.R.; methodology, O.Z.; supervision, P.J.; validation, S.P.; writing--original draft, O.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Louis Pasteur University Hospital (protocol code 69/EK/22, approval 6.5.2022) for studies involving humans. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Level of platelets during hospitalization. Figure 2 HRCT examination of the chest: (A)--Detection of fluidothorax bilaterally, up to 25 mm, more to the right (circle). (B)--Fluidopericarde up to 19 mm (circle). Figure 3 Temperature curve during hospitalization. Figure 4 MRI of the heart--white circle showing the area of myocarditis. diagnostics-13-00983-t001_Table 1 Table 1 Results of performed hematological and biochemical examinations (*--an unexamined parameter on that day). Day of Hospitalization 1. 3. 5. 6. 8. 13. 17. Monitored Parameter C-reactive protein (CRP) (mg/L) 82.06 128.1 172.2 115.1 63.6 8.2 0.69 Procalcitonin (PCT) (ug/L) 0.24 0.73 1.19 0.73 0.34 0.05 0.04 Interleukin-6 (IL-6) (ng/L) 42.13 328.1 65.6 7.68 3.96 1.5 2.3 Lactate (mmol/L) 2.67 2.17 1.88 1.58 1.44 2.08 1.74 Creatinekinase (ukat/L) 1.2 1.5 0.8 0.52 0.41 0.15 1.2 Creatine kinase-MB (ukat/L) 0.17 0.14 0.16 0.19 0.20 0.29 0.22 Troponin T (ug/L) 0.003 0.007 0121 0.077 0.041 0.028 0.005 White blood cell (x109/L) 6.36 3.26 4.80 7.21 9.55 7.26 8.79 Neutrophils (%) 82.6 82.1 91 91.7 93.2 89.2 77.9 Platelets (x109/L) 101 64 51 67 105 273 267 D-dimer (mg/L) 0.43 1.5 1.48 2.26 2.40 1.96 0.46 NTproBNP (ng/L) 122 * 5438 8730 3709 * 125 diagnostics-13-00983-t002_Table 2 Table 2 Results of performed microbiological examinations (*--repeated examination). Biological Material Result PCR SARS-CoV-2 Nasopharyngeal Swab Pozit. Ct 32.2 Pozit. Ct 35.2 * Anti-Epstein-Barr virus antibodies serum IgM negat./IgG pozit Anti-Cytomegalovirus antibodies serum IgM negat./IgG negat. * Anti-HIV virus antibodies serum negat. Anti-Chlamydia pneumoniae antibodies serum IgM/IgA/IgG negat. Anti-Mycoplasma pneumoniae antibodies serum IgM/IgA/IgG negat. Hepatitis B surface antigen serum negat. anti-Hepatitis C antibodies serum negat. Anti-Herpes simplex 1,2 antibodies serum IgM negat./IgG pozit. Anti-Francisella tularensis antibodies serum negat. Anti-Leptospira icterohemoragiae antibodies serum negat. Candida/Aspergillus antigen serum negat. antigen Legionella pneumophila/Streptococcus pneumoniae urine negat. PCR Influenza A/B nasopharyngeal swab negat. adeno, rota, noroviruses antigen stool negat. stool/rectal swab culture stool negat. urine culture urine sterile * Clostridioides difficile-toxin A/B, antigen stool negat. blood culture blood sterile * diagnostics-13-00983-t003_Table 3 Table 3 Diagnostic algorithm for the definitive case of MIS-A (12). Brighton Collaboration Case Definition Patient from Our Case Report Age Age <21 years (MIS-C) or >=21 years (MIS-A) 22 Fever >=3 Consecutive days 6 >=2 Clinical features Mucocutaneous Nonpurulent conjunctivitis, maculopapular exanthema on the chest Gastrointestinal Diarrhea, vomiting, and abdominal pain Shock/hypotension Hypotension, clinical signs of shock Neurologic Headaches Laboratory markers of inflammation Elevated CRP 172.2 mg/L (maximal value) Erythrocyte sedimentation rate 20 mm (after 1 h)/35 mm (after 2 h) Elevated ferritin 556 ug/L (maximal value) Elevated procalcitonin 1.19 ug/L (maximal value) >=2 Measures of disease activity Elevated BNP or NTproBNP or Troponin T NTproBNP: 8730 ng/L; Troponin T: 0.121 ug/L (maximal value) Neutrophilia, lymfophenia, or thrombocytopenia Neutrophils: 93.2%; Lymphocyte 3.30%; Platelets 51 x 109/L Echocardiographic evidence of cardiac involvement or physical sigmata of heart failure Pericardial effusion ECG changes consistent with myocarditis Sinus tachycardia and bigeminal ventricular extrasystoles SARS-CoV-2 Laboratory confirmed SARS-CoV-2 infection or Yes--PCR SARS-CoV-2 pozit. ct 32.2; ct 35.2 Personal historyof suspected COVID-19 within 12 weeks or Yes Close contact with known COVID-19 case within 12 week Probably yes OR SARS-CoV-2 vaccination Yes--1 dose before 1 year Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000502 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050905 diagnostics-13-00905 Interesting Images The Impact of the COVID-19 Pandemic on the Prognosis of Laryngeal Adenoid Cystic Carcinoma: A Case Report and a Literature Review Fatuzzo Irene 1* Colizza Andrea 1 Meliante Piero Giuseppe 1 Elfarargy Haitham 2 Altomari Roger 1 Fiore Marco 3 Ralli Massimo 1 Messineo Daniela 4 Greco Antonio 1 de Vincentiis Marco 1 Barbato Christian 3* Minni Antonio 15* Russo Alessandro Academic Editor 1 Department of Sense Organs DOS, Sapienza University of Rome, Viale del Policlinico 155, 00161 Roma, Italy 2 Department of Otorhinolaryngology, Faculty of Medicine, Kafrelsheikh University, El-Geish Street, Kafrelsheikh 33155, Egypt 3 Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Department of Sense Organs DOS, Sapienza University of Rome, Viale del Policlinico 155, 00161 Roma, Italy 4 Department of Radiology, Oncology, and Anatomopathological Science, Sapienza University of Rome, 00161 Rome, Italy 5 Division of Otolaryngology-Head and Neck Surgery, Ospedale San Camillo de Lellis, ASL Rieti-Sapienza University, Viale Kennedy, 02100 Rieti, Italy * Correspondence: [email protected] (I.F.); [email protected] (C.B.); [email protected] (A.M.) 27 2 2023 3 2023 13 5 90510 2 2023 21 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Laryngeal adenoid cystic carcinoma (LACC) is a sporadic neoplasm, especially if supraglottic. The COVID-19 pandemic worsened the presenting stage of many cancers and impacted their prognosis negatively. Here, a case of a patient with adenoid cystic carcinoma (ACC) with delayed diagnosis and a rapid deterioration with distant metastasis due to the COVID-19 pandemic is illustrated. Next, we present a literature review of this rare glottic ACC. The COVID-19 pandemic worsened the stage of presentation of many cancers and adversely affected their prognosis. The present case had a rapidly lethal course, undoubtedly due to the diagnosis delay caused by the COVID-19 pandemic, which impacted the prognosis of this rare glottic ACC. Strict follow-up is recommended for any suspicious clinical findings, as an early diagnosis will improve the disease prognosis, and to consider the influence of the COVID-19 pandemic, especially on the timing of common diagnostic and therapeutic procedures for oncological diseases. In the post-COVID-19 era, it is important to generate new diagnostic scenarios to achieve an increasingly rapid diagnosis of oncological diseases, especially the rare ones, through screening or similar procedures. laryngeal adenoid cystic carcinoma (LACC) COVID-19 laryngectomy adenoid cystic carcinoma (ACC) head and neck cancer 'Progetto Medio Ateneo' Univ. SapienzaRM11916B88DF74E7 This research was funded by the grant 'Progetto Medio Ateneo' Univ. Sapienza, Prot. N. RM11916B88DF74E7 to A.M. pmcFigure 1 Endoscopic view of the larynx showing the lesion. The adenoid cystic carcinoma (ACC) arises from the minor salivary glands. It accounts for 1-5% of all head and neck malignancies. Since the minor salivary glands are present in small amounts throughout the larynx, the laryngeal adenoid cystic carcinoma is sporadic, representing less than 1% of all laryngeal malignancies . Regarding the onset of laryngeal ACC (LACC), the prevalent age ranges from 50 to 60 years. However, younger generations can be affected, and both sexes are equally affected, with a slight male predominance and a male-to-female ratio of 1,5:1. There is no evidence connecting LACC etiology with smoking. An early perineural and hematological spread make this kind of carcinoma liable for local recurrence and distant metastasis, especially to the lung. Therefore, is important to increase the frequency of controls during follow-up . Laryngeal ACC can originate from any part of the larynx. The most common origin is the subglottic area (64%), followed by the supraglottic area (25%), the glottic area (5%), and the trans-glottic area (6%) . The clinical presentation is usually variable and related to the lesion location . In November 2021, a 70-year-old no-smoker female patient presented to our hospital's emergency department with stridor, severe dyspnea at rest, and hoarseness of voice. The O2 saturation level was 87% on air without cyanosis. An endoscopic laryngeal examination revealed bilateral vocal cord paralysis in adduction. Firstly, the patient underwent an urgent tracheostomy under general anesthesia. The procedure also included a laryngeal examination (micro-laryngeal surgery) under general anesthesia with tumor mapping, which revealed a bilateral mucosal thickening of the anterior thirds and anterior commissures of both vocal folds and a right vocal fold submucosal thickening . Multiple biopsies from different laryngeal areas were taken for histopathological examination. The pathological tissue revealed the presence of an adenoid cystic carcinoma of the solid type associated with the immunophenotype CK AE1 AE3 +, CD117+, CK7+/-, p63 +/-, p40+/-, Vimentin +/-, SMA+/-, S100+/-. Then, the patient underwent a CT scan of the neck chest and brain with a contrast medium and an abdominal ultrasound examination. The first chest, brain, and abdominal radiological evaluations did not show metastatic lesions. The neck CT scan revealed the presence of small submucosal bilateral glottic masses, associated with increased cervical lymph nodes volume, without subglottic and extra-laryngeal extensions . Figure 2 CT scan showing (during hospitalization) pneumonia by Cytomegalovirus. At the lateral-basal segment of the right inferior lobe, in the subpleural level, the gross intraparenchymal collection with hydro-aerial content is compatible with the pneumatocele. In the lung window, multiple areas of parenchymal thickening are visible in the right basal location. (On the left, coronal section parenchymal window, on the right, axial section lung window). Partial laryngectomy (OPHL II B) with bilateral selective neck dissection (cervical nodal Robbins levels II-IV) and postoperative radiotherapy were planned to manage this case. Unfortunately, this planned surgical intervention was impossible because of the patient's poor general conditions. Moreover, one of the follow-up CT scans of the chest (three months after the initial one) revealed the presence of bilateral diffuse multiple micronodules, which were considered early distant metastasis from the laryngeal adenoid cystic cancer . Figure 3 CT scan windows showing metastasis and inflammatory phenomena on both sides of the lung. (On the left, axial parenchymal lung section. On the right, axial lung window). During hospitalization, bacterial pneumonia began, worsened by secondary viral (Cytomegalovirus) and fungal pneumonia. The patient received a triple antibiotics course with an antiviral, an antifungal, and systemic and local inhalational corticosteroids. However, despite the medical therapy, the chest condition deteriorated progressively . Figure 4 CT scan on the left. The neck scan revealed the presence of small submucosal bilateral glottic masses, associated with increased cervical lymph node volume, without subglottic and extra laryngeal extensions. (A) Axial section basal CT scan on the left. (B) Axial contrast-enhanced CT on the right. Lung window showing a small scar at the level of the right lower lobe from previous pneumonia reported by the patient; (C) coronal and (D) axial lung window). Due to the worsening conditions, the patient was mechanically ventilated because of acute respiratory failure. Despite the therapy and mechanical ventilation, the pulmonary functions deteriorated progressively, resulting in the patient's death. The patient was not diabetic, hypertensive, or cardiopathic and was not a smoker. By anamnestic clinical history, we discovered that two years before this event (October 2019), the subject presented mild hoarseness of voice. At the time, an endoscopic laryngeal examination revealed bilateral mobile vocal folds without apparent abnormalities. For further confirmation, the subject underwent a laryngeal exam under general anesthesia, which showed the absence of any macroscopic lesion, and the histopathological results of the biopsies were negative. The physicians scheduled a follow-up after three months, but unfortunately, the lockdown caused by the COVID-19 pandemic and the fear of viral infection prevented her to attend the recommended follow-up visits. The patient was COVID-19-negative throughout the whole illness (Table 1). We performed a literature analysis by searching the PubMed database for 'laryngeal adenoid cystic carcinoma'. We did not limit the search to article types because of the rarity of the disease and the little number of papers about it. We choose only papers published in English within the past five years. The articles in the database whose full text could not be found were also excluded. The title and abstracts of the identified manuscripts were initially screened and selected by all authors independently (IF, AC, PGM, HE, RA, MF, MR, DM, AG, MdV, CB, and AM) based on their relevance to the review topic. The following set of shared chosen inclusion criteria was applied individually to the selected articles in their full-text version: primary laryngeal affection of adenoid cystic carcinoma and therapy consensus of LACC. The literature search yielded 48 papers. Subsequently, 28 studies were excluded because they did not meet the objective of our review, and 20 studies were included and discussed . diagnostics-13-00905-t001_Table 1 Table 1 Clinical synopsis of the laryngeal adenoid cystic carcinoma. Clinical timeline Hoarseness without laryngeal mucosal abnormalities in 2019. Admission to the emergency room in 2021. Tracheostomy. Clinical staging Laryngeal biopsies and diagnosis of ACC. CT scan with contrast. Partial laryngectomy with bilateral selective neck dissection planning. Clinical worsening. Death. Figure 5 Articles selection on laryngeal adenoid cystic carcinoma. Primitive LACC is a rare head and neck carcinoma with slow growth but a high rate of malignancy due to its frequent perineural invasion. A high percentage of distant metastasis has been reported both at first diagnosis and during follow-up. The main distant metastasis site for LACC is the lung, but metastasis can develop in many sites. Iype et al. even described a case of an isolated scapular metastasis . Although the first evaluation of neoplastic disease usually involves TNM staging according to AJCC, which is considered to have a significant prognostic value, Taha M. et al. observed that this is not true for LACC . The histologic grade seems to be a more significant prognostic factor for survival in the presence of LACC, although this finding was established in a small sample of patients . Radiation therapy is not considered a primary curative treatment for adenoid cystic carcinoma, whatever its location, but it has been widely used as an adjuvant treatment. Benefits in terms of local control and survival with adjuvant radiotherapy have been reported in many papers . Tan et al. tried to create an overview of rare tumors of the larynx and of therapeutic protocols approved for laryngeal adenoid cystic carcinoma. It seems that there are no international guidelines for their treatment, but only recommendations, as reported in Lionello's work . The recommended treatment for LACC is extensive surgical resection combined with postoperative radiotherapy. However, there is no agreement regarding the treatments for LACC. According to the AJCC criteria, surgery seems to be the best therapeutical choice, with a good disease-free survival rate in the following 5 years; however, the outcomes are not satisfactory . Total laryngectomy was the most used surgical procedure . However, nowadays the best surgical treatment is chosen based on the staging of the disease, thus considering surgical approaches aimed at preserving the morphology and function of the larynx . The main goal is to free patients from cancer and at the same time guarantee them the best quality of life. Iandelli et al. reported only two cases of laryngeal non-SCC and argued that conservative surgery is possible without affecting the patients' survival . As the conservative approach is the best choice, Kozhanov et al. reported a case of endolaryngeal resection of ACC in a T1N0M0 R0 . Partial laryngectomy could be a valid alternative to radical surgery according to disease staging . For example, Wang et al. reported a partial laryngectomy for LACC, and the patient had no evidence of disease recurrence or metastasis during the follow-up period . To improve the outcome, adjuvant therapy is to be considered in case of adverse features such as close or positive margins, T3-4, neural and perineural invasion, and lymph node metastases. Some authors proposed concurrent chemotherapy and radiotherapy, such as Vardaxi et al. . No studies compared these different therapeutic protocols. Even though LACC is relatively radioresistant, Akbaba et al. stressed the role of RT as an alternative to total laryngectomy . The same group reported eight cases of LACC who underwent radiotherapy with carbon ions (C12) at the Heidelberg Ion Beam Therapy Center (HIT). The small number of enrolled patients does not allow us to come to conclusions . Adjuvant radiotherapy is the best choice after surgical treatment and should be used in each case of perineural invasion, as also Marchiano et al. observed in 2016 . Cui et al. reported, in 2019, that radiant therapy after surgery is more recommended, but there are many cases of recurrent LACC with or without distant metastasis in the lung some years after treatment . The adenoid cystic carcinoma represents a rare tumor originating from the salivary glands that can affect the upper aero-digestive tract, including the larynx. It manifests with a slow growth pattern, often with macroscopic submucosal characteristics, such that it does not manifest symptomatically until advanced stages. Based on the laryngeal subsite involved, there are different clinical manifestations. In each case, the severity of the pathology is assessed according to both clinical and radiological analyses, but a definitive histological staging is usually necessary. Therefore, to determine its local extension, the histological pattern should always be identified, with particular attention to perineural invasion that characterizes high-risk cancers. After a careful evaluation of the literature about LACC, we can state that the first choice of treatment should be the most radical surgery as possible, considering conservative procedures such as partial laryngectomies among the options. The recommendation for adjuvant treatment is required on a case-by-case basis depending on the histology, extent, and stage of the pathology. A considerable number of distant metastases was found during follow-up. It should be emphasized that there is no direct correlation between the degree of pathology severity and the incidence of distant metastasis. Considering our clinical case, when the patient came to our clinic for the first time two years earlier, she had a recent onset of mild voice hoarseness. Although the endoscopy examination revealed no lesions, with bilateral mobile vocal folds without apparent mucosal abnormalities or neck involvement, we tried to confirm the exclusion of any malignant lesion by a complete laryngeal examination under general anesthesia. The negative clinical, radiological, and histopathological results denied the proposal of a suspicious malignancy. This negativity during the pathology's starting period was most likely due to the inert submucosal nature of LACC lesions, which may take years to be noticeable. However, for additional confirmation, we asked the patient to follow a restricted follow-up protocol and to undergo an endoscopic office laryngeal examination every three months for the early detection of any developing lesion. Unfortunately, the patient did not follow this protocol and two years later developed a sudden onset of stridor which necessitated tracheostomy due to a T3 glottic LACC lesion. This follow-up delay was mainly due to the lockdown during the COVID-19 pandemic. After diagnosing the glottic T3 N0 M0 ACC lesion, we decided on a therapeutic plan in the form of partial laryngectomy (OPHL II B) surgery with neck dissection, with adjuvant radiotherapy. We decided on a partial laryngectomy to preserve the voice function and reserved total laryngectomy for recurrence. ACC is conventionally thought to be radioresistant. However, some studies have shown prolonged patient survival and decreased recurrence following radiotherapy, suggesting that ACCs are radiosensitive . Moreover, postoperative adjuvant radiotherapy may help confirm negative free margins after surgery, as this tumor has a high liability for local growth because of perineural and hematological spread. This therapeutic plan was canceled because of a pulmonary infection and the bad general conditions of the patient. In addition, the presence of a cancer lesion decreased her immune function, resulting in refractory pneumonia. Moreover, this effect was worsened by the following uprising of lung metastasis from the laryngeal ACC lesion . During the COVID-19 pandemic, all medical services were shortened, and most outpatient clinics and services were canceled. The medical services were mainly directed to manage COVID-19 cases and control the pandemic. In addition, the main priorities were the emergency cases and the oncological surgeries. All these circumstances were associated with a public fear of seeking medical services to avoid COVID-19 infection, which was associated with high mortality rates . This worsened the presenting stage of many cancers and impacted their prognosis badly. According to the research of Stevens et al., head and neck mucosal squamous cell carcinoma patients presented with more advanced clinical nodal disease during the early months of the COVID-19 pandemic, despite no change in the symptoms . Moreover, Tevetoglu et al. concluded that the COVID-19 pandemic caused delays in diagnosing and treating many diseases, such as head and neck cancers. Admissions with advanced-stage disease and the need for more complex reconstructive procedures increased . The disease-specific survival rates of LACC are 69% and 49% at 5 and 10 years, respectively, after a primary treatment . In contrast, the presenting case had a rapidly progressive disease course and died without receiving oncological management. Many factors were responsible for this bad prognosis, such as the delay in the diagnosis, the advanced stage at presentation, the bad general conditions, and the presence of distant metastasis to the lung. This case report shows that the COVID-19 pandemic worsened the stage of presentation of many cancers and adversely affected their prognosis . The management of cancer patients was deeply modified, and oncology departments' staff reorganized their protocols and priorities to counteract the COVID-19 impact. The presence of a COVID-19 infection in cancer patients increased the complexity of cancer treatment and the risk of complications . In most patients, elective cancer treatments were postponed, with the aim of finding a balance between a potential COVID-19 infection and cancer treatment protocols in the cancer population . The present case of LACC had a rapidly lethal course, undoubtedly due to the effects of the COVID-19 pandemic, which affected the prognosis of this rare glottic ACC. We recommend rigorous follow-up for any suspicious laryngeal clinical findings. However, it is not yet established that early intervention can improve the prognosis of laryngeal lesions. Overall, the purpose of our work is to recommend to strictly apply the already-known diagnostic-therapeutic algorithms and to alert patients about their clinical conditions. It would also be desirable to try to think of screening algorithms to speed up the time of early diagnosis and ensure a better post-treatment outcome, in the case of diseases that are rare but have a prognostically inauspicious course if misrecognized until an advanced stage. It is hoped that the pandemic, which has now been efficiently controlled by public health services, and post-COVID-19 studies and research may help define a new route of approaching patients, especially oncology patients, for the purpose to improve the outcomes of some malignancies, such as the laryngeal adenoid cystic carcinoma. diagnostics-13-00905-t002_Table 2 Table 2 LACC diagnosis and treatment protocol. Findings References Diagnosis Staging and histopathological assessment It is necessary to perform an accurate histopathological analysis because histological grading seems to have a greater prognostic impact than TNM staging. Treatment Surgery It is recommended to perform extensive surgical resection of the cancer. Total laryngectomy is the most used technique, partial laryngectomy can be used in selected cases. Adjuvant therapy Adjuvant radiotherapy or chemoradiotherapy improves local control and survival. There is no direct comparison between protocols. Adjuvant therapy is particularly recommended in case of adverse features. Patients not eligible for surgery Curative radiotherapy with radiotherapy with carbon ions (C12) has been used in few patients, with encouraging results. Further studies are needed. Follow-up Frequent follow-up Frequent follow-up with whole-body evaluation is necessary, considering that cases of metastases have been reported in districts unusual for laryngeal carcinoma. Acknowledgments The authors thank IBBC-CNR, Sapienza University of Rome, Policlinic Umberto I, Rome, Italy. Author Contributions Conceptualization, M.d.V., A.G. and A.M.; methodology, I.F., A.C., P.G.M., R.A. and H.E.; validation, M.R. and D.M.; investigation, I.F., A.C., P.G.M., R.A., H.E., M.R. and D.M.; resources, I.F., A.C. and P.G.M.; data curation, I.F., A.C. and P.G.M.; writing-original draft preparation, I.F. and P.G.M.; writing--review and editing, C.B. and A.M.; visualization, I.F., M.F., M.d.V., A.G. and A.M.; project administration C.B. and A.M.; funding acquisition, A.M.; All co-authors provided a valuable interpretation of the data. They have ensured that all aspects of the work are accurate and have been appropriately investigated and interpreted. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the Declaration of Helsinki and followed the Institutional Review Board standards from the Sapienza University of Rome, Policlinico Umberto I. Informed Consent Statement Written informed consent was obtained from the patient to publish this paper. Data Availability Statement The data presented in this study are available upon reasonable request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Cui Y. Bi L. Sun L. Wang X. Zhu Z. Laryngeal adenoid cystic carcinoma: Three case reports Medicine 2019 98 e18177 10.1097/MD.0000000000018177 31860963 2. Liu W. Chen X. 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PMC10000503 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050712 cells-12-00712 Article Diagnostic and Prognostic Comparison of Immune-Complex-Mediated Membranoproliferative Glomerulonephritis and C3 Glomerulopathy Kovala Marja Conceptualization Methodology Investigation Data curation Writing - original draft Writing - review & editing Visualization Funding acquisition 1* Seppala Minna Conceptualization Methodology Investigation Resources Data curation Writing - original draft Writing - review & editing Funding acquisition 2 Raisanen-Sokolowski Anne Conceptualization Methodology Investigation Writing - review & editing Visualization Supervision Project administration Funding acquisition 1 Meri Seppo Conceptualization Methodology Investigation Writing - review & editing Funding acquisition 3 Honkanen Eero Conceptualization Methodology Writing - review & editing Funding acquisition 2 Kaartinen Kati Conceptualization Methodology Investigation Resources Writing - review & editing Supervision Project administration Funding acquisition 2 Mitrofanova Alla Academic Editor 1 Department of Pathology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland 2 Department of Nephrology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland 3 Translational Immunology Research Program TRIMM, Department of Bacteriology and Immunology, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland * Correspondence: [email protected] 23 2 2023 3 2023 12 5 71230 12 2022 19 2 2023 21 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Membranoproliferative glomerulonephritis (MPGN) is subdivided into immune-complex-mediated glomerulonephritis (IC-MPGN) and C3 glomerulopathy (C3G). Classically, MPGN has a membranoproliferative-type pattern, but other morphologies have also been described depending on the time course and phase of the disease. Our aim was to explore whether the two diseases are truly different, or merely represent the same disease process. All 60 eligible adult MPGN patients diagnosed between 2006 and 2017 in the Helsinki University Hospital district, Finland, were reviewed retrospectively and asked for a follow-up outpatient visit for extensive laboratory analyses. Thirty-seven (62%) had IC-MPGN and 23 (38%) C3G (including one patient with dense deposit disease, DDD). EGFR was below normal (<=60 mL/min/1.73 m2) in 67% of the entire study population, 58% had nephrotic range proteinuria, and a significant proportion had paraproteins in their serum or urine. A classical MPGN-type pattern was seen in only 34% of the whole study population and histological features were similarly distributed. Treatments at baseline or during follow-up did not differ between the groups, nor were there significant differences observed in complement activity or component levels at the follow-up visit. The risk of end-stage kidney disease and survival probability were similar in the groups. IC-MPGN and C3G have surprisingly similar characteristics, kidney and overall survival, which suggests that the current subdivision of MPGN does not add substantial clinical value to the assessment of renal prognosis. The high proportion of paraproteins in patient sera or in urine suggests their involvement in disease development. C3 glomerulopathy immune-complex-mediated membranoproliferative glomerulonephritis complement activation MPGN Helsinki and Uusimaa University Hospital Diagnostic CenterY780021085 Y780021067 Y780020023 The Kidney and Liver foundation, Finland2019 Alexion20669 This research was funded by Helsinki and Uusimaa University Hospital Diagnostic Center, grant numbers Y780021085, Y780021067, and Y780020023, by The Kidney and Liver foundation, Finland grant 2019, and a research grant 20669 from Alexion. pmc1. Introduction Membranoproliferative glomerulonephritis (MPGN) is a pattern seen in light microscopy (LM) in approximately 7-10% of all biopsy-confirmed glomerulonephritis cases . Typical hallmarks are endocapillary and mesangial hypercellularity, mesangial matrix expansion, and formation of capillary double contours resulting in a lobulated morphology . However, these changes can vary from minimal to mesangial, endocapillary proliferative, exudative, crescentic, and sclerosing patterns , possibly portraying different time points of injury. Based on immunofluorescence microscopy staining (IF), MPGN is divided into immune-complex-mediated (IC-MPGN) and complement-mediated MGPN (C-MPGN), also known as C3 glomerulopathy (C3G) . In addition, C3G is divided into dense deposit disease (DDD) and C3 glomerulonephritis (C3GN), based on the presence or absence of intramembranous dense deposits on electron microscopy (EM), respectively . EM is also necessary to differentiate organized deposits from MPGN-type deposits . In IC-MPGN, IF reveals immunoglobulins (Igs) and C3 deposits, mainly due to activation of the classical pathway , while C3G has bright, dominant, C3 staining at least twice the intensity of any immune reactant, primarily due to abnormal activation of the alternative pathway . The etiology of IC-MPGN includes autoimmune diseases, chronic infections, malignant diseases, and paraproteinemias , such as monoclonal gammopathy of unknown significance (MGUS) or renal significance (MGRS) . An underlying abnormality is lacking in some 30% of cases . In C3G, the alternative pathway is thought to be dysregulated due to gain-of-function or loss-of-function mutations in complement proteins, autoantibodies, or inhibitors against complement regulators . However, a subset of patients has no identifiable cause . A triggering second hit is often required to manifest the disease . The clinical presentation of MPGN varies from asymptomatic hematuria and proteinuria to nephrotic or nephritic syndrome, or even rapidly progressive glomerulonephritis. MPGN has a progressive nature and often recurs in kidney transplants . Treatment depends on the etiology, but supportive therapy aiming at reducing proteinuria and controlling blood pressure is recommended for all . For more severe cases, immunosuppressive therapy, plasma infusions or plasma exchange may be beneficial, but the results vary . Some C3G patients may profit from complement C5-inhibitor therapy . Several other drugs blocking different sites of the complement cascade have been developed, and are expected to achieve marketing authorization in the near future . Although the information on the pathophysiology of MPGN has greatly advanced in the past 10 years, the diagnosis can still be challenging. The diagnostic accuracy of IF may necessitate proteinase K-processed paraffin-embedded IF (PIF) analysis to show masked immunoglobulins. However, the distinction between C3GN and DDD can sometimes be problematic. In fact, the diagnostic category between IC-MPGN and C3G may even change upon analysis of subsequent biopsies . The distinction between classical and alternative pathway complement activation is not always straightforward, since the two pathways are interdependent. Alternative pathway activation is common and can also occur in IC-MPGN . Diagnostic challenges also exist between postinfectious glomerulonephritis (PIGN) and C3G, as dominant C3 deposition with immunoglobulins can be observed in both entities . In PIGN, the disease process has been thought to be immune complex-mediated and self-limiting . If the IF result is negative, thrombotic microangiopathy (TMA) should be considered . It is postulated that complement activation occurs on cell surfaces in TMA as opposed to mostly fluid-phase activation in MPGN . Thus, there is still a great need for further understanding of the mechanisms and diagnostic differences between the various forms of MPGN. The aim of this study was to investigate the prognostic histological and clinical factors between adult IC-MPGN and C3G patients and to investigate their complement system, both at diagnosis and at the follow-up visit. 2. Materials and Methods 2.1. Patient Population and Data Retrieval This single-center study was carried out at Helsinki University Hospital district, Finland, covering roughly 1.7 million inhabitants (31% of the total population). Patients were identified from records in the Department of Pathology. All eligible adults who had received a non-transplanted (native) or transplant biopsy-confirmed diagnosis of MPGN, C3G, TMA, or PIGN from 2006 to 2017 were included. Only the 1st biopsy within the time frame of interest was included (index biopsy), including eight patients who had a diagnostic biopsy taken before 2006. Clinical information was recorded from electronic medical records from the initial diagnosis until the end of 2019, the last visit, death, or when lost to follow-up, whichever occurred latest. The study flow is depicted in Figure 1. Exclusion criteria were other clear-cut diagnoses merely resulting in an MPGN-type pattern (such as systemic lupus erythematosus or IgA nephropathy), or an inadequate biopsy sample. Other secondary IC-MPGN patients were included. For TMA biopsies, transplant glomerulopathy and antibody-mediated rejection resulting in an MPGN-type pattern were excluded (see the full list of exclusion diagnoses in Supplementary Table S1). The eligibility of problematic cases was judged by the research team. Study was reviewed by the Helsinki University Hospital's Ethical Committee (HUS/2520/2018) and a research permit (HUS/459/2018) was granted. The study was conducted according to the Declaration of Helsinki. All patients evaluated on the follow-up visit signed a declaration of informed consent. 2.2. Laboratory Analyses Laboratory analyses were performed in the accredited Helsinki University Hospital laboratory using standardized laboratory methods. Hemoglobin was measured from plasma photometrically. The normal ranges for males and females were 134-167 g/L and 117-155 g/L, respectively. Creatinine (upper normal value 100 mmol/L for males and 90 mmol/L for females) and low-density lipoprotein (LDL) (reference values according to Nordic Reference Interval Project ) values were analyzed photometrically and enzymatically, respectively. C-reactive protein (CRP) levels were studied photometrically (normal range <4 mg/L). Plasma albumin analysis was carried out photometrically with bromocresol purple reaction, for which the reference values used are from the Nordic Reference Interval Project . Antibodies to extractable nuclear antigens (ENA) were analyzed using a Phadia 250 instrument, and an accredited fluoroenzyme-immunological (FEIA) method with a two-phase test protocol at the HUSLAB Laboratory, Helsinki, Finland. First, the sample was screened for existing antibodies using a known mix of ENA-proteins as an antigen. If the sample was screened positive in the first phase, it was analyzed further against eight ENA antigens (S-JoAb, S-RNP70Ab, S-Scl70Ab, S-SentBAb, S-SSAAb, S-SSBAb, S-SmAb (upper normal limit: 7 U/mL, slightly elevated: 7-10 U/mL and elevated: >10 U/mL), and S-RNPAb (normal: <5 U/mL, slightly elevated: 5-10 U/mL and elevated: >10 U/mL). The type of commercial kit used varied according to the year in which the test was performed. Estimated glomerular filtration rate (eGFR) was calculated according to the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI), for which the cut-off for lower limit of normal was 60 mL/min/1.73 m2. Urine albumin was analyzed photometrically and immunochemically and the upper limit of normal for urine albumin/creatinine ratio was 3.0 mg/mmol. Daily urine protein excretion was analyzed photometrically and with a benzethonium chloride reaction and the upper limit of normal was 100 mg. Microscopic hematuria was analyzed with automatic phase contrast microscopy, and its normal value for erythrocytes was <10 E6/L. Serum-free light chains were analyzed photometrically and immunochemically using Freelite reagents from The Binding Site, Birmingham, UK. Serum and urine paraproteins were analyzed using immunofixation after agarose gel electrophoresis. Other analyses were performed using routine laboratory methods. 2.3. Kidney Biopsies LM, IF and EM analyses of index biopsies were re-evaluated by pathologists according to the MPGN classification , diagnostic criteria of C3G , 2018 Banff classification and Definition of Glomerular Lesion by the Renal Pathology Society , where appropriate. The overall biopsy morphology was divided into minimal change (morphology nearly normal), MPGN, crescentic (if any crescents were visible), mesangial proliferative (if mesangial matrix expansion and cellularity were seen without double contours), and exudative forms (if glomerular granulocytes were visible) . Index biopsy was defined as the first biopsy acquired during the period of interest (2006-2017). Initial diagnostic biopsies procured earlier than 2006 were not available for re-evaluation. IF brightness was evaluated for IgG, IgM, IgA, C3, C1q, kappa, lambda, and fibrinogen as 0-4, where brightness is negative (0), trace (1), mild (2), moderate (3) or strong (4), respectively. If a frozen section IF was unavailable or masked immunoglobulins were suspected, PIF was performed and evaluated similarly. EM was performed for 41 cases (68%), from which sufficient material was available for the analysis. This included one DDD patient. IC-MPGN was defined when mesangial and/or capillary immunoglobulins and C3 and/or C1q on IF were detected and C3G was defined when staining was C3 dominant and at least twice brighter than any other reactant on IF . PIGN was defined when a previously diagnosed infection had resulted in kidney injury that resolved within 6 months from the onset of symptoms. TMA was defined when a MPGN-type of injury was seen in LM and no (or only a few) immunoglobulins and/or C3/C1q were detected on IF. 2.4. Clinical Data Clinical information was documented from the electronic medical records at diagnosis and during follow-up until the preselected endpoint. Follow-up started from the diagnostic biopsy and ended at the end of 2019 or when the patient moved out of the hospital district, was lost to follow-up, attended the last outpatient visit, or died, whichever occurred latest. All eligible patients were invited for an outpatient follow-up visit, where laboratory tests, differential diagnostics, and complement testing were completed. Patients who had a severe psychiatric illness or severe dementia were excluded from the appointment. Data from their electronic medical records were, however, evaluated. The time of diagnostic biopsy was set as the baseline. Kidney function was assessed by using both serum creatinine and eGFR. Progressive disease was defined as at least 50% reduction in eGFR from baseline and plasma creatinine level exceeding the upper limit of normal at the last follow-up and/or by kidney failure leading to kidney replacement therapy. 2.5. Complement Analyses Complement analyses were performed for patients attending the outpatient visit. C3 and C4 levels were measured by nephelometry. Anti-factor H-antibodies, anti-C3b-antibodies, and anti-factor B antibodies were quantified using an ELISA assay according to the Helsinki protocol . Human sera without or with autoantibodies were included as negative and positive controls. Nunc Maxisorp plates were coated with 100 mL portions of factor H (Complement Technologies, Tyler, Texas, USA), purified factor C3b, or purified factor B to quantify anti-factor H, anti-C3b, and anti-factor B antibodies, respectively. The plates were then left overnight at 4 degC, whereafter they were washed with phosphate-buffered saline (PBS) containing 0.05% Tween 20 and blocked with 200 mL of the same buffer at ambient temperature for 2 h. Samples were analyzed in duplicate. Serum samples diluted 1/20 were added in 80 mL portions and incubated for 2 h at 37 degC. After washing, HRP-conjugated (horse radish peroxidase, Dako, Glostrup, Denmark) secondary antibodies diluted at 1:2000 in PBS were added and incubated again at 37 degC for 1 h. The plates were washed with PBS and o-phenylenediamine dihydrochloride (OPD) substrate was added. The reaction was stopped at 120 mL of 0.5 M H2SO4 and a spectrophotometer was used to measure the optical density of samples at a wavelength of 492 nm. C3 nephritic factor (C3Nef) was analyzed by in-house immunofixation electrophoresis, which involved examining the ability of the patient's serum to activate the alternative pathway of complement in normal serum in the presence of magnesium ethylene glycol tetra-acetic acid (MgEGTA). Factor H and Factor H-related proteins were analyzed by immunoblotting and compared to normal human serum controls. Appropriately diluted samples were added in 1:100 and 1:300 dilutions into 4-12% SDS-PAGE gradient gels (Thermo Fisher Scientific, Waltham, MA, USA). The samples were then run for 45 min at 165 V in 1x MES buffer, whereafter they were transferred onto a filter membrane. Non-specific binding sites were blocked for 1 h at room temperature with 1 mL of 5% non-fat dry milk prepared in 1x PBS and 0.05% Tween 20. Later, primary goat anti-factor H-antibody was added into the solution and incubated overnight at 4 degC. The membranes were then washed at room temperature for 1 h with 15-20 min changing intervals of 2-3 mL 1x PBS and 0.05% Tween 20. Secondary rabbit-anti-goat HRP-conjugated antibody was added with 5% non-fat dry milk and incubated at room temperature for 1 h. The washing with PBS changing intervals was then repeated at room temperature for 1 h. The bands were visualized with an in-house protocol of electrochemiluminescence recipe for 1 min at room temperature. Films were developed at different exposure times, after which the results were interpreted visually. If the band(s) corresponding to factor H-related proteins 1 and 3 (FHR1-3) were absent, a deletion of FHR1-3 proteins was reported. For FHR1-3 proteins, the immunoblot demonstrates two isoforms (FHR1b and FHR1a). FHR1b is embedded in the same band with the factor H-like protein-1 (FHL-1), but the intensity of FHR1a can be compared to the standards with normal or half-normal levels of FHR1a to indicate homozygous or heterozygous deletion, respectively. Since the FHR1 and FHR3 genes are tightly linked, in most cases, the FHR1 deletion also encompasses FHR3. This observation has been verified by a Multiplex Ligation Dependent Probe Amplification (MLPA) test. C3 activation and C3 activating factors in patient sera were analyzed using serum mixing tests and immunoblotting. Different mixtures were prepared as follows: (1) 100 mL patient serum and 2 mL 5 M EDTA, (2) 50 mL patient serum, 50 mL donor serum, and 2 mL 5 M EDTA, (3) 50 mL patient serum, 50 mL donor serum, and 2 mL 5 M EDTA, (4) 50 mL patient serum, 50 mL donor serum, and 2 mL PBS and (5) 50 mL patient serum, 50 mL donor serum and 2 mL 1 M MgCl2/5 M EGTA. Mixtures 1-2 were incubated for 1 h at 4 degC to stop the reaction and mixtures 3-5 at 1 h at 37 degC to allow the reaction to continue. For mixtures 2 and 3, the mixtures were prepared similarly, but the incubation temperature was different in order to see the baseline and whether any cation-independent C3 conversion (e.g., by microbial proteases) would occur. After incubation, the reactions of mixtures 3-5 were stopped with 2 mL 5 M EDTA. To appropriately diluted samples 1-5, 3 mL of reducing agent and 7.5 mL of buffer were added, then they were incubated for 10 min at 70 degC. Twenty mL portions of prepared samples were added to 4-12% SDS-PAGE gels and ran and transferred onto a filter membrane similar to factor H immunoblotting. After that, non-specific binding sites were blocked in a similar manner as factor H immunoblotting; however, 10 mL was used. To the blocking liquid, 1:10,000 polyclonal rabbit anti-human anti-C3c-antibody (Dako, Glostrup, Denmark) was added and incubated overnight at 4 degC, except for patients 10-17, for whom a polyclonal sheep anti-human C3c-antibody (Bio-rad Laboratories, Solna, Sweden) was used. Similarly, for factor H immunoblotting, membranes were washed with PBS. Next, HRP-conjugated goat anti-rabbit IgG secondary antibody (Dako, Glostrup, Denmark) was added in a dilution of 1:10,000 (into a 5% milk power and PBS with 0.05% Tween 20). For patients aged 10-17, a donkey anti-sheep HRP-conjugated secondary antibody (Jackson ImmunoResearch, Ely, UK) was used. Similar to factor H testing, washing with PBS was carried out for 1 h, and an in-house protocol for enhanced electrochemiluminescence was performed for visualization. Films were then developed at variable exposure times. See the full list of complement analyses performed in Supplementary Table S2. The reference values for complement tests were as described for each analysis. 2.6. Statistical Analysis Statistical analyses were performed by a professional biostatistician using R software version 4.0.4 (R Core Team, 2021). Mean values were compared using the t-test of independent samples. As the mean estimator was assumed to be asymptotically distributed regardless of the distribution of the variable itself, and as we wanted to emphasize the difference in distribution, the parametric t-test was chosen. Categorical data analysis was carried out using Fisher's exact test. In addition, logistic regression was used to predict factors determining the changes in binary dependent variables, and the difference of survival functions between groups was estimated using a Kaplan-Meier curve , and the corresponding statistical test used was a log-rank test. The significance level (p-value) of all statistical tests was set to 0.05. 3. Results 3.1. Patient Population A preliminary data search of 7078 adult biopsies identified 204 patients, out of which 60 (0.8%) fulfilled the inclusion criteria. The relative annual incidence of MPGN varied between 0.4-1.5%. After index biopsy re-evaluation, there were 37 (62%) IC-MPGN patients and 23 (38%) C3G patients (including one DDD patient). Index biopsy was the diagnostic biopsy for 52 (87%) patients, and for 8 (13%) patients, the diagnosis was from an earlier biopsy. Nine (15%) index biopsies were from kidney transplants. Out of the entire study population, 42 (70%) were primary MPGN and C3G cases. No misdiagnosis among TMA patients and no masked immunoglobulins were observed after 24 PIF examinations. However, 4/11 (36%) PIGN patients were reclassified as either C3G or IC-MPGN. Twenty-nine (29/60, 48%) patients attended the outpatient visit, for which detailed complement analyses were performed. 3.2. Clinical Characteristics Baseline characteristics at the time of clinical diagnosis are summarized in Table 1 and Table 2. No statistically significant differences between IC-MPGN and C3G patients were found in the patient or kidney characteristics or the other laboratory variables. Estimated GFR was below normal (<=60 mL/min/1.73 m2) in 63% and 73%, and nephrotic range proteinuria was detected in 68% and 43% of the IC-MPGN and C3G patients, respectively. The mean ages were 52 and 54 years, and the proportions of males were 62% and 57% for IC-MPGN and C3G groups, respectively. 3.3. Histological Characteristics No statistically significant differences in the index biopsy histological analyses were found between the two patient groups (Table 3). However, in the C3G group, there seemed to be a higher frequency of mild interstitial fibrosis (48% in C3G and 11% in IC-MPGN, p = 0.059). The IF and EM findings between the groups are presented in Supplementary Table S3, which showed no differences in EM findings. The IF findings differed between the groups, as the diagnosis of IC-MPGN and C3G is based on these findings. None of the studied morphological variables predicted progressive kidney disease in multivariate analysis (Supplementary Table S4). Various LM features possibly representing a different phase of the injury process were observed , and their ratios in IC-MPGN and C3G patients are portrayed in Figure 3. Classical MPGN-type patterns were the most common, but overall, it was observed in only 34% of cases. The various LM features portrayed in Figure 3 did not predict dialysis (p = 0.189), transplantation (p = 0.814), or death (p = 0.996) in either of the groups for the entire study population, or for the primary MPGN and C3G cases (p = 0.451, p = 0.763, and p = 0.973, respectively). 3.4. Baseline Complement and Paraprotein Findings Complement variables at baseline were available for only a subset of patients. Serum C3 was decreased in two (20%, n = 10) C3G patients, but in none of the IC-MPGN patients (n = 7). Serum C4 was decreased in one (13%) C3G and two (18%) IC-MPGN patients. Functional complement analysis showed that alternative pathway activity was lower than the reference value in two (29%) C3G and one (13%) IC-MPGN patients. Classical pathway activity was decreased in two (25%) and six (50%) patients, and lectin pathway activity in one (14%) and one (13%) patient, respectively. Four (50%) C3G patients and three (25%) IC-MPGN had positive C3 nephritic factor, but none had factor H-antibody positivity. Serum paraprotein was detected in five (33%) C3G and eight (28%) IC-MPGN patients and urine paraprotein in four (27%) and one (4%) patients, respectively. 3.5. Complement and Paraprotein Findings at Follow-Up Complement and paraprotein characteristics at the study follow-up visit are summarized in Table 4. Insignificantly, the alternative and classical pathway activities were lower in the C3G than in the IC-MPGN group. Lectin pathway activity was most often decreased below the reference value in the whole study population (34%), and more frequently in IC-MPGN patients (44%) than in C3G patients (21%). A heterozygous deletion of FHR1-3 was detected in 30% of all the patients. Factor H-antibody positivity was seen in 6% of all the patients. A C3 activation test showed an ability to activate the classical or the alternative pathway by serum factors from four IC-MPGN patients (12% and 12%, respectively). 3.6. Treatment, Kidney, and Patient Survival Treatments at baseline and during follow-up did not differ between the patient groups (Table 5). Follow-up time for the whole study population was 7.3 (range 0.08-38) years, during which 11 (49%) C3G and 16 (43%) IC-MPGN patients developed progressive kidney disease. Blood pressure medication was used on 36 IC-MPGN patients, on 20 C3G patients at baseline, and on 37 and 23 patients during follow-up, respectively. Eculizumab was used only for one C3G patient during the follow-up. Time from diagnostic biopsy to the start of kidney replacement therapy, to kidney transplantation, or to death was not significantly different between the groups for the entire study population or for the primary MPGN and C3G cases . Twelve (32%) IC-MPGN patients and 5 (22%) C3G patients died during the study follow-up. At the last study follow-up, twelve (20%) patients out of the entire study population had received a kidney transplant. Multivariate analyses for histological, clinical, and laboratory baseline variables contributing to the progression showed that no histological feature was of prognostic value. Baseline eGFR was associated with disease progression in the entire study population (OR 1.0, 95% CI 0.9-1.0, p = 0.040), but not in the C3G or IC-MPGN subgroups. Serum albumin level was associated with progression in C3G (OR 1.7, CI 1.1-2.8, p = 0.03), but not in IC-MPGN or the whole study population (Supplementary Tables S4 and S5). 4. Discussion Kidney diseases IC-MPGN and C3G have been reported to have similar features. As the presumed pathogenetic processes behind both diseases are diverse and partially overlapping it has remained uncertain whether they could be classified as separate syndromes. Our study shows that the current diagnostic means do not separate the two disease complexes, and their prognoses do not considerably differ either. Because of the multiple causative factors, more precise etiology-based definitions of disease subcategories are needed. As an example, studies on the mechanisms of paraprotein-related disease forms require further attention. Our study consisting of 60 IC-MPGN and C3G patients represents the first analysis of adult MPGN patients in the genetically unique Finnish population. A Korean multicenter retrospective study discovered that the incidence of MPGN was 2.3% , which is somewhat higher than what we observed (0.4-1.5%). The multiple predisposing and etiological factors that contribute to the development of MPGN include infections, autoimmunity, abnormalities in complement activation or regulation, paraproteins, and genetic factors. Several drugs that target the complement system are under investigation for C3G and IC-MPGN, but clinical trials will be challenging and heavily influenced by the heterogeneity of the diseases . In our study, 28% and 22% of IC-MPGN and 33% and 40% of C3G patients had serum paraprotein at baseline and at follow-up visits, respectively. In another study, 41% of MPGN patients had monoclonal gammopathy , while the proportion was 20% in a study of 60 patients with proliferative glomerulonephritis, with an MPGN pattern in only 48% . A study including 14 DDD patients demonstrated that 71% of these patients had MGUS , which is significantly higher than in our study. The mechanisms behind complement-mediated kidney damage are unknown in most cases. For example, a nephritogenic lambda light chain was found to act as a mini-autoantibody against complement factor H in a patient with DDD/MPGN already many years ago . Current evidence suggests that both polyclonal and monoclonal immunoglobulins seem to be involved in immunoglobulin-associated C3G . Any disease causing chronic antigenemia can lead to immune-complex formations and their deposition in the glomeruli. The immune complexes trigger the activation of the classical pathway of complement, leading to the deposition of complement factors. Immunofluorescence typically shows immunoglobulins and complement, and the subsequent morphology of IC-MPGN. Paraproteins are known to be able to cause IC-MPGN and also C3G in cases where paraprotein acts as an autoantibody against complement protein . The underlying mechanisms of complement activation and related pathophysiology are not yet fully understood. Some paraproteins may act as autoantibodies against complement proteins. In these cases, the targets could be factor H, factor B, C3bBb (C3 nephritic factor), or C3b. Other possibilities could be complexes of the paraproteins themselves or immune complexes formed by the paraprotein binding to a glomerular antigen, or to an antigen "planted" within the glomeruli, e.g., as a consequence of infection or tissue trauma. 4.1. Clinical Course, Survival Probability, and Complement Analyses The clinical course in our patients was severe. This is indicated by the fact that eGFR at baseline was abnormal in the majority of the patients in our study. A progressive disease was observed in almost half of the patients, which is in accordance with some previous studies . The two subgroups seemed to resemble each other, as we did not observe significant differences in the clinical course or the survival probability. We chose to include both primary and secondary MPGN cases in our study in order to present a comprehensive patient population of a type that clinicians encounter in their everyday work, in spite of primary and secondary MPGN patients requiring different treatments. We did not, however, observe significant differences in the prognosis of dialysis, transplantation, or death including only primary MPGN and C3G patients in statistical tests. These points suggest that the current subdivision of MPGN does not add substantial value to the assessment of the disease course or prognosis. Similar results were achieved by a clustering analysis of 173 native biopsy patients, in which primary IC-MPGN and C3G were divided into four categories based on multiple clinical and histological features including results from the complement analyses. It seemed that belonging to the cluster consisting of patients with normal levels of blood C3, sC5b-9, and intensive renal biopsy C3 staining was an independent determinant of end-stage renal disease. These were linked to certain histological features (crescents and the number of sclerosed glomeruli) and nephrotic range proteinuria . Collectively, the observations suggest that overactivation of the alternative pathway leads to endothelial damage. Addressing the importance of complement measurements, it was shown in another study that normal C3/high sC5b-9 levels, or low C3/normal sC5b-9 levels, remained independently associated with a worse kidney prognosis in C3G with adult onset of the disease . Many new drugs targeting various sites in the complement cascade are also in clinical trials for MPGN patients . To understand the best treatment for each patient, it is important to study the complement abnormalities in detail. Additionally, it would be important to know the dynamics of complement derangements in the course of the disease. The functions and persistence of autoantibodies should also be clarified. Information about the background and mechanism of the disease is important because a similar medication is unlikely to be suitable for every patient and optimal treatment may even change during the course of the illness. In our study, a form of complement autoantibody was detected in approximately 30% of all patients. Of these, C3Nef was found in 18% of C3G but in none of the IC-MPGN patients at the follow-up visit. Unfortunately, complement variables were not uniformly tested at the time of diagnosis, which prevented proper analyses over the course of the disease. Indeed, this might explain the low rate of hypocomplementemia at diagnosis detected in our study. It is well-known that hypocomplementemia can also fluctuate and the rate of hypocomplementemia at the last follow-up visit could represent the result of various treatments and a more stable phase of the disease. Regardless, out of the tested C3G and IC-MPGN patients at diagnosis, complement autoantibody positivity was found in 50% and 25% of the patients, respectively. These figures are similar in C3G but substantially smaller in IC-MPGN patients than described elsewhere . Factor B and C3b autoantibody positivity in our study was detected in equal numbers in 15% and 6% of C3G and IC-MPGN patients, respectively. Factor B antibodies have been described in 14% of C3G patients in a retrospective study , and in 8.5% in a study that investigated all MPGN patients (primary and secondary IC-MPGN and C3G patients) retrospectively . The latter study revealed anti-C3b positivity in 5.7% of patients and a minority were double positive for C3b and factor B (4%) . 4.2. Histological and Clinical Features Predicting Prognosis Histological light microscopy variables did not significantly differ between the patient groups, but there was a slightly increased frequency of mild interstitial fibrosis in the C3G group, as opposed to the IC-MPGN group. It is unclear whether this reflects the timing of the biopsy as opposed to the course of the disease. Nonetheless, based on the multivariate analysis of histological factors, the amount of fibrosis did not seem to affect the prognosis of the disease. This may merely reflect the low number of patients, as previous studies have concluded that the number of sclerosed glomeruli, crescents, tubular atrophy, and interstitial fibrosis predicts progression in IC-MPGN and C3G patients . It is of notice that LM morphology was variable, and in addition to the classical MPGN-type pattern, other morphologies were evident both in IC-MPGN and C3G. It is possible that the different LM morphologies observed in our study could harbor different prognoses, but as the study population is small, we are unable to test it with all the five different morphological subgroups observed in our study. However, for the entire study population and for the primary and C3G cases, the prognosis of dialysis, transplantation, and death did not show significant differences. Estimated glomerular filtration rate (eGFR) at baseline, 24 h proteinuria, and treatment with immunosuppression were the main determinants of kidney failure in a model with only clinical variables in a study of 111 C3G patients . Kidney function and the amount of proteinuria are generic determinants of poor kidney prognosis in virtually all proteinuric kidney diseases, but only baseline eGFR was a significant prognostic determinant in our study. 4.3. Strenghts and Limitations of the Study Our study was conducted within one hospital district, which ensured that relevant clinical data and the majority of biopsies were available for re-evaluation. In addition, approximately half of the patients attended the research outpatient follow-up visit, allowing further complement testing. While this study was informative, there were some limitations. As we chose to include both primary and secondary MPGN patients in our study in order to present a real-life situation and in order to maintain an adequate study population for statistical purposes, the patient populations with primary and secondary MPGN cases remain heterogenous, limiting the analyses of treatment protocols and prognosis. Moreover, MPGN and C3G are rare kidney disorders, which causes the number of patients included in this study to be limited even when including both primary and secondary cases. This limits the ability of statistical tests to show significant differences. Moreover, as the study group consisted of IC-MPGN and C3GN patients, only one DDD patient was enrolled, preventing the study of differences between DDD and C3GN. The fact that pediatric patients were excluded may have influenced this finding, as DDD is more commonly seen in children. Additionally, diagnostic biopsies from some patients were taken before the research period and were not available for re-evaluation. Moreover, we were unable to have results for detailed complement testing at baseline due to the retrospective nature of the study. At a follow-up visit, the pattern of functional complement testing did not include terminal pathway activation, C4 nephritic factor (C4Nef), or C5 nephritic factor (C5Nef), which could be implemented in the armamentarium of complement tests in these patients. Moreover, approximately half of the patients did not attend the research outpatient visit limiting the comprehensive laboratory, immunologic, and genetic testing performed. In addition, further investigations including genetic testing and MLPA analyses of the FH/FHR gene region are warranted. The fact that the patients were enrolled in only one hospital district may limit the generalizability of these findings. The low number of patients limited the use of thorough multivariate analyses. 5. Conclusions The current division of patients into IC-MPGN and C3G diagnostic groups did not reveal substantial differences in the clinical course, nor in the overall or renal survival. This might suggest that subdividing these patients into currently widely used groups may be unnecessary. Perhaps clustering these patients and taking multiple factors beyond histology into consideration could help with decisions on the prognosis and optimal treatments of MPGN patients. Histological features in MPGN can manifest as different types of morphology depending on the timing of the biopsy and the activity or chronicity of the disease, and it does not always manifest as a classical MPGN-type pattern. Further detailed analyses of individual patients are important in delineating the precise mechanisms of the underlying diseases. Acknowledgments We acknowledge professional statistician Aku-Ville Lehtimaki for carrying out statistical analyses for this research article. Supplementary Materials The following supporting information can be downloaded at Table S1: Full list of excluded diseases not fulfilling diagnostic criteria for IC-MPGN or C3G or index biopsy only showing MPGN-type of pattern as a secondary damage to another known disease/condition or poor/inadequate biopsy sample. Table S2: Blood complement analysis performed on patients attending the research outpatient visit. Table S3: Immunofluorescence and electron microscopy findings on index biopsies. Values are expressed as means (SD) or numbers (percentage) of patients. The number of patients signifies the maximum number of patients with the information. Table S4: Multivariate analysis for histological determinants of progressive disease. Table S5: Multivariate analysis for baseline clinical and laboratory determinants of progressive diseases. Click here for additional data file. Author Contributions This research article was conceptualized, and methodology determined, by the whole research team, M.K., M.S., K.K., A.R.-S., E.H. and S.M. Histological investigation and curation was performed by M.K. and A.R.-S., clinical data curation by M.S. and K.K. Clinical data curation and clinical outpatient follow-up visits were performed by M.S., K.K. and E.H. Complement testing of outpatient follow-up visits was performed by M.K. under the supervision of S.M. The whole data source was assembled and curated by M.K. and M.S. The original draft preparation was performed by M.K. and M.S. Tables were executed by M.K. and figures were executed by M.K. and A.R.-S. M.K., M.S., A.R.-S., E.H., S.M. and K.K. edited the article. The project was administered and supervised by K.K. and A.R.-S. Funding was acquired by the research team members themselves. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and the study was reviewed by the Hospital's Ethical Committee (HUS/2520/2018 date) and a research permit (HUS/459/2018 date) was granted. Informed Consent Statement Informed consent was obtained from all patients who were evaluated on follow-up visits and signed a declaration of informed consent. Patient consent was waived from other patients due to the fact that this was a retrospective registry-based study that was conducted in accordance with the Hospital's Ethical Committee permission (HUS/2520/2018). Data Availability Statement The data that support the findings of this study are available from the corresponding author, M.K., upon reasonable request. The data that support the findings of this study are not publicly available due to ethical reasons and due to privacy reasons of research participants. Data availability can be requested from the corresponding author, M.K., upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Study flow of the research patients. * After index biopsy re-evaluation, patients were reassigned to an accurate diagnostic category, ** For one C3G patient complement analysis sample was acquired before research visit and included in complement analysis (total n = 30). PIGN = postinfectious glomerulonephritis, TMA = thrombotic microangiopathy, C3G = C3 glomerulopathy, IC-MPGN = immune-complex-mediated glomerulonephritis. Figure 2 Different morphological features of the index biopsies of IC-MPGN and C3G patients may indicate different activity of the glomerulonephritis (GN) and/or the time point of injury. (A) Minimal to mild mesangial expansion, (B) mesangioproliferative injury, (C) classical membranoproliferative injury with lobular/nodular proliferation and double contours in basement membranes, (D) crescentic injury, (E) exudative GN that can be difficult to distinguish from postinfectious GN in the early phase. However, it usually resolves within 3-6 months, whereas C3G or IC-MPGN do not, (F) Normal glomerulus for reference, (G) IF showing coarse granular C3 positivity in mesangial areas and basement membranes, (H,I) Electron-dense deposits on subendothelial and mesangial spaces. (A-F) Periodic Acid-Schiff staining, (G) frozen section C3 immunofluorescence staining, (H,I) electron micrograph. Figure 3 Different morphological features were observed on light microscopy (LM) in IC-MPGN and C3G patients. Differences in subcategory division between the patient groups were not significant (p > 0.05 for comparisons). Figure 4 Longitudinal changes from diagnosis to dialysis with numbers at risk: (a) for the entire study population; (b) for primary MPGN and C3G cases. The yellow line indicates IC-MPGN and the blue line indicates C3G. Colored areas indicate confidence interval and small vertical lines indicate the end of follow-up. Figure 5 Longitudinal changes from diagnosis to transplantation with numbers at risk: (a) for the entire study population; (b) for the primary MPGN and C3G cases. The yellow line indicates IC-MPGN and the blue line indicates C3G. Colored areas indicate confidence interval and small vertical lines indicate the end of follow-up. Figure 6 Longitudinal changes from diagnosis to death with numbers at risk: (a) for the entire study population; (b) for primary MPGN and C3G cases. The yellow line indicates IC-MPGN, and the blue line C3G. Colored areas indicate confidence interval and small vertical lines indicate the end of follow-up. cells-12-00712-t001_Table 1 Table 1 Patient characteristics at baseline. Values are expressed as means (range or SD) or numbers (percentage) of patients. Reference values and units are given where appropriate. The number of patients indicates the maximum number of patients available with the information. Unless otherwise indicated, the parameter values were available for all patients. The differences between the groups were not significant (p > 0.05 for all comparisons). Baseline Variable IC-MPGN, n = 37 C3G, n = 23 Age, years (range) 52 (5-78) 54 (16-79) Male sex, n (%) 23 (62) 13 (57) BMI (kg/m2) (SD) 28.8 (6.3), n = 34 26 (4.3), n = 22 Smoking Current, n (%) 9 (27), n = 34 7 (32), n = 22 Former, n (%) 14 (41), n = 34 11 (50), n = 22 Diabetes, n (%) 2 (6), n = 34 4 (17) Hypertension, n (%) * 36 (97) 23 (100) Rheumatic disease, n (%) 2 (6), n = 34 4 (17) Chronic infection, n (%) 7 (21), n = 34 3 (13) Malignancy, n (%) 2 (6), n = 34 4 (17) Plasma cell dyscrasia, n (%) ** 8 (24), n = 34 6 (26) Cardiovascular disease, n (%) 10 (29), n = 34 7 (30) Duration of renal findings before diagnosis, years, (range) 1.3 (0-9), n = 27 1.4 (0-7) Macroscopic hematuria, n (%) 4 (13), n = 31 6 (27), n = 22 Diagnostic biopsy Transplant, n (%) 1 (3) 2 (9) Native kidney, n (%) 36 (97) 21 (91) Diagnostic biopsy taken before index biopsy, n (%) 7 (19) 1 (4) SD = standard deviation, BMI = body mass index. The upper limit of normal for hypertension is 135/85 mmHg. * Hypertension is defined as systolic and/or diastolic blood pressure that is over the limit and/or the use of antihypertensive medication; ** myeloma is excluded. cells-12-00712-t002_Table 2 Table 2 Renal function and laboratory variables at baseline. Values are expressed as means (SD) or numbers (percentage) of patients. Reference values and units are given where appropriate. Number of patients signifies the maximum number of patients available with the information. If variable values were not available for all patients, it is expressed in the table. None of the differences between the groups were significant (p > 0.05 for all comparisons). Baseline Variable IC-MPGN, n = 35 C3G, n = 23 eGFR (SD) * 56 (32) 49 (27), n = 22 eGFR decreased, n (%) 22 (63) 16 (73), n = 22 S-creat, mmol/L (SD) 155 (99) 166 (121) Urine dipstick proteinuria positive, n (%) 33 (97), n = 34 21 (100), n = 21 Urine alb/creat, mg/mmol (SD) 192.6 (160.6), n = 15 158.8 (171.5), n = 9 Urine protein excretion, g/24 h (SD) 5.3 (4.2), n = 34 3.6 (3.3), n = 21 Nephrotic proteinuria (<3 g/24 h), n (%) 23 (68), n = 34 9 (43), n = 21 Microscopic hematuria, n (%) 28 (90), n = 31 20 (100), n = 20 Alb, g/L (SD) 27 (6) 25 (6) Hb, g/L (SD) 116 (18) 116 (19) CRP, mg/L (SD) 13 (20) 37 (81) LDL, mmol/L (SD) 3.5 (1.5) 3.3. (1.7) ENA-Ab positivity, n (%) 0 (0) 1 (14) SD = standard deviation, Creat = creatinine (upper limit of normal <= 100 for male and <= 90 for female), Urine alb/creat = urine albumin/creatinine (upper limit of normal 2.5 mg/mmol for male, 3.5 mg/mmol for female), Alb = albumin (36-45 g/L), Hb = hemoglobin (134-167 for male, 117-155 for female), CRP = C-reactive protein (upper limit of normal 4 mg/L), LDL = low-density lipoprotein (upper limit of normal 3 mmol/L), ENA-Ab = extractable nuclear antigen antibody. * eGFR = estimated glomerular filtration rate, calculated according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation (EGFR lower limit of normal >= 60 mL/min/1.73 m). cells-12-00712-t003_Table 3 Table 3 Histological parameters of index biopsies. Values are expressed as means (SD) or numbers (percentage) of patients. The number of patients signifies the maximum number of patients with the information available. Variable IC-MPGN, n = 37 C3G, n = 21 * p-Value Glomerular changes % of sclerotic glomeruli 17 (47), n = 36 11 (52) 1.000 Biopsies containing crescents, n (%) 5 (13.5) 4 (19) 0.710 Mesangial matrix expansion none, n (%) 10 (27) 6 (29) 1.000 mild, n (%) 8 (22) 6 (29) 0.761 moderate, n (%) 6 (16) 2 (10) 0.703 strong, n (%) 13 (35) 7 (33) 1.000 Lobulated pattern of glomeruli, n (%) 20 (54) 9 (43) 0.811 Doubled GBM None, n (%) Mild, n (%) Moderate, n (%) Strong, n (%) 3 (8) 7 (19) 3 (8) 24 (65) 4 (19) 5 (24) 2 (10) 10 (48) 0.415 0.751 1.000 0.648 Tubulointerstitial changes Total interstitial inflammation None, n (%) Mild, n (%) Moderate, n (%) Strong, n (%) 27 (73) 4 (11) 4 (11) 2 (5) 10 (48) 8 (38) 2 (10) 1 (5) 0.379 0.062 1.000 1.000 Interstitial fibrosis None, n (%) Mild, n (%) Moderate, n (%) Strong, n (%) 29 (78) 4 (11) 2 (5) 2 (5) 10 (48) 9 (43) 2 (10) 0 (0) 0.375 0.059 0.623 0.537 Tubular atrophy None, n (%) Mild, n (%) Moderate, n (%) Strong, n (%) 24 (65) 11 (30) 0 (0) 2 (5) 10 (48) 10 (48) 0 (0) 1 (5) 0.648 0.437 1.000 1.000 Arteriolar sclerosis None, n (%) Mild, n (%) Moderate, n (%) Strong, n (%) 17 (49), n = 35 12 (34), n = 35 6 (17), n = 35 0 (0), n = 35 11 (52) 8 (38) 2 (10) 0 (0) 1.000 1.000 0.7 1.000 * Two C3G patients had inadequate material for light microscopy (LM) but were adequate for immunofluorescence (IF) and electron microscopy (EM) to conclude the diagnosis. GBM = glomerular basement membrane. cells-12-00712-t004_Table 4 Table 4 Complement and paraprotein characteristics during the last outpatient visit. Values are expressed as means (SD) or numbers (percentage) of patients. The number of patients signifies the maximum number of patients with the information. Unless otherwise indicated, the variable numbers were available for all patients. None of the differences between the groups were significant (p > 0.05 for all comparisons). Variable IC-MPGN, n = 23 C3G, n = 17 Complement proteins S-C3, g/L (SD) Decreased (lower limit of normal 0.5 g/L), n (%) 1.0 (0.2), n = 21 1 (5) 0.9 (0.3) 1 (7) S-C4, g/L (SD) Decreased C4 (lower limit of normal >0.12), n (%) 0.2 (0.1), n = 20 2 (10) 0.2 (0.1) 3 (21) FHR1-3 heterozygous deletion, n (%) 5 (29), n = 17 4 (31), n = 13 Functional complement analysis S-CH100AI, % (SD) Decreased, n (%) 93 (31), n = 18 1 (6) 75 (33), n = 14 2 (14) S-CH100CI, % (SD) Decreased, n (%) 95 (25), n = 18 2 (11) 77 (34), n = 14 4 (29) S-CH100L, % (SD) Decreased, n (%) 50 (53), n = 18 8 (44) 58 (42), n = 14 3 (21) Complement autoantibodies C3Nef positivity, n (%) 0 (0), n = 22 2 (18), n = 11 Factor H-antibody positivity, n (%) * 1 (6), n = 18 1 (8), n = 13 Factor B antibody positivity, n (%) 1 (6), n = 17 2 (15), n = 13 C3b-antibody positivity, n (%) 1 (6), n = 17 2 (15), n = 13 C3 activating factors classical pathway activator, n (%) alternative pathway activator, n (%) 2 (12), n = 17 2 (12), n = 17 0 (0), n = 13 0 (0), n = 13 Paraproteins Free kappa light chain in serum, mg/L (SD) 66.9 (77.2) 79 (80.9), n = 14 Free lambda light chain in serum, mg/L (SD) 37.4 (31.9) 64.5 (53), n = 14 Kappa/lambda light chain ratio (SD) 1.6 (1) 1.2 (0.4), n = 15 Serum paraprotein, n (%) 5 (22) 6 (40), n = 15 Urine paraprotein, n (%) 0 (0), n = 16 3 (25), n = 12 C3 = complement C3 (0.5-1.5 g/L), C4 = complement C4 (0.12-0.42 g/L), FHR1-3 = factor H-related-protein 1-3 (deletion determined by immunoblotting), CH100Al = activity of the alternative pathway of complement (<39%), CH100Cl = activity of the classical pathway of complement (>74%), CH100L = activity of the lectin pathway of complement (>10%), C3Nef = Complement C3 nephritic factor, free kappa light chains (6.9-25.6 mg/L), free lambda light chains (8.6-26.5 mg/L), kappa/lambda light chain ratio (0.52-1.40). * Weakly positive (+/-) results are also considered positive. cells-12-00712-t005_Table 5 Table 5 Treatment, including medications at baseline and during follow-up as well as data on kidney replacement therapy and follow-up. Values are expressed as means (range or SD) or numbers (percentage) of patients. Number of patients signifies the maximum number of patients with the information. Unless otherwise indicated, the variable numbers were available for all patients. Immunosuppressive medication denotes treatment aimed at kidney disease (not due to kidney transplantation). Differences between the groups were not significant (p > 0.05 for all comparisons). Variable IC-MPGN, n = 37 C3G, n = 23 Immunosuppressive medication at baseline Corticosteroids, n (%) Mycophenolate mofetil, n (%) Other, n (%) * 3 (9), n = 34 0 (0), n = 33 1 (3) 6 (26) 1 (5) 1 (4) Immunosuppressive medication during follow-up Corticosteroids, n (%) Mycophenolate mofetil, n (%) Other, n (%) * 17 (46) 5 (14) 8 (22) 13 (57) 6 (26) 7 (30) Follow-up Dialysis during follow-up, n (%) 8 (22) 7 (30) Kidney transplantation during follow-up, n (%) 8 (22) 4 (17) Progressive disease, n (%) 16 (43) 11 (48) More than one kidney transplant, n (%) 3 (8) 1 (4) Follow-up time from diagnostic biopsy, years (range) 8.1 (0.9-39.1) 5.9 (0.6-25.7) Time from diagnostic biopsy to start of 1st dialysis, months (range) 59 (0.2-140), n = 10 30 (0.2-61), n = 9 Time from diagnostic biopsy to 1st transplantation, months (range) 83 (33-165), n = 6 51 (34-70), n = 3 * Cyclosporin A, tacrolimus, azathioprine, rituximab, or cyclophosphamide. 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PMC10000504 | Background: Gastric cancer is a malignant tumor with high morbidity and mortality. Therefore, the accurate recognition of prognostic molecular markers is the key to improving treatment efficacy and prognosis. Methods: In this study, we developed a stable and robust signature through a series of processes using machine-learning approaches. This PRGS was further experimentally validated in clinical samples and a gastric cancer cell line. Results: The PRGS is an independent risk factor for overall survival that performs reliably and has a robust utility. Notably, PRGS proteins promote cancer cell proliferation by regulating the cell cycle. Besides, the high-risk group displayed a lower tumor purity, higher immune cell infiltration, and lower oncogenic mutation than the low-PRGS group. Conclusions: This PRGS could be a powerful and robust tool to improve clinical outcomes for individual gastric cancer patients. gastric cancer prognostic signature tumor microenvironment oncogenic mutation clinical outcomes machine learning National Key Research and Development Program of China2017YFA0505503 Beijing Municipal Natural Science FoundationZ200021 Research Funds for the Central Universities2019RC045 National Key Research and Development Program of China2021YFE0201100 2022YFA1103401 CAS Interdisciplinary Innovation TeamJCTD-2020-04 National Natural Science Foundation of China81890991 This work was funded by the National Key Research and Development Program of China (2017YFA0505503), Fundamental Research Funds for the Central Universities (2019RC045), Beijing Municipal Natural Science Foundation (Z200021), National Key Research and Development Program of China (2021YFE0201100, 2022YFA1103401), the National Natural Science Foundation of China (81890991), CAS Interdisciplinary Innovation Team (JCTD-2020-04). pmc1. Introduction Gastric cancer (GC) is a leading cause of cancer morbidity and mortality worldwide . According to GLOBOCAN 2020, there were about 1,089,103 new cases of gastric cancer patients (5.6% of the total cancer burden) . Disease progression and a lack of effective treatment cause most of the mortality . Therefore, preventing "high-risk" GC is the key to improving clinical outcomes. The tumor, node, metastasis (TNM) classification and the American Joint Committee on Cancer (AJCC) classification are commonly used methods to assess the risk and treatment demand for patients in the clinical setting. Nevertheless, due to the limitation of the current grading system, it cannot provide the best clinical treatment for patients. For example, in the clinic, the decision of adjuvant chemotherapy (ACT) is mainly dependent on the clinical-pathological stage rather than molecular biological characteristics . This approach is insufficient and may result in latent overtreatment or undertreatment. Hence, in the era of individualized treatment, it is imperative to identify effective biomarkers to optimize the prognosis of GC. The ideal biomarker should have a consistent expression within and between tumor tissues to perform stably among all patients. Hence, a multigene signature may be an effective approach for addressing this heterogeneity. To date, there are three categories of clinically important GC markers, CEA, CA19-9, and CA72-4, with positive rates of 21.1%, 27.8%, and 30.0%, respectively . However, they are present in a limited number of patients with GC, and the sensitivity and specificity of these biomarkers are not sufficient. With the development of bioinformatics technology, many prognostic biomarkers have been published . Unfortunately, most of the identified biomarkers failed in the validation. GC is a heterogeneous malignant disease. Histologically, the human gastric mucosa can be divided into three zones, i.e., the cardiac zone, the fundus/corpus zone, and the pyloric zone . These zones differ vastly in their histology, regeneration rates, and profiles . In addition, there are different morbidity and mortality rates among GC in these three zones. It is believed that GC patients with the GC localized in the cardiac zone have the worst prognosis. As the patient's age progresses, the location of the gastric cancer moves upward, and the incidence of it occurring in the cardiac zone increases . The composition of cell types within them is also discrepant. For instance, the quantities of gastric parietal cells are considerably different in these three zones. Namely, parietal cells account for 25%, 50-100%, and 0-1% of all cells in the cardiac zone, the fundus/corpus zone, and the pyloric zone, respectively . Of note, most researchers who investigate gastric cancer biomarkers have ignored the differences between these three zones and analyzed them as if all gastric cancers are of one single area. Hence, it is essential to construct gene co-expression networks and select prognostic-related genes separately for GC data in these three zones. In this work, we attempted to computationally develop and experimentally validate a prognostic risk gene signature with 1226 GC patients from three independent public datasets (Tables S1-S4), a gastric cancer cell line, and several clinical samples to assess the prognosis, tumor growth, and molecular characterization of GC. A multi-step procedure of machine-learning approaches was performed to develop and cross-validate the prognostic risk gene signature (PRGS) model based on the co-expression networks of GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone. This PRGS may help optimize precision treatment and further improve the clinical outcomes of GC patients. 2. Materials and Methods 2.1. Data Acquisition and Processing In this study, we used three independent public datasets, including 1226 GC patients obtained from the UCSC Toil Recompute Compendium of The Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (TCGA target GTEx, primary_site = stomach) and the Gene Expression Omnibus (GEO) (Tables S1-S4). These datasets (TCGA target GTEx, GSE66229, and GSE15459), which encompass complete overall survival (OS) information, were used. Among these, we converted the RNA-seq raw read count from the TCGA target GTEx database to transcripts per kilobase million (TPM) and then log2-transformed. And the data has been removed batch effects among these patients . We retrieved GSE15459 and GSE66229 from the Affymetrix(r) GPL570 platform (Human Genome U133 Plus 2.0 Array). We selected the most highly expressed probe for each gene to ensure reliable results in consensus clustering and we reserved all probes of each gene to ensure accurate results in binary classification. The ATAC-seq and somatic variation data were obtained from the database of the Genomic Data Commons Data Portal accessed on 1 February 2022). 2.2. Human Tissue Specimens In this study, the collection of gastric tissues was approved by the Department of Gastroenterology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China, on 1 June 2022. Overall, one advanced GC sample, an early GC sample, and a normal gastric sample were collected. All patients provided written informed consent, and the ethics committee of the PLA General Hospital also approved our research. 2.3. Differentially Expressed Analysis and Weighted Correlation Network Analysis The DEGs between cancer and normal samples were detected by edgeR . The genes with an absolute log2 (fold change) >= 1.5 were considered to be significant differentially expressed genes (DEGs) between tumor and normal tissues. The volcano plots of upregulated or downregulated genes were generated by the ggplot2 R 4.0 package. The Venn diagram was plotted by the VennDiagram R 4.0 package. The co-expression gene networks were constructed by the WGCNA package . To recognize modules of significantly correlated clusters in the cardiac zone, the fundus/corpus zone, and the pyloric zone, the module that displayed the highest correlation was selected. 2.4. Construction of the Co-Expression Network The brown, purple, and salmon modules of the result of WGCNA were used for the edges, signifying the correlations in the cardiac zone, the fundus/corpus zone, and the pyloric zone, respectively. The filter criterion of a weight value was set to greater than 0.02. A total of 25,350, 1819, and 706 edges and 308, 69, and 54 nodes correlated with these zones were separately obtained and processed in Cytoscape 3.8.1 . To construct the network and select the hub genes, the Cytoscape software was used with the CytoHubba method . 2.5. PRGS Signature Generation LASSO is a regularization and dimensionality reduction technique combined with Cox models, which can be applied in biomarker screening . To identify the hub genes, the top 25 genes of the co-expression network from the cardiac zone, the fundus/corpus zone, and the pyloric zone by Cytoscape were inputted into the LASSO-Cox regression . To ensure the stability of the gene and the model, this procedure was repeated 1000 times. Then, the regression coefficients of each gene were calculated (Table S5). Ultimately, genes with positive regression coefficients were selected. Four genes (APOB, VCAN, ABCA6, and CTSF) whose p-values in the Kaplan-Meier analysis were also < 0.05 were identified to generate the PRGS model. The PRGS risk score of GC patients was calculated by the formula: PRGS score = k=14(41)bk x RNAk. In this formula, k means the genes in the PRGS--we used k = 1, 2, 3, 4 to index the genes in the PRGS--the b value was the multivariate Cox regression coefficient; and RNAk means the expression level of gene k of each patient. 2.6. Chromatin Accessibility Analysis The peak regions on chromosomes were shown by the R package chromosome locator. Using the R-packaged ChIPseeker, the alignment can be mapped to peaks in the TSS region to build a signature matrix. Peak position annotation and motif enrichment analyses were performed using HOMER (V4.10). In the range of +-1 kb around the TSS, the peak overlapping the gene initiator was considered as the peak of gene regulation. 2.7. Consensus Clustering This process was accomplished through the ConsensusClusterPlus package . We subsampled 80% of the samples, and then used the k-means algorithm to divide each subsample into k (k = 9) according to the Euclidean distance. This procedure was repeated 1000 times. Finally, using the PAC with the smallest k value, the optimal cluster (k = 2) was derived. 2.8. Binary Classification (1) We pre-processed the GSE66229 data and selected the top 5 genes from the three generated co-expression networks of the three zones' expression spectrum matrices, then divided the data into normal and tumor samples. We also generated the GSE66229 data and generated PRGS, CEA , and GCscore expression spectrum matrices. (2) We performed 5-fold cross validation using the logistic regression classifier (LR) and the random forest classifier (RF) on the GSE66229 and computed the ROC curve for each fold. We then calculated the means of every fitting curve to generate the plot. We then divided the data into five subsets based on the sample tags "Tumor/Normal", "Stage 1/Normal", "Stage 2/Normal", "Stage 3/Normal", and "Stage 4/Normal". Details of the data are shown in Table S4. The parameters were set as follows: RF, max_depth = 5, n_estimators = 5, random_state = 123; LR, solver = "liblinear", penalty = "l2", C = 1.0. The rest were set as default. We trained and validated each fold and calculated the FPR, TPR, and AUC. We fitted each result into the ROC curve using np.interp and took the means of all fitting curves to craft the figure. 2.9. Haematoxylin-Eosin (HE) and Immunohistochemistry (IHC) For HE staining, a 4% paraformaldehyde solution was used to fix GC tissues. After 24 h, the GC tissues were dewaxed in xylene, dehydrated in ethanol, and subjected to hematoxylin staining (5 min), then dehydrated in eosin solution (10 s), dehydrated in graded alcohol, removed in xylene, and sealed with neutral glue. They were observed and photographed with a microscope (Olympus, Tokyo, Japan). For IHC, 5% bovine serum was used to incubate sections. Then, they were mixed with primary antibodies (anti-APOB, 1:100; anti-VCAN, 1:100; anti-ABCA6, 1:200; and anti-CTSF, 1:200, Abcam, UK) and a secondary antibody (1:800, Abcam, Cambridge, UK). Then, they were stained with a DAB kit and photographed with an optical microscope (Olympus, Japan). 2.10. Cell Culture, Transfection, and Immunostaining GES-1 gastric cancer cells (a gift from Prof. Jun Qin) were cultured with 5% CO2 at 37 degC in Dulbecco's modified Eagle's medium (DMEM) (Thermo Fisher, Waltham, MA, USA, C11995500BT) with 20% FBS and 100 mg/mL penicillin/streptomycin. For the siRNA treatment, LipofectamineTM 3000 Transfection Reagent (Thermo Fisher, L3000001) was used to transfect cells using a standard procedure. For immunostaining, poly-l-lysine-coated coverslips were used to culture cells for 72 h to perform the siRNA transfection; 4% paraformaldehyde was used to fix the cells for 10 min, and then the cells were washed with PBSTr buffer (PBS plus 0.1% Triton X-100, Sigma-Aldrich, St. Louis, MO, USA T8787). The cells were incubated with the anti-phosphorylated histone 3 (pH3) antibody overnight at 4 degC. The cells were incubated with a secondary antibody at room temperature and washed with PBSTr buffer. Then, 0.01 mg/mL DAPI and the Vectashield Antifade Mounting Medium (Vector Laboratories, San Francisco, CA, USA H-1200) were used to incubate and mount the cells, respectively. 2.11. Flow Cytometric Analysis For flow cytometric analysis of the cell cycle with propidium iodide (PI) staining, a standard procedure was used . 2.12. Quantitative Real-Time PCR The Eastep Super Total RNA Extraction Kit (Promega, Madison, WI, USA LS1040) was used to extract the total RNA of siRNA-treated GES-1 cells. The Eastep RT Master Mix Kit (Promega, LS2050) was used to synthesize the cDNA. An Applied Biosystems 7500 real-time PCR system (Thermo Fisher) was used to perform real-time PCRs with the PowerUp SYBR Green Master Mix (Thermo Fisher, A25776). The comparative CT method and Graphpad Prism 8 (GraphPad Software, La Jolla, CA, USA) were used to analyze the data. All experiments were repeated three times. 2.13. Cell Infiltration Estimation ESTIMATE and CIBERSORT were used to evaluate immune infiltrates. The immune scores, stromal scores, and tumor purity were calculated by the ESTIMATE algorithm. CIBERSORT was used to analyze the levels of infiltrating immune and stromal cells. 2.14. Tumor Mutation Status Analysis Maftools was used to calculate significantly mutated genes (p < 0.05) between the high-PRGS groups . A one-sided z-test and two-sided Chi-square test were used to calculate the statistical test for the proportion of mutations (p < 0.05). 2.15. Functional Enrichment Analysis A functional enrichment analysis was performed on DEGs and peak-related genes. The possible peak-related genes of GO/KEGG enrichment were used to analyze the ClusterProfiler package in R . Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used to annotate the tumor-related pathways. The gene set variation (GSVA) method was used to enrich the pathways. We used the enrichment score of the GSVA to obtain the expression pathway of the PRGS. 3. Results 3.1. Construction of the Gene Modules The workflow of this work is shown in Figure 1. First, we identified the differentially expressed genes (DEGs) in the TCGA target GTEx with the edgeR package independently to screen DEGs in normal samples and GC samples from the cardiac zone, the fundus/corpus zone, and the pyloric zone. For GC in the cardiac zone, 1498 upregulated and 883 downregulated DEGs were identified. A total of 1661 upregulated and 826 downregulated DEGs were found between normal and GC samples from the fundus/corpus zone. There were 1542 upregulated and 889 downregulated DEGs for GC in the pyloric zone compared with normal samples (Table S5). The distributions of DEGs are shown by volcano plots . There were 1553 DEGs shared among the GC samples from the three zones . We adopted GO and KEGG enrichment analysis methods to investigate the annotation of the DEGs. The DEGs of GC samples from the cardiac zone were mainly enriched in sensory perception (GO:0050907), the collagen-containing extracellular matrix (GO:0062023), the sarcomere (GO:0030017), and olfactory transduction. Sensory perception (GO:0050907), the ion channel complex (GO:0034702), olfactory receptor activity (GO:0004984), and olfactory transduction were detected in GC samples from the fundus/corpus zone. In addition, the GC samples from the pyloric zone were highly associated with digestion (GO:0007586), the collagen-containing extracellular matrix (GO:0062023), receptor-ligand activity (GO:0048018), and neuroactive ligand-receptor interactions . To further identify the gene modules related to GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone, the WGCNA method was applied. We assured a scale-free network (soft threshold = 3) with a high scale independence and a low mean connectivity (near 0) . DEGs in the GC samples from the cardiac zone, the fundus/corpus zone, and the pyloric zone were respectively divided into 22 modules by a cluster analysis . The brown module related to GC in the pyloric zone was the most significant (cor = 0.76, p = 2 x 10-112). For GC in the cardiac zone and the fundus/corpus zone, the purple and salmon modules were chosen according to the correlation (cor = 0.22, 0.33; p = 3 x 10-8, 1 x 10-16). We selected the brown, purple, and salmon modules for the edges, representing the correlations in GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone, respectively, by the WGCNA algorithm . The Cytoscape software was used to visualize the gene co-expression networks , and Cytohubba was used to select hub genes . We also performed a GO and KEGG enrichment analysis of the purple (correlated with the cardiac zone), salmon (correlated with the pyloric zone), and brown (correlated with the fundus/corpus zone) modules . We performed a survival analysis of the genes from the co-expression networks of the three zones on GC patients in the TCGA target GTEx and GSE66229 datasets (GSE15459 did not have information on the three zones). The results indicated that the top five genes (APOA4, MS4A10, SLC28A1, AQP10, and APOB) from the cardiac zone co-expression network correlated most significantly with the outcomes of GC patients in the cardiac zone compared to GC patients of the other two zones . The same was true for patients with GC in the fundus/corpus zone. The top five genes (VCAN, COL1A2, FAP, PODNL1, and SULF1) from the fundus/corpus zone co-expression network also displayed the vastest correlation with the fundus/corpus zone GC patients compared to GC patients of the other two zones . Meanwhile, we a performed binary classification using the logistic regression classifier (LR) and random forest classifier (RF) with the hub genes (APOA4, MS4A10, SLC28A1, AQP10, and APOB) of GC in the cardiac zone as the feature genes to predict whether patients have GC, and we achieved the highest AUC in patients with GC of the cardiac zone compared to the other two zones in the GSE66229 datasets . The same was true for the hub genes (VCAN, COL1A2, FAP, PODNL1, and SULF1) of GC patients in the fundus/corpus zone . These results further indicated that discriminating among different zones of GC is of great importance. 3.2. Construction and Cross-Validation of the PRGS Model in Gastric Cancer Cohorts To further determine the prognostic genes related to the three zones of GC, we continued to generate predictive genes using the TCGA target GTEx and cross-validated these genes with two independent datasets (GSE66229 and GSE15459). Based on the expression profiles of 25 genes correlated with GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone, a LASSO-Cox regression analysis generated the predictive genes. This process was repeated 1000 times with the glmnet R package to ensure the stability of the gene . In the LASSO regression, the partial likelihood of deviance reached the minimum value to obtain the optimal l . Six, four, and three genes from GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone, respectively, with positive LASSO coefficients were subjected to the log-rank test and the Kaplan-Meier curve , which identified a final set of four genes. There were four genes with the maximum coefficient of GC in the three zones, including APOB (p-value = 0.028, FDR = 0.0042) correlated with GC in the cardiac zone, VCAN (p-value = 9.2 x 10-25, FDR = 0.0004) correlated with GC in the fundus/corpus zone, and ABCA6 (p-value = 0.0028, FDR = 0.0042) as well as CTSF (p-value = 0.023, FDR = 0.023) correlated with GC in the pyloric zone. For each of these four genes, the increased expression level was vastly associated with a worse OS for gastric cancer patients . Besides, these four genes (APOB, VCAN, ABCA6, and CTSF) are included in the DEG lists in the GC data of respective zones in dataset GSE66229. We next depicted the PRGS expression level at a single-cell resolution. We analyzed the scRNA-seq data derived from 29 gastric cancer and 11 normal gastric tissues . After the quantity control and removal batch effect, we obtained a total of 200,954 cells majorly comprising lymphoid cells (CD8A and KLRD1 positive), plasma (TNFRSF17 positive), epithelial cells (CDH1 positive), macrophages (CD163 positive), fibroblasts (FN1 and LUM positive), B cells (MS4A1 positive), mast cells (KIT positive), and pericytes (NOTCH3 positive) . As shown in Figure S5B, VCAN was expressed in macrophages and fibroblasts; ABCA6 and CTSF were mainly expressed in fibroblasts; and APOB was expressed in epithelial cells . We also observed that GC samples in different Lauran classifications (intestinal, diffuse, and mixed types) exhibited higher PRGS scores than normal samples . We computed global PRGS scores for all cell types and found that fibroblasts had the highest PRGS scores compared to other cell types . We also identified the chromatin accessibility of these four genes; thus, we analyzed the relative enriched proportions of coding regions, intergenic regions, introns, exons, and upstream and downstream regions with ATAC-seq data from TCGA. The peak annotation demonstrated that the peaks of these genes were more likely to be located in promotor regions . We also performed motif enrichment and calculated potential regulatory TFs within the 200 bp range of gene loci based on genes from the PRGS model with HOMER . A KEGG analysis of the peaks was also performed . The risk score for each patient was then calculated using the expression matrix of these four genes (APOB, VCAN, ABCA6, and CTSF) weighted by their regression coefficients in the Cox model (Table S7). All patients were divided into low-PRGS groups by the survminer package . As can be seen from Figure 3B, the overall survival (OS) was significantly lower in the high-PRGS group relative to the low-PRGS group in the TCGA target GTEx training dataset and the two validation datasets (all with p < 0.05) . In Figure S9A, we see the distribution of the PRGS scores for the patient group, as well as the relationship between the PRGS and survival time. The cut-off for the low-PRGS groups was 50%. We also evaluated the PRGS in Lauren and WHO histotypes. The results shown in Figure S9B-D also indicate that the overall survival (OS) of all classifications was significantly lower in the high-PRGS group relative to the low-PRGS group in the TCGA target GTEx training dataset and the two validation datasets (all with p < 0.05) (The GSE66229 and GSE15459 only provide the information of Lauran classification). Then, we assessed the OS status in different TNM stage groups. As shown in Figure S10A,B,D,E, the high-PRGS group was tightly correlated with a worse OS status in late stages in TCGA target GTEx (T3, T4, N2, and N3) and in GSE66229 (T2, T3, N1, N2, and N3). The high-PRGS group was vastly associated with a worse OS status in the M0 stage and most of the patients in these datasets were in the M0 stage . We noticed that patients with a high PRGS were distributed in all different stages and OS statuses , indicating that our PRGS model is prognosis-specific and capable of assessing the risk of GC patients regardless of stage and status, though clinically, it would be potentially used at later stages for precision. To investigate whether the prognostic value of the PRGS based on the four genes was an independent risk factor, a multivariate Cox regression analysis was performed; the results indicated that the PRGS was notably associated with OS compared with other clinical characteristics (age, sex, clinical stages, and T, N, and M stages), thus validating that the PRGS is robust in independently predicting the GC prognosis . Similarly, the PRGS was still an independent risk factor for OS in the validation datasets (GSE66229 and GSE15459) . We further explored the performance of the PRGS with other characters and found that the performance of the PRGS was better than that of other factors, including gender (whether male or female), age, pathological stages (T1~4, N0~3, M0~M1), and clinical stages (stage I~IV) in TCGA target GTEx, GSE66229, and GSE15459 . The discrimination of the PRGS was measured by an ROC analysis, with 1-, 3-, and 5-year AUCs of 0.601, 0.663, and 0.717 in TCGA target GTEx; 0.607, 0.709, and 0.707 in GSE66229; and 0.657, 0.674, and 0.711 in GSE15459 . The C-index (95% confidence interval) of the PRGS was the highest compared with other factors (gender; age; T, N, and M; clinical stage) in the TCGA target GTEx cohorts . 3.3. PRGS Are Significantly Related to Clinical Outcomes To further validate the performance of our PRGS model, we conducted multiple analyses to evaluate the robustness of these four prognostic genes in the aforementioned independent datasets (GSE66229 and GSE15459). First, through consensus clustering based on the four prognostic genes, we applied a consensus cluster analysis to all GC samples, resulting in the division of the samples into k clusters (k = 2-9). The cumulative distribution function (CDF) curves of the consensus score matrix and proportion of ambiguous clustering (PAC) statistic indicated that the optimal number was obtained when k = 2 . We classified GC patients in GSE66229 and GSE15459 into Cluster 1 and Cluster 2 , respectively. The Kaplan-Meier curve indicated significant OS differences between the two clusters via the log-rank test, and the OS of the patients in Cluster 1 was significantly worse than that of Cluster 2 . As shown in Figure S14A,E, the overall expression levels of the PRGS in Cluster 1 were higher than in Cluster 2 for both datasets. When k = 3 and 4, the Kaplan-Meier curve indicated that patients in Cluster 1 with the lower PRGS expression level had a vastly better OS than that of the other clusters . Thus, for these four genes, the increased expression level was associated with a worse survival rate for gastric cancer patients. The observed consistency suggests that the expression levels of these four genes are vastly correlated with the OS of patients. There are many prognostic gene expression signatures that have been developed based on bioinformatics methods. To compare the performance of the PRGS with other signatures, we selected five cancer stem cell-related feature genes in GCscore risk models (FANCA, DUSP3, HIST1H3B, CLNS1A, and FANCC) , three common clinical GC biomarkers (CEACAM1, CEACAM5, and CEACAM6) , seven immune-related signatures (TGFB1, NOX4, F2R, TLR7, CIITA, RBP5, and KIR3DL3) , two cadherin gene signatures (CDH2 and CDH6) , six metastasis-related gene signatures (TMEM132, PCOLCE, UPK1B, PM20D1, FLJ35024, and SLITRK2) , eight methylation-based gene signatures (TREM2, RAI14, NRP1, YAP1, MATN3, PCSK5, INHBA, and MICAL2) , and three hypoxia-immune-based gene signatures (CXCR6, PPP1R14A, and TAGLN) as features to classify gastric cancer patients with different machine-learning (ML) classifiers. We utilized the logistic regression (LR) classifier and random forest (RF) classifier ML models to predict whether patients had GC in GSE66229 (GSE15459 did not have normal samples). We performed binary classification with them at the same time. The results indicated that the PRGS had a low sensitivity to different classifiers while it had the highest and most robust AUC . Additionally, when performing classification tasks on the patients in different clinical stages (stages I, II, III, and IV), the PRGS had the highest and most robust accuracy . Hence, the PRGS signature had optimized effects in classifying GC samples from control samples, which could serve as a potential feature for examining patients' prognoses. Together, we believe that the expression matrix based on these four genes (APOB, VCAN, ABCA6, and CTSF) as features for screening GC samples could properly assist classifiers in distinguishing cancerous samples from normal samples, acquiring satisfactory precision from test datasets and predicting whether patients have gastric cancer in each stage accurately. 3.4. Experimental Validation of the PRGS in the Clinical Samples and Cell Lines To examine the protein expression levels of the four genes (APOB, VCAN, ABCA6, and CTSF) in gastric cancer, we performed immunohistochemistry (IHC) on the pathological section of the samples from patients of different stages, including normal, paracancerous tissue, early gastric cancer (EGC), and advanced gastric cancer (AGC) . Compared with the samples from the normal tissues, the expression levels of the four proteins (APOB, VCAN, ABCA6, and CTSF) were much higher in EGC . These four genes showed strong expression in almost all of the AGC samples and showed weak expressions in a portion of the paracancerous areas . These results indicated a higher expression level for the four genes (APOB, VCAN, ABCA6, and CTSF) in GC compared to normal and paracancerous lesions. Furthermore, these proteins have already reached high expression levels in EGC samples compared to the matching normal samples. To investigate how these four highly-expressed genes influence tumorigenesis, we further performed anti-phosphorylated histone 3 (pH3) immunostaining and flow cytometry-based cell cycle assays . Consistent with the results in human cancer tissues, all four genes were highly expressed in GES-1 and BGC803 gastric cancer cells . Knocking down any of these four genes independently led to reduced phosphorylated histone 3, a well-established biomarker of cell proliferation . Consistently, the cell cycles of GC cells shifted from the S/G2/M to the G1 state upon the knockdown of APOB, VCAN, ABCA6, and CTSF, as demonstrated in flow cytometric analyses of the cell cycle with propidium iodide staining . Note that the knockdown efficacy of the siRNAs used in our experiments were validated by quantitative real-time PCR . These data unraveled that APOB, VCAN, ABCA6, and CTSF play important roles in the incidence of GC. We detected the gene expression of the PRGS using an RT-PCR assay in a clinical cohort that included 19 normal gastric samples, 18 EGC patients, and 8 AGC patients by conducting qRT-PCR experiments . The result indicated that the expression level in GC patients was significantly higher than in normal samples. These assays supported that our PRGS model was robust. 3.5. The Immune Cell Infiltration between the Low-PRGS Patients Immune-infiltrating cells in the tumor microenvironment (TME) can modulate the tumor phenotype. We assessed tumor purity as well as stromal and immune scores using the ESTIMATE algorithm in TCGA target GTEx samples . ESTIMATE generates three types of scores, namely stromal scores indicating the presence of stroma, immune scores representing the infiltration of immune cells, and an ESTIMATE score, which infers tumor purity. Samples with a low tumor purity show high ESTIMATE scores . The results demonstrated that stromal and immune cells significantly increased along with malignancy progression (from stages I to IV). The ESTIMATE score also increased from stage I to stage IV, whereas tumor purity decreased in higher grades in accordance with previous studies , which illustrated that lower tumor purity correlates with severer malignancy. As expected, a high abundance of stromal cells and immune cells and a low tumor purity were shown in the high-PRGS group . Hence, the high-PRGS group was positively correlated with malignancy. To further chart the underlying immune cells, we implemented the CIBERSORT algorithm to infer the differential abundance between the low-PRGS patients . ]. The high-PRGS group had a very high level of naive B cells (p = 0.00014), monocytes (p = 0.0312), M2 macrophages (p = 1.6 x 10-5), and resting mast cells (p = 5.6 x 10-5) , whereas T follicular helper cells (p = 3.9 x 10-7), Treg (p = 2.1 x 10-6), resting NK cells (p = 0.00716), and activated mast cells (p = 0.03602) exhibited a consistent negative correlation with the low-PRGS group. Then, we determined whether the infiltrating immune cells mentioned above could be associated with patient survival. In agreement with previous studies indicating the promoting roles of M2 macrophage cells in tumor progression and naive B cells when they differentiate into Breg cells in the tumor microenvironment, participating in tumor metastasis , we discovered that the naive B cells and M2 macrophage cells appeared to be associated with poor survival , consistent with the PRGS groups. In addition, the regulatory T cells (Treg), T follicular helper (Tfh) cells, and M0 macrophage cells showed a negative correlation with patient survival , which accords with the low-PRGS group, where there were more Treg and Tfh cells than in the high-PRGS group. Together, our data indicate that the group was characterized by a TME with a high immune cell infiltration and a low tumor purity. 3.6. Mutation Status in GC Patients in the Low-PRGS Groups To investigate PRGS-related mechanisms in GC, we also analyzed somatic mutations. When comparing the mutant frequency between samples of the high-PRGS groups, we detected more mutations in the low-PRGS group than the high-PRGS group, indicating that more mutations led to a lower PRGS and GC risk . Past studies have revealed sophisticated correlations between mutations and tumor prognoses, e.g., TP53 mutations have significant associations with poor outcomes in kidney renal clear cell carcinoma, head and neck squamous cell carcinoma, and acute myeloid leukemia, as well as improved outcomes in ovarian serous cystadenocarcinoma . Besides, IDH1 and MUC16 mutations are associated with an improved prognosis in gastric cancer . All of the top 20 frequent mutations were significantly enriched in cases with patients in both groups . As a reference, we utilized the GCscore as feature genes (FANCA, DUSP3, HIST1H3B, CLNS1A, and FANCC) to classify GC patients from the TCGA dataset into low-risk groups . The top 20 genes with the highest mutation frequencies also had relatively higher mutation frequencies in the low-risk group than in the high-risk group . This result exhibited a similar tendency as our PRGS. We also found that MUC16 (p = 0.051), CSMD1 (p = 0.054), and FAT4 (p = 0.033) mutants had better outcomes than wild type (WT), while TP53 and TTN, genes with the highest mutation frequencies, did not show differences in the outcomes between their mutants and the WT . Frequent mutations in TNN, TP53, and MUC16 were significantly enriched in the low-PRGS groups, which were within expectations according to previous reports . Additionally, APOB portrayed a mutation percentage of 8% and 18% in patients of the low-PRGS groups, respectively. The mutation percentage for VCAN was 6% and 10% in the low-PRGS groups; for ABCA6, it was 2% and 3%; and for CTSF, it was 1% and 3% . Previous work has reported APOB and VCAN as mutation driver genes. Moreover, we observed significant co-occurrences among mutations of these genes. Among the top 20 genes with the highest mutation probabilities in gastric cancer, the majority of these gene mutations were co-occurring. The gene mutations in the low-PGRS group displayed more significant co-occurrences than those in the high-PRGS group . There were also gene pairs that were mutually exclusive. For example, previous studies have reported that ARID1A mutant tumors display p53 pathway activation, and that ARID1A directly regulates TP53 target genes ; our analysis also displayed that in the high-PRGS group, TP53 and ARID1A mutations were significantly mutually exclusive. On the other hand, within the low-PRGS group, KMT2D and FAT4 were also significantly mutually exclusive along with the previous two. These results also indicate a possible pair of mutually exclusive mutations in patients within the low-PRGS group. Somatic mutations were further explored on the basis of oncogenic signaling pathways. We summarized the gene expression levels and mutations of common oncogenic signaling pathways from patients of the high-PRGS group and low-PRGS group. For instance, disturbing the hippo pathway promoted GC proliferation and metastasis , and dysregulation of the MAPK pathway promoted cell metabolism, proliferation, apoptosis, and migration . Our results also indicated that both the hippo and MAPK pathways had high mutation percentages for the samples from the high-PRGS and low-PRGS groups . We discovered that for the most investigated cancer pathways, the patients from the high-PRGS group had higher pathway enrichment scores than the patients in the low-PRGS group . Yet, the percentage of patients with mutations was lower in the high-PRGS group than in the low-PRGS group, which might have arisen from other molecular mechanisms. 4. Discussion To date, there have rarely been effective prognostic genes identified for detecting and predicting gastric cancer prognoses. There is a noticeable difference among GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone. However, researchers might neglect some significant genes when considering mixed data. Hence, we constructed co-expression networks of GC in these three zones separately to select prognostic genes and build the PRGS. Different treatment options mean that patients need better-individualized evaluations when implementing clinical decisions. These can be used as reliable biomarkers for the diagnosis of "high-risk" GC patients. In this study, WGCNA and Cytoscape were applied to identify the gene co-expression networks of GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone. With the expression profiles of these genes in TCGA target GTEx and two independent datasets, the LASSO-Cox regression model was applied to develop a prognostic gene signature. The prognostic analysis demonstrated that this PRGS was a deleterious indicator of the OS. Besides, the PRGS demonstrated a high accuracy and consistent performance for TCGA target GTEx. We also performed cross-validation using two independent GEO datasets (GSE66229 and GSE15459), which indicated great potential for the clinical application of the PRGS. The common tools for evaluating clinical outcomes and making therapeutic schedules include T, N, M, and the clinical stage . Remarkably, our signature worked independently of these factors and had a vastly superior performance in predicting prognoses. Besides, we took the PRGS as features to classify GC and normal samples with machine-learning classifiers. All of the classification accuracy based on the PRGS signature as features were highest with independent datasets (GSE66229) and for several clinical stages (stages I, II, III, and IV). There are a number of prognostic gene signatures based on characteristic genes, such as stem cell-related gene signatures and DNA methylation-related gene signatures . These gene signatures overlook the differences among tumor locations. Although several of these signatures have been developed, few have been implemented in clinical experiments and even fewer have undergone rigorous validation. We compared the PRGS with these signatures to classify GC patients, and the PRGS had a better performance than the other signatures. To further confirm the clinical significance of the PRGS, we conducted a validation assay using qRT-PCR on 45 frozen gastric cancer tissues. The results further supported the validity of the PRGS as a clinical marker. Consequently, our signature has the potential to be a useful clinical tool for the prognosis determination of GC. To further test the clinical explanation of the PRGS, the experimental validation was based on the IHC results from different clinical stages of independent GC patients, validating our prior findings and assessing their feasibility. This indicated that the protein expression level of the PRGS signature was significantly higher in GC patients. This conclusion was further experimentally validated in GES-1 and BGC803 gastric cancer cells, as the knockdown of these four genes led to cell growth inhibition by regulating the cell cycle. Hence, the PRGS signature could serve as a promising surrogate for assessing the prognosis of GC in clinical settings. Pathologists generally determine tumor purity by visual evaluation, which is affected by the sensitivity of histopathology, interobserver bias, and variability in accuracy . Our results show that the high-PRGS-group patients had a lower tumor purity and higher levels of immune and stromal cell infiltration compared with patients in the low-PRGS group. Previous studies have reported that tumor cells can dominate the microenvironment , which has given rise to the hypothesis that malignant GC recruits abundant surrounding cells and subjugates them to compose a protective shield. Therefore, a lower tumor purity and correlated cellular heterogeneity may contribute to a worse prognosis for GC. In our study, we found that the PRGS was positively correlated with several infiltration cells, such as M2 macrophages and naive B cells, which are positively correlated with the prognosis of GC patients; furthermore, the PRGS was negatively correlated with follicular helper T cells, M0 macrophages, and regulatory T cells, which are negatively correlated with the prognosis of GC patients. We found that GC patients in the low-PRGS group had a higher rate of oncogenic mutations. It should be noted that the association of gene mutations with cancer outcomes is sophisticated. Take MUC16 and IDH1 as examples: past GC studies have illustrated that MUC16 mutations could activate the p53 pathway and DNA repair pathway, which are all tumor suppressor pathways ; thus, improved outcomes of GC might be expected from mutated MUC16 . Mutations in IDH1, as a tumor suppressor in human glioma cells through the negative regulation of Wnt/b-catenin signaling, improves survival conditions . In addition, mutations in the top 20 genes had a high frequency of co-mutations. However, further investigations are needed for a deep understanding of the mechanisms of mutations in GC. 5. Conclusions In a word, based on a series of bioinformatics, machine-learning-based algorithms, and experimental validation, we developed a powerful and robust signature for assessing the prognosis of GC patients. This PRGS model may be a promising tool for screening and monitoring individual GC patients. Acknowledgments We thank Jianming Zeng (University of Macau), all the members of his bioinformatics team, and Biotrainee for generously sharing their experience and codes, as well as the use of the biostudio's high-performance computing cluster accessed on 1 January 2022) at Biotrainee and The Shanghai HS Biotech Co., Ltd. for conducting the research reported in this paper. We thank Jun Qin and Xianju Li, Beijing Proteome Research Center, for giving us the gastric cancer cell line GSE-1. We thank Zijie Shen from the College of Agriculture and Biotechnology, Zhejiang University; Haotian Wang from Kunming Institute of Zoology, CAS; and Wenbo Guo, Department of Automation, Tsinghua University for data processing. Supplementary Materials The following supporting information can be downloaded at: Figure S1. (A) Bubble plot of GO enrichment for GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone. Green represents biological processes; red represents cellular components; blue represents molecular functions. (B) Identify differentially expressed genes (DEGs) and KEGG enrichment of DEGs for GC in the cardiac zone, the fundus/corpus zone, and the pyloric zone. The color of the bubble represents the significance of p.adjust. (C) Analysis of network topology for different soft-threshold power. The left panel shows the impact of soft threshold power on the scale-free topology fit index; the right panel displays the impact of soft-threshold power on the mean connectivity. Figure S2. GO and KEGG enrichment of genes in the purple, brown and salmon modules. (A-C) GO enrichment of the purple module (correlated with the cardiac zone) (A), salmon module (correlated with fundus/corpus zone) (B) and brown module (correlated with the pyloric zone) (C). (D-F) KEGG enrichment of the purple module (correlated with the cardiac zone) (D), salmon module (correlated with the cardiac zone) (E) and brown module (correlated with the pyloric zone) (F). Figure S3. Survival analysis and binary classification of the genes from the co-expression networks (A) Kaplan-Meier curves of OS according to the top5 genes (APOA4, MS4A10, SLC28A1, AQP10, APOB) from the cardiac zone co-expression network separate of GC in the cardiac zone (left, p = 0.074), the fundus/corpus zone (middle, p = 0.22), and the pyloric zone(right, p = 0.73) in TCGA target GTEx. (B) Kaplan-Meier curves of OS according to the top5 genes (APOA4, MS4A10, SLC28A1, AQP10, APOB) from the cardiac zone co-expression network separate of GC in the cardiac zone (left, p = 0.059), the fundus/corpus zone (middle, p = 0.15), and the pyloric zone(right, p = 0.33) in GSE66229. (C) Kaplan-Meier curves of OS according to the top5 genes (VCAN, COL1A2, FAP, PODNL1, SULF1) from the fundus/corpus co-expression network separate of GC in the cardiac zone (left, p = 0.16), the fundus/corpus zone (middle, p = 5.32 x 10-6), and the pyloric zone(right, p = 0.73) in TCGA target GTEx. (D) Kaplan-Meier curves of OS according to the top5 genes (VCAN, COL1A2, FAP, PODNL1, SULF1) from the fundus/corpus co-expression network separate of GC in the cardiac zone (left, p = 0.83), the fundus/corpus zone (middle, p = 0.0047), and the pyloric zone(right, p = 0.045) in GSE66229. (E,F) BoxPlot of AUC of two classifiers (LR, Logistic Regression; RF, Random Forest) with the top5 genes (APOA4, MS4A10, SLC28A1, AQP10, APOB) and the top5 genes (VCAN, COL1A2, FAP, PODNL1, SULF1) from the cardiac zone co-expression network (E) and the fundus/corpus co-expression network (F) separately as features in TCGA target GTEx and GSE66229. The cardiac zone means GC in the cardiac zone; the Fundus/Corpus zone means GC in the fundus/corpus zone; the Pyloric zone means GC in the pyloric zone. Figure S4. (A) In the TCGA target GTEx cohort (383 GC samples with clinical information), the optimal l was determined when the partial likelihood deviance reached the minimum value and further generated Lasso coefficients of the most useful prognostic genes. Data are presented as mean +- 95% confidence interval [CI]. (B) Cell-type markers. The expression levels of cell-type markers across cell types are shown. Cell-type marker genes were identified in Wilcoxon rank-sum test (FDR < 0.01, and fold change > 1.5) and only the top genes are shown in the figure. (C) The UMAP plot of 200,954 cells to visualize cell-type clusters. (D) The UMAP plot of both samples. (E) The UMAP plot of both cells from normal and tumor tissues (blue means tumor tissues; red means normal tissues). Figure S5. (A) The UMAP plot of cell types marked by specific marker genes. The epithelial cell is marked by CDH1, and including pit mucous cell (Pit, MUC5AC and TFF1 positive), chief cell (Chief, LIPF and PGA3 positive), and intestinal cell (Intestinal, REG4 and TFF3 positive). Fibroblast is FN1, LUM, DCN positive; Pericytes is RGS5 and NOTCH3 positive; Endothelial cell is PLVAP and ACKR positive; T cell is CD8A positive; T regulatory cell (Treg) is IL2RA positive; NK cell is KLRD1 positive; B cell is MS4A1 positive; Plasma is TNFRSF 17 positive; mast cell is KIT positive; Macrophage is CD163 positive; Dendritic cell is PLD4 positive. (B) The UMAP plot of PRGS expression level. Figure S6. (A-C) The UMAP plot of all samples (A), normal samples (B), tumor samples (C) according to PRGS score. (D) BoxPlot of PRGS in different cell types. Normal, normal samples; tumor, tumor samples; Diffuse, diffuse-type gastric cancer; Intestinal, intestinal-type gastric cancer; Mixed, mixed-type gastric cancer. Figure S7. (A) Genome characterization and enrichment analysis. (A) Distribution map of transcription factors and TSS. (B) location distribution of Peaks on the genome. (C) relative proportions of gene coding regions, intergenic regions, introns, exons, and upstream and downstream regions. (D) Browser showing chromatin accessibility status of PRGS signature (APOB, VCAN, ABCA6, CTSF). The grey bars highlighted peaks of PRGS signature in promoter regions. All of the genes showed duplication of two samples. Figure S8. (A) Motif enrichment analysis of common genes around open chromatin regions. Fra1 and Foxa2 were found to be significantly enriched with APOB; KLF6 and Erra were found to be significantly enriched with VCAN; Fos and GABPA were found to be significantly enriched with ABCA6; BATF and Sp5 were found to be significantly enriched with CTSF (B-D) GO enrichment of the GC with ATAC-seq data. (E) KEGG enrichment of the GC with ATAC-seq data. Figure S9. (A) Establishment of PRGS model dividing patients into in the TCGA target GTEx (left), GSE66229 (middle) and GSE15459 (right). The cutoff value on the top (red: high expression; blue: low expression); survival statues on the bottom. (B-D) Kaplan-Meier curves of overall survival (OS) according to the PRGS of the different Lauren/WHO histotypes patients in TCGA target GTEx (B), GSE15459 (C), and GSE66229 (D). Intestinal means Intestinal-type gastric cancer patients; Diffuse means diffuse-type gastric cancer patients; Adenocarcinoma means gastric adenocarcinoma patients, and accurate histotypes is unknown; Tubular adenocarcinoma means tubular adenocarcinoma patients. Figure S10. (A) Survival analysis of the different TNM stages patients. (A-F) Kaplan-Meier curves of overall survival (OS) according to the PRGS of the different TNM stages patients in TCGA target GTEx (A-C), and GSE66229 (D-F). Figure S11. The integrated sankey diagram portrays the underlying correlations across the PRGS group, stage and OS status in the TCGA target GTEx cohort (345 samples with information on the clinical stage). Figure S12. Multivariate Cox analysis evaluating independently predictive ability of PRGS model and other clinical characteristics for OS. (A) Multivariate Cox regression of PRGS regarding OS in TCGA target GTEx (345 samples with information on the clinical stage). (B) Multivariate Cox regression of PRGS regarding OS in GSE66229 (n = 298). (C) Multivariate Cox regression of PRGS regarding OS in GSE15459 (n = 191). Statistic tests: two-sided Wald test. Data are presented as hazard ratio (HR) +- 95% confidence interval [CI]. * p < 0.05. ** p < 0.01. *** p < 0.001. Figure S13. The performance of PRGS was compared with other clinical and molecular variables in predicting prognosis. Statistic tests: two-sided z-score test. Figure S14. (A) Heatmap showed that the expression level of cluster1 is higher than cluster2 in GSE66229. (B) The consensus score matrix of all samples in GSE66229 when k = 3 or 4. (C) Kaplan-Meier analysis showed that patients in Cluster 1 exhibited better OS in the GSE66229 cohort when k = 3 (left, p = 0.048) or k = 4 (right, p = 0.0071). (D) Heatmap showed that the expression level of cluster1 is lower than others in GSE66229 when k = 3 (left) or k = 4 (right). (E) Heatmap showed that the expression level of cluster1 is higher than cluster2 in GSE15459. (F) The consensus score matrix of all samples in GSE15459 when k = 3 or 4. (G) Kaplan-Meier analysis showed that patients in Cluster 1 exhibited better OS in the GSE15459 cohort when k = 3 (left, p = 0.00064) or k = 4 (right, p = 0.00064). (H) Heatmap showed that the expression level of cluster1 is lower than others in GSE15459 when k = 3 (left) or k = 4 (right). C1 means cluster1, C2 means cluster2, C3 means cluster3, C4 means cluster4. Figure S15. Evaluation of the PRGS signature with machine learning classifiers in GSE66229. (A,B) ROC curve of binary classification with logistic regression classifier (A) and random forest classifier (B) for all and different stage(stage I-IV) GC patients with PRGS signature as features. "Tumor" means GC patients; "Normal" means gastric tissues with a non-tumor state. Figure S16. (A) BoxPlot of AUC in two classifiers (LR, Logistic Regression; RF, Random Forest), respectively. (B-D) HE staining of advanced gastric cancer (AGC) (B), normal tissue (C) and early gastric cancer (D). Figure S17. Tumor mutation status of GCscore (FANCA, DUSP3, HIST1H3B, CLNS1A, FANCC) and Kaplan-Meier curves of high frequency mutant genes. (A) Kaplan-Meier curves of OS according to the GCscore in TCGA. (B) OncoPlot of significantly mutated genes in high- (left) and low- (right) GCscore groups. The mutation types with their frequencies were presented. (C-G) Kaplan-Meier curves of OS between the oncogenic mutation and wild type (WT) of MUC16 (C), CSMD1 (D), FAT4 (E), TP53 (F) and TTN (G). Figure S18. Tumor mutation status of groups. (A) The mutation percentages of PRGS signature (APOB, VCAN, ABCA6, CTSF) in high-(left) and low-(right) PRGS groups. (B) Interaction effect of genes mutating differentially in patients in the high-(left) and the low-(right) PRGS groups. (C) The mutation percentages of nine common oncogenes signaling pathways in high-(left) and low-(right) PRGS groups. (D) BoxPlot of nine common oncogenes signaling pathways expression profile in the high-(red) and low-(blue) PRGS groups. Table S1. Details of baseline information in TCGA target GTEx. Table S2. Details of baseline information in GSE15459. Table S3. Details of baseline information in GSE66229. Table S4. Datasets in use. Table S5. The remaining genes of each step. Table S6. Top25 genes selected by Cytoscape. Table S7. LASSO coefficients. Table S8. TCGA-STAD database with PRGS groups. Table S9. The evaluation metrics of PRGS in training and testing cohorts. Table S10. GSE66229 database with consensus clustering. Table S11. GSE15459 database with consensus clustering. Table S12. The stromal, immune cell infiltration and purity in TCGA target GTEx samples by ESTIMATE. Table S13. The immune cell infiltration in all TCGA target GTEx samples by CIBERSORT. Click here for additional data file. Author Contributions Conception and design: M.Q.Z., C.L. and X.L.; experimental operation: Y.Z.; collection and assembly of data: C.L., X.L. and Y.H.; provision of materials and patient information: P.J. and F.Y.; manuscript writing and revision: M.Q.Z., C.L., X.L., M.S., Y.H., Y.Z., P.J., F.Y., T.C., Z.W. and J.G. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement In this study, the gastric tissues used were approved by the Department of Gastroenterology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, China, on 1 June 2022. Overall, one advanced GC sample, an early GC sample, and a normal gastric sample were collected. All patients provided written informed consent, and the ethics committee of PLA General Hospital also approved our research. Data Availability Statement The datasets that support the findings of this study are available from the Cancer Genome Atlas TARGET and Genotype Tissue Expression project datasets (TCGA target GTEx, primary_site = stomach) and the NCBI Gene Expression Omnibus (GEO) under accession numbers GSE66229 and GSE15459. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The overall design of this study. Figure 2 Identified co-expression networks of the cardiac zone, the fundus/corpus zone, and the pyloric zone. (A) Volcano plots of DEGs in the cardiac zone, the fundus/corpus zone, and the pyloric zone. Red and blue spots represent significant down-regulated RNAs, respectively. The remark for the gene symbols represents the significant down-regulated RNAs. (B) Venn diagram of the DEGs in the cardiac zone, the fundus/corpus zone, and the pyloric zone. Different colors indicate GC in different zones. The numbers represent the common DEGs among GC in different zones. (C) Correlation analysis between module eigengenes and the three zones. (D) Co-expression networks of the cardiac zone, the fundus/corpus zone, and the pyloric zone. Figure 3 Cox and survival analysis of the PRGS model. (A) Kaplan-Meier curves of overall survival (OS) according to the PRGS in TCGA target GTEx. (B) Kaplan-Meier curves of OS according to the PRGS in TCGA target GTEx (log-rank test: p = 7.75 x 10-5); GSE66229 (log-rank test: p = 2.11 x 10-11); and GSE15459 (log-rank test: p = 0.00034). (C) Multivariate Cox regression of PRGS regarding OS in TCGA target GTEx (n = 345). (D) Multivariate Cox regression of PRGS regarding OS in GSE66229 (n = 298) and GSE15459 (n = 191). Statistic tests: two-sided Wald test. Data are presented as hazard ratio (HR) +- 95% confidence interval (CI). * p < 0.05. ** p < 0.01. *** p < 0.001. Figure 4 Evaluation of the PRGS signature. (A) A time-dependent ROC analysis for predicting OS at 1, 3, and 5 years in TCGA target GTEx, GSE66229, and GSE15459. (B) The consensus score matrix of all samples in GSE66229 and GSE15459 when k = 2. A higher consensus score between two clusters indicates they are more likely to be grouped into the same cluster in different iterations. (C) The CDF curves of the consensus matrix for each k. (D) Kaplan-Meier analysis showed that patients in Cluster 1 exhibited a worse OS in both the GSE66229 (p = 0.04) and GSE15459 (p = 0.00031) cohorts. (E) Box plot of AUC of two classifiers (LR, logistic regression; RF, random forest) with eight gene signatures as features in GSE66229. (F) Box plot of AUC of CEA, GCscore, and PRGS in clinical stages I to IV. CEA is three common clinical GC biomarkers, including CEACAM1, CEACAM5, and CEACAM6; GCscore includes FANCA, DUSP3, HIST1H3B, CLNS1A, and FANCC; PRGS includes APOB, VCAN, ABCA6, and CTSF; IRSHG includes seven immune-related signatures (TGFB1, NOX4, F2R, TLR7, CIITA, RBP5, and KIR3DL3) ; CGF includes two cadherin gene signatures, CDH2 and CDH6 ; DMGs include six metastasis-related gene signatures (TMEM132, PCOLCE, UPK1B, PM20D1, FLJ35024, and SLITRK2) ; MDEGs include eight methylation-based gene signatures (TREM2, RAI14, NRP1, YAP1, MATN3, PCSK5, INHBA, and MICAL2) ; and hypoxia-immune-based gene signature includes CXCR6, PPP1R14A, and TAGLN . Figure 5 The results of immunohistochemistry (IHC). (A-D) IHC staining of APOB (A), VCAN (B), ABCA6 (C), and CTSF (D) in an early gastric cancer sample (EGC, left) and a normal sample (right). (E-H) IHC staining of APOB (E), VCAN (F), ABCA6 (G), and CTSF (H) in advanced gastric cancer (AGC). The pathological section of AGC shows the overall site (left), tumor region (AGC, upper right), and paracancerous tissue region (lower left). Figure 6 Knockdown of PRGS inhibited proliferation of gastric cancer cells. (A-D) Knockdown of any one of APOB, VCAN, ABCA6, or CTSF by siRNA inhibited cell proliferation of GES-1 and BGC803 gastric cancer cells. Shown are the anti-phosphorylated histone 3 (pH3) immunostaining (A,B) and flow cytometry-based cell cycle assays (C,D) of the APOB, VCAN, ABCA6, or CTSF siRNA treatment. For (A), scale bar is 10 mm. For (B-F), n = 3. One-way ANOVA and Tukey's multiple comparison tests were used. In all figures, standard errors of the mean were represented. NS is not significant. * p < 0.05. ** p < 0.01. *** p < 0.001, **** p < 0.0001. (G) Box plot of PRGS expression level in normal, early gastric cancer, and advanced gastric cancer patients. (H) Box plot of PRGS expression level in normal and gastric cancer patients. N means normal gastric tissues; EGC means early gastric cancer tissues; AGC means advanced gastric cancer tissues; and GC means gastric cancer tissues. Figure 7 The landscape of immune infiltrations and tumor mutation status in the high-PRGS groups. (A) Distinct distribution of stromal score (upper left), immune score (upper right), ESTIMATE score (lower left), and tumor purity (lower right) among GC patients in TCGA target GTEx. (B) The immune-infiltrating cells in the TME were determined based on the CIBERSORT algorithm in the TCGA target GTEx. (C-F) Kaplan-Meier curves of OS according to the M2 macrophages (C), naive B cells (D), follicular helper T cells (E), and regulatory T cells (F) in TCGA target GTEx. (G) OncoPlot of significantly mutated genes in high- (left) and low- (right) PRGS groups. The mutation types with their frequencies are presented. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000505 | Deep microwave hyperthermia applicators are typically designed as narrow-band conformal antenna arrays with equally spaced elements, arranged in one or more rings. This solution, while adequate for most body regions, might be sub-optimal for brain treatments. The introduction of ultra-wide-band semi-spherical applicators, with elements arranged around the head and not necessarily aligned, has the potential to enhance the selective thermal dose delivery in this challenging anatomical region. However, the additional degrees of freedom in this design make the problem non-trivial. We address this by treating the antenna arrangement as a global SAR-based optimization process aiming at maximizing target coverage and hot-spot suppression in a given patient. To enable the quick evaluation of a certain arrangement, we propose a novel E-field interpolation technique which calculates the field generated by an antenna at any location around the scalp from a limited number of initial simulations. We evaluate the approximation error against full array simulations. We demonstrate the design technique in the optimization of a helmet applicator for the treatment of a medulloblastoma in a paediatric patient. The optimized applicator achieves 0.3 degC higher T90 than a conventional ring applicator with the same number of elements. deep hyperthermia cancer treatment brain tumor ultra-wide-band microwave applicator medulloblastoma thermal therapy Swedish Research Council2021-04935 This research was funded by the Swedish Research Council grant number 2021-04935. pmc1. Introduction Local hyperthermia for cancer treatment consists of the selective increase in the tumor temperature to 40-44 degC for about an hour . In combination with chemo-therapy, this modality has been shown to enhance the therapeutic outcome for several tumor types in clinical trials . Conformal phased arrays are used in microwave (MW) hyperthermia (HT) to non-invasively deliver the prescribed thermal dose to deep-seated tumors . In this process, it is of paramount importance to subject the target volume to a high and uniform temperature increase while keeping the surrounding healthy tissues within physiologically tolerated temperatures . External MW-HT has been successfully applied to targets in the pelvis and the head and neck with remarkable results. To date, however, no clinical applications in the treatment of brain tumors have been reported, despite early encouraging results obtained with interstitial techniques . The implementation of MW-HT for the treatment of solid brain tumors could be particularly beneficial in paediatric patients, where the incidence of such malignancies is the highest . Current treatment modalities based on chemoradiotherapy are known to cause long-term disorders in survivors . There is, thus, a strong motivation for the development of brain applicators and the introduction of hyperthermia as a means of lowering the ionizing dose while maintaining the same clinical output. Local heating of tissues in the head is a challenging task due to the presence of critical organs and their extra sensitivity to hyperthermic temperatures . Ideally, the therapeutic range of 40-44 degC should be reached everywhere in the tumor, while healthy tissues should not exceed 42degC. Particular care should be devoted to avoiding MW radiation in the eyes . Unfortunately, radio-frequency (RF) waves in the MW range are known to be easily absorbed by biological tissues , resulting in poor penetration depth. This is especially true for the cerebrospinal fluid (CSF), due to its high conductivity at these frequencies . The enclosure of the skull (cortical bone) adds to the complication as its dielectric contrast causes irregular wave scattering and multiple reflections. For these reasons, additional efforts must be spent in ensuring that the applicator can reliably target the tumor while minimizing losses in healthy tissue. The latter may result in the formation of hot-spots, which are known to be the limiting factor for the maximum achieved tumor temperature during a treatment session . In a typical MW-HT applicator design, the array is a conformal ring of equally spaced antennas immersed in a water bolus, which fills the gap between the antennas and the patient's skin. The bolus realizes a dielectric match for an increased power transfer to the body and simultaneously cools off the first layer of tissue where the electromagnetic losses are the strongest . Several groups in the past decades have investigated the relationship between the array design parameters and the resulting ability of the applicator to selectively heat tumors in the pelvis and the neck. These include: operating frequency, array topology (usually ring), distance between antennas, and number of antennas and their distance from the body . For brain tumors, external MW-HT has not yet been clinically tested, and the few available non-invasive heating solutions rely on magnetic nano-particles or focused ultra-sound . More recently, however, researchers have begun investigating the feasibility of MW-HT in this anatomical region . Preliminary results suggest that high-quality heating can be better achieved when the array configuration is customized to the specific tumor location, shape and size . By means of radio-biological modeling, the addition of hyperthermia to the treatment of medulloblastoma has been shown to yield a considerable theoretical boost in the biologically equivalent dose (BED) when combined with stereotactic radiosurgery . In this work, we attempt to go beyond the classical single-frequency ring array configuration and exploit the spherical morphology of the head to develop an ultra-wide-band helmet applicator (250-500 MHz). In doing so, we relax the constraints of fixed distance between the antennas and their mutual alignment. We treat the antenna arrangement around the surface of the scalp as a global optimization problem where each element's location is left as a degree of freedom. At each iteration of the optimization algorithm, we determine the E-field due to each antenna in the array as the interpolation of a grid of simulated individual antennas at fixed locations. As cost-function for the assessment of a particular array configuration, we utilize a novel metric, the hot-to-cold spot quotient (HCQ), which is based on the specific absorption rate (SAR) distribution and has been shown to correlate well with the resulting temperature increase in deep-seated targets . We demonstrate the procedure in the design of several helmet applicators of increasing numbers of elements for the treatment of a paediatric patient with medulloblastoma. We assess the quality of the interpolated field by analyzing the approximation error when compared to an actual simulation. Finally, we quantitatively compare the optimized, semi-spherical arrays to classical elliptical designs of the same number of elements, by developing full thermal treatment plans for each solution. 2. Method 2.1. Patient Model We consider a 13-years old male patient with a 126 mL medulloblastoma in the dorsal area of the brain, shown in Figure 1. The tumor is relatively large and extends from the medulla to the skull. The challenge in this patient is due to the hyperthermia target volume (HTV) presenting both peripheral and deep regions, with the distance from the skin surface ranging from 1 cm to almost 9 cm. The model was obtained via MRI scans with 1mm resolution. The raw data was manually segmented by a trained oncologist into 10 distinct tissues: skin, muscle, bone (cortical), pharynx, cerebrospinal fluid, brain (gray matter), brain (white matter), eye (vitreous humor), cartilage, and tumor. The caudal part of the model, below the brain stem, is filled with muscle to emulate the presence of the rest of the body and allow the simulated wave to propagate with the expected negligible reflection, while reducing the segmentation complexity. 2.2. Antenna and Bolus Design The array elements utilized in our applicator design are self-grounded bow-tie (SGBT) antennas , Figure 2. The geometrical parameters of the antennas are optimized to obtain a stable impedance, radiation pattern, and return loss above 10dB across the whole 250-500 MHz band when positioned at a distance of 5 cm from the head (measured at the antenna ground plate). This distance is chosen as a compromise between reducing the sensitivity of the antenna response to variations in the patient anatomy (lower at longer distances), and decreasing the losses in the water bolus (lower at shorter distances). The water bolus shape is, thus, obtained by fitting an ellipsoid over a cloud of points randomly located around the scalp and offset by 5 cm, as shown in Figure 3. The resulting ellipsoid has a different radius in each direction: 12.5cm along the x axis, 14.2cm along y, and 14.4cm along z. The ellipsoid is trimmed just above the nostrils to provide an opening for breathing, with the cutting plane perpendicular to the z axis and being located 7.7cm caudal to the ellipsoid center. Each antenna was placed with its background plate lying as far as possible from the patient while preventing the metal from protruding out of the water. 2.3. Numerical Simulations Electromagnetic (EM) simulations were performed in COMSOL Multiphysics(r) 5.6 . To reduce the computational burden for the simulation of the interpolation grid (Section 2.5), the patient model was down-sampled to 4mm using a winner-takes-all strategy . This corresponds to approximately l/18 in the tissue with highest permittivity (CSF), where l is the wavelength at the highest considered frequency (500MHz). A regular hexahedral mesh was assembled in the patient respecting this step, while the water bolus and the surrounding air background were discretized with a tetrahedral mesh whose resolution varies from l/30 at the antenna feed and metal corners to l/5 in the bulk. A convergence test based on the single antenna response (S11) in water was performed to confirm the adequacy of the mesh. The antennas were modelled as sheets of perfect electric conductor (PEC) and excited via a TEM port whose real characteristic impedance was set to the value that minimizes the individual antenna reflection across the bandwidth (26O for the SGBT model used in this study). Absorbing conditions (perfectly matched layer, PML) were defined at the domain boundaries. Dispersive healthy tissue properties were retrieved from the IT'IS database . Dispersive tumor properties were obtained as an average of all malignant-tissue properties reported in , as recommended by . Thermal (TH) simulations were also performed in COMSOL. The steady-state temperature distribution was determined for each final applicator design. The patient model was added and meshed in the same fashion as for the EM simulation. We added heat-flux boundary conditions to model the convective extraction of heat at the interface between patient and air or water. The chosen convection coefficient between skin and air was 8 W/m2/K , while the coefficient between skin and water was 100 W/m2/K . The air temperature was set to 20degC. Due to the proximity of the tumor to the surface, the water bolus directly affects the temperatures in the target volume . Therefore, the water temperature was set to a higher 30degC. Thermal properties were once more obtained from the IT'IS database for each healthy tissue, while the following properties were used for the tumor : density r = 1090 kg/m3, specific heat capacity cp = 3421 J/kg/K, and thermal conductivity k = 0.49 W/m/K. In the TH simulation, the EM losses were added as a distributed heat source term in the bio-heat equation . This term was obtained from the array's E-field distribution at each frequency (Ef) as shaped by the treatment-planning optimization stage (Section 2.4) and obtained by a full array simulation (no interpolation involved):(1) PLD=kf12sf|Ef|2 where PLD stands for power loss density (W/m3) and k is a scaling factor. Note that, unlike the SAR distribution in Section 2.4, the PLD distribution is not smoothed out nor masked. The value of k was determined by a local gradient descent optimization whose goal is to obtain a maximum temperature in the healthy tissue equal to 42degC, to respect the toxicity limits in the central nervous system . The resulting temperature distribution in the target volume was assessed by means of the T50 and T90 indexes , i.e., the minimum temperature achieved within the highest 50% and 90% of the temperature distribution in the target, respectively. 2.4. Treatment Planning For each applicator configuration, either during the optimization stage or for final validation, a full multi-frequency SAR-based treatment plan optimization was carried out. The plans were prepared considering the MHz set of frequencies for simultaneous operation. The optimization variables were the phase and amplitude of each array channel and for each frequency, for a total of 2*nf*nc degrees of freedom, where nf is the number of frequencies and nc is the number of channels (antennas). The cost function and goal to be minimized is the hot-to-cold spot quotient (HCQ), defined as follows :(2) HCQp=SAR RqSAR Tp. where SAR Tp is the average SAR in the lowest p percentile of target (tumor) tissue, while SAR Rq is the average SAR in the highest q percentile of remaining (healthy) tissue. The relationship between percentiles is fixed: (3) q=p+T++R+ where ++ denotes the volume of the argument. A target percentile p of 50% was selected to promote coverage even in the deepest parts of the tumor and increase the resulting temperature indexes. For the present patient model, the corresponding percentile of remaining healthy tissue becomes q=2.8%. The procedure was implemented in MATLAB(r) R2021a using our previously devised scheme for the fast minimization of HCQ in multi-frequency problems , which is based on an iterative form of time reversal. When a full array simulation is performed on COMSOL, the E-field distributions due to each antenna are directly exported from the software and re-sampled to a uniform matrix with 4mm spatial resolution and single precision. During the array optimization, on the other hand, the individual E-fields were determined by linear interpolation, as described in Section 2.5. The SAR distribution, in W/kg, upon which Equation (2) has to be evaluated was determined by superposition of the frequency contributions:(4) SAR=f12sfr|ckhf,cEf,c|2 where s is the local material conductivity and r its density, while khf,c and Ef,c are the complex steering parameter and E-field distribution of channel c at frequency f, respectively. The SAR was further processed to increase its correlation with temperature. First, the distribution was smoothed out by a 5 g mass averaging scheme within the patient, where surface voxels were treated by expanding the convolution kernel until the mass of tissue within reached 5 g . Secondly, the voxels belonging to the first 20mm of healthy tissue at the surface in contact with the water bolus were completely excluded from the patient mask for the evaluation of the cost-function. This step was included to model the cooling effect of the water bolus in SAR, as the EM losses are effectively counteracted by the convective heat extraction . Additionally, the exclusion of such a thick layer of patient surface was motivated by the knowledge that the most prominent hot-spot was expected to arise in the deep-seated pocket of CSF caudal to the target volume , while the peripheral strati of CSF were kept within safe temperatures by the joint action of the water bolus and the naturally high perfusion rate of gray matter . Altogether, these measures ensured a high degree of correlation between the SAR and the resulting temperature distribution. All parallel SAR calculations were performed in single precision on a GPU (nVidia(r) RTXTM A6000). 2.5. Field Interpolation To determine the E-field distribution due to a single antenna at any location across the surface of the helmet, we introduced a linear interpolation scheme which relies on a limited number of pre-simulated locations around the head (grid). The procedure consisted of several steps and made use of a local 2D spherical coordinate system (th,ph) mapping the surface of the water bolus, illustrated in Figure 4. 2.5.1. Interpolation Grid Given the fitted bolus ellipsoid obtained in Section 2.2, a number of points np were randomly placed around its available surface. The superficial coordinates of each point (th and ph in terms of a local spherical coordinate system aligned with the ellipsoid) were then fed to a local least-squares minimization algorithm (lsqnonlin) which aims at minimizing the sum of the inverse of the squared distances between each pair of points (emulating the repulsion of charged particles of the same sign). Constraints to this optimization stage were the bolus limits, i.e., thMAX in case of a truncated ellipsoidal helmet. The procedure was repeated for increasing np until the maximum distance between any pair of nearby points fell below a certain target sampling distance. In the patient model at hand, we prepared a grid of np=221 points resulting in a maximum distance of 2.9cm, which is slightly below a half of the minimum wavelength in water (6.8cm @ 500MHz) to provide adequate sampling resolution. The full grid is shown in Figure 5. For each grid point, a local antenna coordinate system was generated. The origin O=(x,y,z) was initially placed at the surface point corresponding to the spherical coordinates (th, ph) of this grid point. Indicating with U the antenna's orientation (polarization axis), with W its main directivity axis (pointing direction), and with V a third axis which completes a right-handed (U,V,W) triple, the local coordinate system was obtained by making W inwards perpendicular to the ellipsoid's surface at the point location and finding U as the vector tangent to the bolus surface and lying on the ZW plane, where Z is the patient's cranial-caudal axis. Finally, the origin O was translated towards the positive W direction by the distance necessary to prevent the antenna's back plate from projecting out of the water ellipsoid. In COMSOL, np*nf full EM simulations were performed, each with a single antenna model rigidly transformed to match the coordinate system previously prepared. The E-field distributions relative to the individual frequencies were then exported to MATLAB and uniformly re-sampled. 2.5.2. Linear Interpolation Once the grid distributions were available, the E-field due to a single antenna a at arbitrary coordinates (tha,pha)(xa,ya,za)=Oa could be obtained using a linear interpolation of the distributions relative to the 3 closest grid points O1,O2,O3 (triangular patch), as illustrated in Figure 6:1. A local coordinate system (U,V,W)a was built for the antenna, in a similar way to for the grid points in Section 2.5.1. 2. The complex vector E-field distribution E1 of the first grid point at frequency f was divided everywhere by the local impedance ef of the material, yielding a surrogate H1 of the H-field of an antenna at that location. This important step was included to render the field distribution less dependent on the patient's anatomy, thanks to the biological tissues being predominantly non-magnetic. 3. This complex vector H-field distribution was transformed to H^1 according to a translation T', a rotation R, and a second translation T'', such that: (5) T'[O1]=(0,0,0)R[(U,V,W)1]=(U,V,W)aT''[(0,0,0)]=Oa 4. The transformed H-field distribution H^1 was multiplied by the material impedance ef to restore the transformed E-field intensity E^1. 5. Steps 2 to 4 were repeated for each of the 3 closest grid points. 6. The E-field distribution relative to the individual antenna was obtained as a weighed average of the transformed distributions. The weights o1,o2,o3 were determined as the ratio between the area of the subtended triangle to the area of the interpolation patch: (6) Ea=o1E^1+o2E^2+o3E^3o1=+(Oa,O2,O3)+/+(O1,O2,O3)+o2=+(O1,Oa,O3)+/+(O1,O2,O3)+o3=+(O1,O2,Oa)+/+(O1,O2,O3)+ where ++ denotes the area of the argument. 2.5.3. Coupling Modeling The above procedure provides a rough approximation of the E-field of a single antenna in a particular position across the water bolus surface. In any array configuration with two or more antennas, however, coupling phenomena affect the E-field distribution of the single element. We tackled this by utilizing the very individual fields of each antenna to model the coupling distortion of each array element. To this end, we prepared a separate simulation where a spherical brain phantom is enclosed in a spherical water bolus of the same thickness of our applicator design (5 cm), Figure 7a. The phantom includes the same tissues found in the upper hemisphere of the head: brain, cerebrospinal fluid, cortical bone, skin. These were modelled as concentric shells whose thickness was determined by averaging a number of radial samples taken from the patient model, Figure 1. The result was 6.3mm for the skin, 6.8mm for the bone, and 10.7mm for the cerebrospinal fluid. The outer radius of the phantom was 96.9mm, determined in a similar way (average head radius). The inner core is filled with brain material. Using this model, we determined the coupling factor between two antennas located anywhere inside the bolus. We added a fixed active antenna (A) and generated a number of random locations for a passive antenna (P), including random rotations of its polarization axis, Figure 7b. For each arrangement of this pair, we simulated the individual E-field distributions EA and EP generated when the other antenna is absent, and we extracted the value of EA at the phase center of the passive antenna, EA(OP'). For our SGBT antennas, the phase center O'=O+W*1.4cm lies in between the flaps, at the end of the feed line, Figure 7c. We projected this value onto the polarization axis of the passive antenna, UP, to obtain the complex scalar:(7) eAP=<UP,EA(OP')> where <,> denotes the scalar product. Subsequently, we simulated the E-field distribution EA+P due to the active antenna A when the passive antenna P is present. The passive antenna was terminated by an absorbing TEM port of the same (real) impedance used in excitation mode. Since both antennas are perfect conductors, the overall field is an infinite sum of reflections between the active and passive elements:(8) EA+P=EA+kAP*(EP+kPA*(EA+...)) where kAP=kPA is the coupling factor between A and P. Due to losses in the domain, wave propagation and antenna misalignment, the coefficients were expected to be very small. Therefore, one can approximate the overall field as the sum of the impinging field and the first reflection only:(9) EA+PEA+kAP*EP From this relationship, the coupling factor kAP can be determined as the spatial average of the ratio between the remainder EA+P-EA and the coupled field EP. A more robust fit, however, can be obtained by means of decorrelation:(10) kAPM<E P,(EA+P-EA)> dMM<E P,EP> dM where M is the domain of the model, i.e., the bolus sphere including the phantom, and E denotes the complex conjugate of E. Once eAP and kAP have been determined for different arrangements of A and P, one can study the correlation between the two. For the present study, we generated 30 random pairs and obtained the complex scatter plots shown in Figure 8. The plots confirm the straightforward linear relationship between eAP and kAP. A complex coefficient c can be fitted on this set of points such that:(11) kAP=c*eAP for any arbitrary arrangement of A and P along the boundary of the water bolus. This important result enables the calculation of the overall field of an antenna in any array configuration given the individual fields E of the single antennas approximated in Section 2.5. For an array of n elements, the approximated true field distributions E^ relative to each antenna can be found as:(12) E^1E^2E^n=1ce12ce1nce211ce2ncen1cen21(K-1)*E1E2En where K is the total number of wave propagations that should be accounted for (first excitation followed by K-1 reflections). As shown later in Section 3, a sufficient number of propagations is K=3, and throughout the rest of the article we present results obtained utilizing this value. 2.6. Approximation Analysis We quantitatively assessed the approximation error of a single antenna field by comparing the interpolated distribution to an equivalent full simulation in COMSOL. The comparison was carried out for a series of 5 locations within the largest interpolation patch and of increasing distance from a simulated grid point, as shown in Figure 9. We assessed four different aspects of the average relative error between the simulated (SIM) and interpolated (INT) complex vector E-fields: the distribution (DIS), the amplitude (ABS), the phase (ANG), and the direction (DIR). These were calculated as: (13) eDIS=M|ESIM-EINT||ESIM|dM/+M+eABS=M||<U,ESIM> |-|<U,EINT> |||<U,ESIM> |dM/+M+eANG=M|wrap(<U,ESIM> -<U,EINT> )|pdM/+M+eDIR=Macos(<|ESIM|,|EINT|> /||ESIM||/||EINT||)p/2dM/+M+ where M denotes the patient model volume excluding the first 20mm of tissue in contact with the water bolus, and U is the (unitary) polarization vector of the antenna. The SIM and INT distributions were preliminarily mass-averaged according to the scheme described in Section 2.4. The values were evaluated for each individual frequency in the operating set. 2.7. Array Optimization The optimization task must determine the location of each antenna in an array of a given size (number of elements or channels, nc). The solver must also make sure that the solution represents a physically feasible arrangement. In particular, the antennas must be placed within the bolus boundaries and they must not overlap with each other. The first requirement is met by providing lower and upper boundaries to the tha and pha coordinates of each antenna. In the present case, pha was unbounded since the ellipsoid covers a full 360deg on the XY plane. The second requirement can be implemented as a set of non-linear constraints. If r is the radius of the smallest circle enclosing the antenna on its local UV plane, then the following has to be true for any pair (i,j) of antennas:(14) |L|-li-lj>0L=Oi-Ojli=(r<Ui,L> |L|)2+(r<Vi,L> |L|)2lj=(r<Uj,L> |L|)2+(r<Vj,L> |L|)2 where L is the vector from antenna j to antenna i. This constraint is sufficient as long as the curvature of the bolus ellipsoid is large compared to the size of the antenna along its W axis. Further constraints relevant for the HT treatment are the locations of the eyes. The optimizer should not place any antenna in front of these organs as they can be easily damaged by MW radiation. We determined the center O and radius r of each eye in the model as projected on the water bolus surface, and appended these terms to the set of constraints that was assembled according to Equation (14). If the pair (tha,pha) describes one antenna a, then the design procedure must solve a minimization problem consisting of 2*nc degrees of freedom. These degrees of freedom, however, are not truly independent from each other. For instance, in the case of 3 antennas, the solution vector:(15) (th1,ph1)(th2,ph2)(th3,ph3) represents an array arrangement that is identical to:(16) (th2,ph2)(th1,ph1)(th3,ph3) and similar permutations. In other words, there exists a semantic overlap between the optimization variables. Due to this, classical global optimization algorithms (particle swarm, genetic evolution, simulated annealing, etc.) cannot be employed for an efficient solution of this problem. Therefore, we adopted a simpler random search (RS) strategy followed by local refinement (LR). The RS stage generates a random set of uniformly distributed solutions within the optimization boundaries. This step also has to make sure that the generated points fulfill the non-intersection criterion discussed above. The number of initial solutions has to be enough to reasonably cover all qualitatively different array arrangements across the bolus surface. Intuitively, it can be expected that the translation of one element of the array in any direction by an amount smaller than l/2 does not result in a qualitatively different illumination of the body. This is also the rationale behind the choice of number of grid points in Section 2.5. At the same time, increasing the number of array elements (nc) produces more redundancy among a set of solutions, because different antennas can end up covering the same spot. Consequently, we estimated the number of initial random solutions to be generated as:(17) nr=round(np/nc) where np is the number of triangular patches available from the interpolation grid (which is inversely related to the minimum wavelength in water). Once all nr arrangements have been evaluated, the optimization enters the LR stage, which is implemented using fmincon from MATLAB's library. This function easily allows for the inclusion of the non-linear constraints, Equation (14). To reduce the computational time, we sorted the randomly generated solutions in ascending order according to their cost. We then applied the LR to the first solution, obtaining the minimum achievable HCQ for this qualitative arrangement. We proceeded with the next solution until the refined HCQ became worse, thereby assuming that the remaining qualitative arrangements were not likely to yield more favourable SAR patterns. The overall array design procedure is summarized in Figure 10. Here, we note that the rationale behind developing the analytical expressions reported in Section 2.5 and geometrical expressions for the bolus shape and the antenna coordinate system with respect to the spherical surface coordinates (th, ph), is to make the landscape of the cost-function (HCQ) as smooth as possible with respect to the array optimization variables (th and ph themselves). This is crucial for the LR step, which requires the gradients of the cost function to be numerically evaluated with respect to each optimization variable. 2.8. Design Validation We prepared 8 optimized array designs of increasing order: nc . For each arrangement, we performed a full array simulation in COMSOL. We compared the predicted and the actual SAR distributions according to the following metrics: (18) eDIS=M|SARSIM-SARINT||SARSIM|dM/+M+eH-S=+HSIMHINT+/+HSIM+eC-S=+CSIMCINT+/+CSIM+ where H denotes the hot-spot sub-volume mask (highest q-percentile of remaining healthy tissue) and C denotes the cold-spot sub-volume mask (lowest p-percentile of target volume). While eDIS denotes an error metric (the lower the better), eH-S and eC-S are coverage metrics (the higher the better). To quantify the overall improvement in heating capability of the optimized arrays, we carried out thermal simulations to evaluate the clinically relevant hyperthermia indexes T50 and T90 for each treatment plan. We also prepared a set of "canonical" applicator designs consisting of one or two rings of equally spaced antennas for nc and report their achieved temperature indexes. These applicators are shown in Figure 11. Since the canonical designs might violate the constraints relative to the avoidance of the eyes, during the evaluation of the treatment plans we turned off the channels relative to the antennas that overlap with the projected eye locations. This resulted in channel 02 being turned off in the canonical applicator design of order nc=10, while in the applicator of order nc=12 this applies to channels 02 and 03. 3. Results Grid Simulation The 221 simulations of the interpolation grid took about 200h on a 32 cores Intel Xeon 2.90 GHz system with 192 Gb of RAM. For comparison, a full eight-channel array simulation takes around 1h on the same computer system, while the interpolated approximation of the same array takes about 15 s, yielding a speedup of roughly 240 times. As the optimizer evaluates around 2000 potential array configurations to determine the best arrangement for eight antennas, the use of the approximation method renders the global optimization feasible. The numbers are even more compelling for higher array sizes. An example of interpolated versus simulated SAR distribution is shown in Figure 12 for the optimized array design of size nc=08 . The two distributions agree well qualitatively. The relative error becomes unacceptable (50%) only in regions far from the antennas, such as the mouth , where the SAR intensity is almost negligible. The cold spot is predicted with high accuracy (eC-S=81%), while the hot-spot identification suffers the most from the approximation error (eH-S=46%). Figure 14 reports the results of the analysis of the approximation for a single antenna at locations of increasing distance from a simulated grid point. As the selected patch is the largest triangle across the grid, this represents a worst-case scenario. The overall average distribution error eDIS reaches a peak of almost 30% when the query location is near the center of the patch. This error is mainly due to a difference in amplitude, as can be seen from Figure 14b. The phase is approximated with the highest accuracy. The optimized applicator designs for each array size are shown in Figure 13. These should be compared with the location and shape of the target volume, recall Figure 1. The designs of order up to four consistently placed an antenna in the closest proximity to the distal part of the tumor. Beginning from order four, an antenna was also placed on the opposite, frontal side of the head. The design for nc=6 closely resembles a canonical one with two interleaved rings of three antennas. The treatment plans prepared using the optimized designs yielded the values of HCQ and temperature indexes shown in Figure 15. The figure also reports the corresponding values for the canonical designs. The HCQ predicted by the interpolated distribution follows quite closely the actual HCQ evaluated on the simulated distribution, except for the 10-antennas canonical case, which, however, performs poorly in terms of target temperature increase. The relative changes in interpolated 1/HCQ values correlate well with the variations in temperature indexes for both canonical and optimized designs. The only exception is the 12-antennas optimized case, likely due to the main hot spot becoming superficial, as discussed in the following section. The improvement in T50 from the best canonical solution (nc=8) to the best optimized solution (nc=10) is 0.2degC. The improvement in T90 from the best canonical solution (nc=8) to the best optimized solution (nc=10) is 0.3degC. The SAR and temperature distributions relative to the plans obtained with each optimized design are reported in Figure 16 and Figure 17. The progressive inclusion of more antennas reduces the cranial-caudal elongation of the hot-spot volumes in SAR and simultaneously shifts them closer to and more uniformly surrounding the target volume, which is the desired behavior. The hot-spot masks in SAR follow well the actual resulting location of the temperature peak, except for the 12-antennas case. Here, the hot spot becomes superficial and the SAR prediction degrades. In the majority of dense-array applicator designs, however, the limiting hot spot arises in the pocket of CSF caudal to the target volume. Table 1 reports the average relative approximation errors and spot mask coverage of each SAR distribution, for both optimized and canonical designs. It is interesting to notice that the distribution error and the mask coverage do not necessarily agree. In particular, eDIS is relatively high for the smaller array sizes 02 and 03, but the spot identification has a high degree of accuracy (eH-S,eC-S>79%). On the contrary, eDIS diminishes for denser arrays, but the hot-spot identification eH-S becomes worse. While the distribution errors reach, at most, 30% in the majority of cases, the canonical design of size 10 experiences a remarkably larger approximation error of 58%. This also reflects in a poor hot-spot identification score of only 41%. To further investigate the reasons behind the failed approximation of the regular ring of 10 antennas, we show the simulated and approximated SAR distributions of this array in Figure 18. The distributions suggest that the inaccuracy stems from a misidentification of the hot spot, which is, in turn, due to a large relative error in the SAR values in the regions of high intensity located cranial and caudal to the target. To understand where this error originates, we show the array arrangement in Figure 19 and the steering power of each channel from the HCQ-optimal treatment plan in Table 2. We further report the relative distribution, amplitude, phase and direction errors of the individual antenna fields in Table 3. Note that the approximations are now severely affected by the amplitude error introduced by the coupling effects between antennas in the array, which is expected. This error is often above 100% because of the high relative errors in the regions of the model subjected to low field intensity. Nevertheless, antennas 02, 06, 07 and 09 exhibit a substantial error above average in the amplitude approximation at the 250MHz operating frequency, which is the main contributor to the total treatment power. Antenna 02 can be disregarded, since its power is zero in the treatment plan. Antenna 07 is also not likely to play a role in the highlighted hot-spot areas, as these lie far from the antenna location. Antennas 06 and 09, on the other hand, are closer to the target and illuminate it from opposite sides with relatively high power. Their deposition patterns interfere precisely in the hot-spot regions and produce an amplitude error that results in an inaccurate prediction of the HCQ value. 4. Discussion The purpose of the approximation method developed in the present work is to facilitate the qualitative evaluation of a large number of array configurations prior to the HT treatment of a brain cancer patient. The assessment of the treatment plans was performed in terms of clinically established parameters, i.e., median temperature T50 and 90-percentile temperature T90 . Due to the added computational complexity of thermal simulations, however, the direct assessment of the temperature distribution for thousands of array configurations becomes impractical. The proposed SAR-based field approximation method circumvents this limitation and enables the qualitative evaluation of a given antenna arrangement within seconds. Together with our previously devised SAR-based iterative time-reversal multi-frequency treatment-plan optimization , these tools can be used in combination with optimization algorithms to refine an applicator design for a specific patient. We argue that the proposed approximation method is accurate enough for relative comparison between different design solutions. To support this conclusion, we needed to address the two specific cases (canonical nc=10 and optimized nc=12) where the approximation method performed worst. In the first case (canonical nc=10), the error arose already in the SAR distribution, and the reason for this is the imprecise prediction of the field amplitudes in the zones around the target. The error originates in the inaccurately modelled interference of two antenna fields. As the method consists of extensive approximations, the appearance of outliers is to be expected. A possible workaround could be a local refinement of the interpolation grid in the regions where one anticipates strong radiation powers. Nevertheless, even at this rather coarse sampling, the relative predictions are still correct: the approximated trend of HCQ for the canonical solutions follows the simulated one, and these are reflected in corresponding variations in T50 and T90, which means that the method can be used for qualitative assessment. However, in the second case (optimized nc=12), the relative improvement in HCQ was also correctly predicted, but this was not reflected in a temperature increase. The reason must be traced to the shift in the location of the most prominent hot spot. While such a limiting hot spot is located in the pocket of CSF caudal to the target volume for the treatment plans relative to the optimized dense arrays nc= , in the optimized nc=12 case the peak temperature was reached near the superficial part of the tumor . We have previously shown that 1/HCQ correlates well with the temperature indexes T50 and T90 for deep targets, but the correlation quickly deteriorates for superficial targets if the water bolus directly affects the temperature distribution in the target volume , as the SAR distribution can no longer predict the location and severity of each spot. One can, thus, speculate that an analog mechanism lies behind this result. Improved temperatures might be achieved with more aggressive water-bolus cooling to suppress the superficial hot spot and restore the SAR-temperature correlation. Alternatively, a thinner exclusion layer in the SAR evaluation mask might guide the optimizer towards solutions that deposit less power in the superficial zone. In this study, we applied a 20mm exclusion, which is on the upper limit of typical cooling depths for clinical water boluses employed in superficial hyperthermia treatments . The comparison between optimized and canonical arrays reveals only a moderate gain in indexed temperatures . This is expected, as the present canonical designs are in fact already tailored to the patient in terms of antenna design and bolus shape. Nevertheless, the achieved gains are still clinically relevant since an increase by 0.3degC in T90 would correspond to an increase by 1.5 in thermal dose when T90 is below the breakpoint value of 43degC, according to the CEM43T90 model . This is further supported by the consideration that measured temperature changes have been shown to reflect the relative variations predicted by numerical simulations with a precision as small as 0.1degC . One could expect even larger differences for tumors located higher in the supratentorial region where the traditional conformal ring design is presumably less effective at delivering the dose due to the geometry of the vertex. The need to down-sample the patient model from 1mm to 4mm, in order to maintain the simulation of the interpolation grid within reasonable time, might represent a limitation in the proposed method. The detail of the segmentation of the CSF, in particular, has been shown to affect the resulting temperature profiles . The CSF can present features below 4mm, especially in the layer between the skull and brain. In this particular medulloblastoma model, however, we can still afford such a coarse meshing as the limiting hot spot consistently arises in the deep pocket of CSF adjacent to the target. We verified that this is the case even when a denser grid of 1mm is utilized for the simulation . The CSF in this region is sufficiently captured by a 4mm resolution for the purpose of assessing qualitative antenna arrangements for this target. However, this may not be the case when other tumor locations and sizes are considered. Glioblastoma patients, for instance, would likely require finer meshing to account for the occurrence of hot spots in the distal layers of CSF. As a final note, we address the question on whether it is meaningful to consider applicator designs with such a degree of customization for a certain patient, especially when it is already a challenge to accurately model and position patients in much simpler applicator designs . In our opinion, the rationale behind this contribution lies in addressing a particularly challenging anatomical region, the brain, and strive for a design that will eventually enable hyperthermia treatments in this organ. Such treatments might require a higher degree of customization than current clinical solutions. The method allows us to qualitatively sift through many potential array configurations and select the most suitable one for a certain tumor size, shape and location. In a practical setting, we envision this method being used for the development and manufacturing of a limited set of (head) applicators, each with a qualitatively different antenna arrangement and optimized for a specific target location. During the treatment planning stage, the applicator with the best heating capability for the patient at hand can be determined and selected. Unfortunately, a direct comparison with current clinical applicators is not possible, as these were not intended for brain-tumor treatment. Furthermore, any comparison with the absolute temperatures reported in the literature would be affected by the considerable uncertainties in thermal simulations and their strong dependence on the specific patient modeling. 5. Conclusions We proposed and validated, by means of numerical comparisons, a novel field-approximation method for the fast evaluation of different antenna arrangements in a helmet applicator for intracranial microwave hyperthermia treatments. The method was further used in conjunction with a fast multi-frequency treatment-plan optimization scheme to improve the design of an applicator for a specific paediatric brain-cancer patient. The method is accurate enough to provide qualitative indications about the most suitable antenna arrangement for a given tumor shape and location. The technique can be particularly useful in the design of UWB applicators where the classical single-frequency array theory used for narrow-band applicators might prove insufficient to achieve an optimal configuration. Further studies are required to assess the sensitivity of the proposed technique to the resolution of the interpolation grid, and future developments might involve the inclusion of the antenna polarization angles in the set of design parameters. Acknowledgments Thanks to Lennart Svensson and Andreas Fhager for providing extra computational resources. Author Contributions Conceptualization, H.D.T. and M.Z.; methodology, M.Z. and E.E.; software, M.Z. and E.E.; validation, M.Z.; formal analysis, M.Z. and E.E.; investigation, M.Z. and H.D.T.; resources, H.D.T.; data curation, M.Z.; writing--original draft preparation, M.Z.; writing--review and editing, H.D.T.; visualization, M.Z.; supervision, H.D.T.; project administration, H.D.T.; funding acquisition, H.D.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement For this specific planning study using pre-acquired CT/MRI datasets without clinical data, no additional informed consent was required. Data Availability Statement Data available on request due to restrictions, e.g., privacy or ethical. The data presented in this study are stored on secure servers and available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Abbreviations The following abbreviations are used in this manuscript: UWB Ultra-wide band MW Microwave HT Hyperthermia RF Radio-frequency CSF Cerebrospinal fluid BED Biologically equivalent dose HCQ Hot-to-cold spot quotient SAR Specific absorption rate PLD Power loss density HTV Hyperthermia target volume MRI Magnetic resonance imaging SGBT Self-grounded bow tie EM Electromagnetic TH Thermal PEC Perfect electric conductor TEM Transverse electromagnetic PML Perfectly matched layer GPU Graphic processing unit RAM Random access memory SIM Simulated INT Interpolated DIS Distribution ABS Amplitude ANG Phase DIR Direction DIF Difference RS Random search LR Local refinement CEM43T90 Cumulative equivalent minutes at 43degC using T90 Figure 1 Sections of the segmented patient model (gray) at the original resolution of 1mm, with superimposed target volume (cyan). Figure 2 Self-grounded bow-tie antenna optimized for the 250-500 MHz band. The antenna's polarization axis u is aligned with the x axis (red), while its main directivity axis w is aligned with the z axis (blue). The center of the antenna's local coordinate system corresponds to the center of its ground plate, which is also the center of the circular feed opening. The overall dimensions are 8.7cm along x, 6.2cm along y, and 2.4cm along z. Figure 3 Patient model (gray) down-sampled to a 4mm resolution, together with the water bolus shape (blue). The ellipsoid is designed to maintain a bolus thickness as close as possible to 5cm around the scalp and is clipped right above the shoulders and nostrils to allow for breathing. The resulting bolus dimensions are 25.0cm along the left-right axis, 28.4cm along the anterior-posterior axis, and 22.1cm along the cranial-caudal axis. Figure 4 Reference schematic for the arrangement of a single antenna. Note that the angle ph, while following the classic right-hand convention, is shown here on the negative y half-space for readability. The figure refers to a local coordinate system centered at the ellipsoid's center and aligned with the global cartesian axes. Figure 5 Interpolation grid made of 221 points (black) uniformly distributed around the child patient model (gray) and lying on the surface of a fitted ellipsoid. The average distance between pairs of nearby points is 2.6cm. Figure 6 Reference schematic for the field interpolation procedure, using a less dense grid to facilitate reading. The ellipsoid is shown in its entirety to highlight the different radii. However, in the actual simulation model, the bolus was clipped at the level of the shoulders. We show the ellipsoid center C and its radii a, b, c. The interpolation grid is shown with black circles. The selected interpolation patch (O1,O2,O3) for an antenna at location Oa is highlighted with thick black edges and yellow vertices. The local coordinate systems of the selected grid points are also shown. An equivalent system was built for the query antenna location Oa. Figure 7 Procedure to determine the coupling between antenna pairs. A spherical brain phantom (a) was inserted into a spherical bolus (b). An active (A) and a passive (P) antenna were added inside the bolus. First, the individual fields EA and EP of each antenna were determined without the presence of the other antenna. Subsequently, the active antenna was excited with the presence of the passive antenna and the overall coupled field EA+P was determined. A correlation factor between the coupled field EA+P and the passive antenna field EP was determined. This was found to be proportional to the projection on UP of the individual field EA at the location of the passive antenna (c). Figure 8 Correlation between the projection eAP of the active antenna's field EA on the passive antenna's polarization axis UP at OP', and the coupling coefficient kAP obtained by decorrelation of the remainder field EA+P-EA with respect to EP. The results are reported for each frequency in the operating set. The solid black lines show the fitted complex coupling coefficient c, while the legends report the correlation coefficients for each fit. The fit was carried out on the complex values. Figure 9 Location sweep for the sensitivity analysis of the field interpolation error. The black circles represent the interpolation grid points. The yellow dots are the grid points selected for interpolation, and are the corners of the triangular patch of largest area. The gray shade is the patient in bird's eye view. The local coordinate systems of each antenna location to be approximated are shown as superimposed triplets. Figure 10 Applicator optimization procedure to determine the best antenna arrangement for a given patient. The procedure begins at the red step and ends at the green step. The steps highlighted in blue involve the sub-steps shown in (b) to determine the cost-function value of a certain array arrangement. Figure 11 Canonical applicator designs with increasing number of antenna elements (nc) for the medulloblastoma pediatric patient model (gray) using the fitted ellipsoidal water bolus shape (blue). Figure 12 Comparison of the normalized SAR distributions obtained via approximation (INT) and full simulation (SIM) for the optimized applicator design of order nc=08. Sections of the SAR distribution inside the patient model, taken at the target center. The volumes in magenta represent the highest q-percentile in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile in the target (cold spot). The difference (DIF) distribution is relative to the simulated one, i.e., SARDIF=|SARSIM-SARINT|/|SARSIM|. In (b,e), the volumes in magenta represent hot-spot coverage (HSIMHINT), while the volumes in cyan represent cold-spot coverage (CSIMCINT). The volumes in red represent hot-spot exclusion (HSIMHINT), while the volumes in blue represent cold-spot exclusion (CSIMCINT). Figure 13 Optimized applicator designs with increasing number of antenna elements (nc) for the medulloblastoma pediatric patient model (gray) using the fitted ellipsoidal water bolus shape (blue). Figure 14 Average relative error between the interpolated and simulated E-field distributions of a single antenna at increasing distance from a grid point for different frequencies across the operating band. The step indicates the position of the antenna within the interpolation patch, where zero corresponds to one of the simulated corners. A phase error eANG of 100% means that the fields are in opposition. A direction error eDIR of 100% means that the fields are orthogonal. Figure 15 Values of HCQ, T50 and T90 relative to the treatment plans prepared using canonical and optimized applicator designs of increasing order (line plots). The values for the canonical applicator designs are also reported as scatter plots. In SAR, the value of HCQ predicted by the field approximation is compared against the value from the actual simulated field. Figure 16 Normalized SAR distributions relative to each optimized applicator design with increasing number of antenna elements (nc). Sections taken at target center. The white line delineates the target volume. The volumes in magenta represent the highest q-percentile (2.8%) in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile (50%) in the target (cold spot). Figure 17 Temperature distributions relative to each optimized applicator design with increasing number of antenna elements (nc). Sections taken at target center. The views are flipped to show the side where the temperature peak in the healthy tissue is located, marked with a black dot, which is located off plane with respect to the sections. The white line delineates the target volume. Figure 18 Comparison of the normalized SAR distributions obtained via approximation (INT) and full simulation (SIM) for the canonical applicator design of order nc=10. Sections of the SAR distribution inside the patient model, taken at the target center. The volumes in magenta represent the highest q-percentile in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile in the target (cold spot). The difference (DIF) distribution is relative to the simulated one, i.e., SARDIF=|SARSIM-SARINT|/|SARSIM|. In (b,e), the volumes in magenta represent hot-spot coverage (HSIMHINT), while the volumes in cyan represent cold-spot coverage (CSIMCINT). The volumes in red represent hot-spot exclusion (HSIMHINT), while the volumes in blue represent cold-spot exclusion (CSIMCINT). The white circle in (d-f) highlights the location of the hot-spot misidentification. Figure 19 Geometrical setup for the canonical applicator design of order nc=10. The patient model (gray) is shown together with the antenna local coordinate systems, where the red vector is U, the green vector is V, and the blue vector is W. The antenna center is represented by a black dot and labeled with the channel number. The target volume is highlighted in yellow. cancers-15-01447-t001_Table 1 Table 1 Error indicators of the overall approximated SAR distributions with respect to the corresponding distributions obtained from full simulations. eDIS distribution error, eH-S hot-spot mask error, eC-S cold-spot mask error. Both optimized (OPT) and canonical (CAN) array designs are reported. The last four rows report the same error indicators for the densest optimized array and increasing propagation order K for the coupling modeling. eDIS[%] eH-S[%] eC-S[%] nc=01 (OPT) 08 98 99 nc=02 (OPT) 32 80 95 nc=03 (OPT) 36 79 96 nc=04 (OPT) 22 63 87 nc=06 (OPT) 28 54 84 nc=08 (OPT) 29 46 81 nc=10 (OPT) 32 46 82 nc=12 (OPT) 28 65 84 nc=06 (CAN) 26 46 88 nc=08 (CAN) 20 69 91 nc=10 (CAN) 58 41 84 nc=12 (CAN) 25 57 85 nc=12 (OPT) [K=1] 42 62 86 nc=12 (OPT) [K=2] 34 71 94 nc=12 (OPT) [K=3] 28 65 84 nc=12 (OPT) [K=4] 29 72 95 nc=12 (OPT) [K=5] 28 44 78 cancers-15-01447-t002_Table 2 Table 2 Normalized power radiated by each antenna according to the channel steering parameters of the HCQ-optimal solution for the 10-elements canonical array design. The last row and column report the total power per frequency and per antenna, respectively. POWER [%] 250 MHz 375 MHz 500 MHz Antenna Total: Ant. 01 06 04 05 15 Ant. 02 00 00 00 00 Ant. 03 02 01 03 05 Ant. 04 07 08 02 17 Ant. 05 16 05 02 23 Ant. 06 03 01 02 06 Ant. 07 01 06 03 10 Ant. 08 01 03 04 09 Ant. 09 05 01 04 09 Ant. 10 04 01 02 07 Frequency total: 44 30 26 cancers-15-01447-t003_Table 3 Table 3 Error indicators of the approximated E-field distributions of each individual antenna in the 10-elements canonical array design, with respect to the corresponding distributions obtained from the full-array simulation. eDIS distribution error, eABS amplitude error, eANG phase error, eDIR direction error. The last row reports the average error among the set of antennas. eDIS[%] 250 MHz 375 MHz 500 MHz eABS[%] 250 MHz 375 MHz 500 MHz Ant. 01 144 099 080 Ant. 01 109 071 046 Ant. 02 201 134 106 Ant. 02 171 117 072 Ant. 03 153 111 091 Ant. 03 127 094 069 Ant. 04 152 106 080 Ant. 04 121 071 051 Ant. 05 150 113 074 Ant. 05 091 095 062 Ant. 06 179 155 096 Ant. 06 151 119 088 Ant. 07 221 161 101 Ant. 07 185 114 102 Ant. 08 155 157 088 Ant. 08 104 105 063 Ant. 09 156 150 096 Ant. 09 160 111 095 Ant. 10 151 144 086 Ant. 10 116 101 055 MEAN: 166 133 090 MEAN: 133 100 070 eANG[%] 250 MHz 375 MHz 500 MHz eDIR[%] 250 MHz 375 MHz 500 MHz Ant. 01 026 022 018 Ant. 01 023 022 022 Ant. 02 040 035 026 Ant. 02 024 027 024 Ant. 03 032 026 025 Ant. 03 024 025 024 Ant. 04 027 022 020 Ant. 04 023 025 021 Ant. 05 028 023 018 Ant. 05 024 024 021 Ant. 06 028 030 032 Ant. 06 023 024 025 Ant. 07 032 035 032 Ant. 07 022 025 025 Ant. 08 026 031 027 Ant. 08 022 023 021 Ant. 09 030 033 025 Ant. 09 021 024 023 Ant. 10 025 029 025 Ant. 10 021 024 023 MEAN: 029 029 025 MEAN: 023 025 023 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000506 | Pancreatic ductal adenocarcinoma remains a global health challenge and is predicted to soon become the second leading cause of cancer death in developed countries. Currently, surgical resection in combination with systemic chemotherapy offers the only chance of cure or long-term survival. However, only 20% of cases are diagnosed with anatomically resectable disease. Neoadjuvant treatment followed by highly complex surgical procedures has been studied over the last decade with promising long-term results in patients with locally advanced pancreatic ductal adenocarcinoma (LAPC). In recent years, a wide variety of complex surgical techniques that involve extended pancreatectomies, including portomesenteric venous resection, arterial resection, or multi-organ resection, have emerged to optimize local control of the disease and improve postoperative outcomes. Although there are multiple surgical techniques described in the literature to improve outcomes in LAPC, the comprehensive view of these strategies remains underdeveloped. We aim to describe the preoperative surgical planning as well different surgical resections strategies in LAPC after neoadjuvant treatment in an integrated way for selected patients with no other potentially curative option other than surgery. locally advanced pancreatic ductal adenocarcinoma neoadjuvant treatment extended pancreatectomies portomesenteric venous resection arterial resection This research received no external funding. pmc1. Introduction Pancreatic ductal adenocarcinoma (PDAC) remains a global health challenge and is predicted to soon become the second leading cause of cancer death in developed countries . Currently, surgical resection in combination with systemic chemotherapy offers the only chance of cure or long-term survival. However, only 20% of cases are diagnosed with anatomically resectable disease. Even localized PDAC should be approached as a systemic disease. For patients with locally advanced pancreatic ductal adenocarcinoma (LAPC), neoadjuvant treatment (chemotherapy with or without chemoradiotherapy) followed by highly complex surgical procedures has been studied during the last decade with promising long-term results . In recent years, a wide variety of complex surgical techniques that involve extended pancreatectomies, including portomesenteric venous resection (PVR), arterial resection (AR), or multi-organ resection, have emerged to optimize local control of the disease and improve postoperative outcomes. Microscopic tumor involvement in the resection margin and lymph node metastases are common in this scenario, and, therefore, local recurrence is frequent and conditions patient survival. One of the main challenges in LAPC is achieving tumor-free resection margins (R0 = tumor-free margin > 1 mm) and lymph nodes clearance due to extensive tumor burden and dense desmoplastic tissue. Although there are multiple surgical techniques described in the literature to improve outcomes in LAPC, the comprehensive view of these strategies remains underdeveloped. We aim to describe the preoperative surgical planning as well different surgical resections strategies in LAPC after neoadjuvant treatment in an integrated way for selected patients with no other potentially curative option other than surgery. 2. Preoperative Surgical Planning Multidetector computed tomography (MDCT), using specific pancreatic contrast protocols, represents the most widespread method for establishing a suspected diagnosis of PDAC. It allows precise staging of the disease, determining tumor resectability and surgical planning according to vascular variations and/or adjacent organ invasion. Historically, localized pancreatic disease has been classified as resectable (without vascular involvement by imaging methods) or locally advanced (unresectable, with extensive arterial or venous vascular involvement). According to the consensus statement of the International Study Group of Pancreatic Surgery (ISGPS) , which is based primarily on the recommendations of the National Comprehensive Cancer Network (NCCN), LAPC presents involvement of the superior mesenteric artery (SMA) or the celiac trunk (CT) in more than 180deg of the vascular circumference or compromise of the aorta and/or compromise of the superior mesenteric vein (SMV) or portal vein (PV), which makes it impossible to provide adequate vascular resection and reconstruction in the absence of distant metastatic disease . The term borderline has been used to describe tumors that are potentially resectable, but that have some degree of vascular involvement. A borderline tumor would be one with reconstructable venous involvement (SMV or PV) and/or contact within 180deg of the vascular circumferences of arterial structures. However, considerable disparities in multidisciplinary team evaluations of patients with pancreatic cancer exist, including substantial variation in resectability assessments . A recent symposium of experts from Western and Eastern high-volume centers reported new resectability classifications from their respective institutions based on tumor biology, conditional status, pathology, and genetics, in addition to anatomical tumor involvement. Interestingly, experts from all the centers reached the agreement that anatomy alone is insufficient to define resectability in the current era of effective neoadjuvant therapy . Neoadjuvant chemotherapy, with or without chemoradiotherapy, may result in successful resection in up to 60% of patients with LAPC with a substantial survival advantage . In high-volume pancreatic centers and after discussion by a multidisciplinary team, surgical exploration may be suggested in patients with non-progressive (stable or regressing) RECIST criteria to assess the possibility of pancreatic resection. Nevertheless, as the resectability of PDAC is well-defined by vascular involvement rather than tumor volume, RECIST is not suitable for the evaluation of tumor response following neoadjuvant treatment. Moreover, MDCT may underestimate the response of neoadjuvant therapy and, therefore, the discrimination of the venous and/or arterial compromise, since the discrimination between fibrosis and viable tumor remains very complex. A recent development in post-process-rendering, called cinematic rendering, overcomes this by utilizing advanced light modeling to generate photorealistic 3D images with enhanced details. For local determination of resectability, vascular mapping allows for accurate assessment of major arteries and the portovenous system. For the portovenous anatomy, it assists in determining the optimal surgical approach (extent of resection, appropriate technique for reconstruction, and need for mesocaval shunting). For arterial anatomy, vessel encasement either represents dissectible involvement via periadventitial dissection or true vessel invasion that is unresectable . Magnetic resonance imaging--halo sign, defined as replacement of solid perivascular (arterial and venous) tumor tissue by a zone of fatty-like signal intensity--might be helpful to assess the effect of induction chemotherapy in patients with LAPC . Further investigations incorporating quantitative parameters such as radiomics and deep learning may improve diagnostic performance of MDCT for predicting R0 resection . Another important aspect during patient work-up is the decreased levels of tumor marker serum carbohydrate antigen (CA) 19-9 after neoadjuvant therapy, because this may predict a better prognosis, with low incidence of hepatic recurrence after surgery . Rose et al. identified that the percent decrease in CA19-9 from baseline to minimum value (odds ratio [OR] 0.947, p <= 0.0001) and the percent increase from minimum value to final restaging CA19-9 (OR 1.030, p <= 0.0001) were predictive of tumor progression in patients with advanced pancreas cancer. Tanaka et al. recently described that the shrinkage rate of the primary tumor, the response rate of MDCT density attenuation of the tumor, and post-chemotherapy CA19-9 serum levels were independent predictors of survival in patients with resected LAPC after preoperative treatment with FOLFIRINOX. Then, 18 F-fluorodeoxyglucose PET/CT was proposed as a radiologic marker to predict the prognosis and treatment response of neoadjuvant therapy for PDAC . Recently, Abdelrahman et al. showed that among patients with post-neoadjuvant therapy, FDG PET highly predicts pathologic response (odds ratio, 43.2; 95% CI, 16.9-153.2), recurrence-free survival (hazard ratio, 0.37; 95% CI, 0.2-0.6), and overall survival (hazard ratio, 0.21; 95% CI, 0.1-0.4), and is superior to biochemical responses alone (CA 19-9). A recent classification proposed a four-stage Whipple procedure categorization based on the extent of surgery and surgical outcomes. Multivisceral pancreatoduodenectomy (type 3) or pancreatoduodenectomy with arterial resection (type 4) had increased probability of surgical complications, relaparotomy, and 90 day mortality . Type 3 and 4-types are correlated with pancreatic resections in LAPC. Therefore, thorough extensive preoperative work-up stratification, taking into account age, comorbidities, functional status, and the viability of the procedure can improve patient selection and predict adverse postoperative events in major cancer surgery . We select our LAPC patients for surgery after neoadjuvant therapy, considering many of these anatomical and biologic criteria and conditional parameters described above, discussed on a case-by-case basis in our multidisciplinary committee. 3. Surgical Aspects The early steps of the operation are similar as in conventional pancreatic resection and some technical aspects have been described previously . However, we would like to emphasize some aspects that may be essential to resolve complex vascular resections and achieve local and overall recurrence. Through an extensive Kocher maneuver in combination with the Cattell-Braasch mobilizations of the cecum, right colon, right colonic flexure, and the root of the small bowel. together with the Treitz ligament. an adequate exposure of the entire infrahepatic vena cava (IVC), aorta, the left renal vein (LRV), and the right origin of the SMA, which is situated just above the LRV, can be achieved and offer adequate tractability of the mesenteric root in case segmental vein resection and reconstruction should become necessary . The origin of the SMA can be marked by a vessel loop to recognize the vessel during the margin dissection and have the facility to clamp the SMA if needed, to prevent bowel congestion during complex venous reconstructions. In the literature there are different approaches to the SMA . All alternatives of the artery-first techniques have in common the fact that dissection is achieved within the tunica adventitia of the SMA. The approach depends on the results of preoperative imaging defining the place of the most likely tumor relating to the vessel. The SMA can be approached from a left-sided infracolic approach if tumors of the body or tail of the pancreas are supposed to infiltrate the artery from this direction . The small bowel can be flipped to the right side of the patient, and the peritoneum opened along the mesentery root parallel and to the left of the proximal jejunum and the duodenojejunal flexure. The origin of the SMA from the right was already identified in the angle formed by the IVC and LRV with the extended Kocher maneuver; on the right side of the SMA, a replaced or accessory right hepatic artery, if existing, can be identified and preserved and the dissection is carried out cephalad beside the aorta until the origin of the SMA is reached. In the situation that MDCT shows tumor extension close to the jejunal branches of the SMV or distal aspects of the SMA, the identification of the superior mesenteric vessels is performed at the root of the mesentery below the transverse mesocolon to the origin from the aorta. The middle colic artery is detached at its origin from the SMA in this manner, and the tumor-infiltrated section of the transverse mesocolon is resected to remain with the specimen . The first jejunal loop is consequently divided and moved to the superior right side of the abdomen. Meticulous dissection beside the SMA with alternation between both directions of dissection, leaves the right lateral circumference of the SMA free from all adjacent soft tissue with the inferior pancreaticoduodenal vessels severed at their origin, or even more clearing the autonomous nerves from the right and posterior circumference of the SMA . A recent systematic review and meta-analysis showed that patients undergoing an artery-first approach to pancreatoduodenectomy may be associated with improved perioperative outcomes and survival in comparison with those having standard pancreatoduodenectomy . The strategy depended on the results of preoperative imaging defining the site of the most likely tumor infiltration. Standard distal pancreatectomy and splenectomy for PDAC in the body or tail have been associated with high positive margin rates and poor overall survival in relation to tumor infiltration of the anterior renal fascia and the left adrenal gland . For this purpose, radical antegrade modular pancreatosplenectomy (RAMPS) is suggested . Conventional RAMPS proceeds in a right-to-left antegrade manner, with early parenchymal transection at the neck of the pancreas and early control of the splenic vessels (in its origin), CT and SMA lymphadenectomy, as well as full visualization of the retroperitoneal plane of dissection . The posterior magnitude of dissection can result in front of the adrenal gland, behind the anterior renal fascia (anterior RAMPS), or behind the left adrenal gland (posterior RAMPS) . The primary goals of RAMPS are to increase the rate of R0 resection and lymph node yield for pancreatic cancer in the body or tail. The resolution to perform anterior or posterior RAMPS is made based on the posterior extent of tumor invasion. It has been theorized that one of the explanations for the poor long-term survival is that tumor-infiltrated autonomous nerve spreads frequently in the preaortic region and this spread can lead to positive resection margins or sites of tumor-infiltrated lymphatic tissue. The TRIANGLE operation is a proper approach to achieve a complete and radical removal of the tumor and associated lymphatic or perineural extension along a region defined anatomically by the origins of the CT (superiorly), the SMA (inferiorly), and the portal vein (anteriorly) . The dissection of the triangle region is best conveyed after the pancreatic head has been entirely mobilized from the SMA and follows the CT from its origin to the common hepatic artery. The CT and SMA might be totally dissected from the right (pancreatoduodenectomy) or the left side (distal pancreatosplenectomy). If a total pancreatectomy has been executed, both arterial vessels should be dissected circumferentially. Extended resection of neural and lymphatic tissue carries a risk of increased surgical morbidity, including adverse effects such as postoperative bleeding, uncontrolled diarrhea, and ascites. 4. Extended Pancreatectomy As mentioned above, the LAPC clinical scenario can be associated with unconventional resections of organs adjacent to the pancreas that involve multivisceral resections. The ISGPS published a list of structures and organs additionally to the ones resected in a standard pancreatoduodenectomy, pancreatic left resection, or a total pancreatectomy because of the many different classifications that existed to that point . Some publications propose that the surgical morbidity is increased in extended resections while overall perioperative mortality appears to be similar compared with standard pancreatectomies . This increased perioperative morbidity demands close postoperative follow-up of these patients and an elaborate and aggressive management of complications that can only be provided in specialized high-volume centers. 5. Vein Resection and Reconstruction Pancreatic surgery in combination with PV and/or SMV resection represent a frequent and more complex surgical scenario in patients with LAPC compared with standard pancreatic resection. Although several studies suggest that pancreatic resections with PVR are associated with acceptable perioperative risk, performing venous resection undoubtedly adds a technical challenge to an already complex surgical procedure . The benchmark cohort revealed a 4% or less in-hospital mortality, with a portal vein thrombosis rate <= 14% . A nationwide cohort analysis showed that patients with segmental resection, but not those who had wedge resection, had higher rates of major morbidity (odds ratio = 1.93, 95% CI 1.20 to 3.11) and worse overall survival (hazard ratio = 1.40, 95% CI 1.10 to 1.78) compared to patients without venous resection . The extent of en bloc venous resection is related to the possibility of venous reconstruction, while the technique of vascular reconstruction differs drastically based on anatomical vascular variations and surgeon preferences. The ISGPS suggests a specific categorization of the types of venous reconstruction to be incorporated in analyses for more detailed and evidence-based evaluation in patients with venous involvement . Small venous wedge resections can be resolved with direct suture of the vein (type 1). In this circumstance, all types of venous narrowing should be avoided to prevent thrombotic complications . A lateral patch into the venous defect can be safely used for some defects (type 2). Autologous substitute for venous reconstruction, such as parietal peritoneum, can be harvested from the diaphragm, the right or left hypochondrium, or the falciform ligament . The mesothelial layer of the patch can be placed on the intraluminal side of the vein and the musculoaponeurotic layer outside . These autologous sources represent a quick and accessible alternative for vascular reconstruction, especially when the need for venous resection is unexpected. Segmental defects can frequently be reconstructed with primary end-to-end anastomosis (type 3) . With the Cattell-Braasch mobilizations of the right hemicolon and mesenteric root, together with the Treitz ligament, an appropriate flexibility for segmented vascular resection and tension-free anastomosis of the porto-mesenteric axis can be obtained. If the splenic vein needs to be divided, various possibilities exist. In most patients, the splenic vein can be ligated, without clinical intervention. However, if venous congestion of the stomach or spleen occurs, the splenic vein can be reimplanted into the PV or SMV in an end-to-side fashion. The use of a vascular graft interposition (type 4) is contemplated for the reconstruction of large vascular segment defects . Suitable autologous graft substitutions for venous reconstruction include LRV, saphenous vein, inferior mesenteric vein, jugular vein, gonadal vessels, peritoneal substitutes (with the possibility of peritoneal tubular graft confection), cryopreserved veins, cadaveric graft veins, or synthetic graft prothesis with materials such as polytetrafluoroethylene (PTFE). The use of PTFE has the drawback of long-term anticoagulation in relation to high risk of vascular thrombosis or prothesis infection. Cavernous transformation of the PV represents a challenging surgical scenario in LAPC. This situation may be associated with complete tumor occlusion of the PV/SMV or in relation to a paraneoplastic procoagulant disorder. The technique of "venous bypass graft first" approach was recently described to avoid major bleeding complications, intestine congestion, or liver perfusion disorders . The procedure includes the identification of the SMV or one of its branches (in the mesenteric root) as well as the PV or vascular tributaries to the liver (pericholedochal varices) in the hepatoduodenal ligament, adjacent to the liver hilum. A jump graft between these vascular structures can be used for this purpose (autologous, cadaveric bank graft, or synthetic prothesis) . This surgical strategy offers continuous portal blood flow to the liver during the resection and reconstruction phase of the operation. Bachellier et al. suggested that venous shunt seemed necessary only for patients with intra-abdominal collateral circulation (types C and D), which maintains the portal inflow by filling the PV downstream to the venous stenosis or occlusion. 6. Arterial Resection Although recent meta-analyses concluded that pancreatectomy with AR were associated with increased morbidity and mortality in comparison to non-AR pancreatectomies , the introduction of new chemotherapy schemes (FOLFIRINOX or gemcitabine + nabpaclitaxel), have changed the paradigm of the treatment approach for LAPC in selected patients with arterial compromise (especially in young patients if a R0 situation can be achieved) . Recently, Tee et al. published the largest single-institution series specifically addressing indications, outcomes, and perioperative risk factors in pancreatectomy with AR. Despite having described a significant improvement in 90 day mortality over time, morbidity and the use of hospital resources remain unchanged. The most significant predictor of worse outcomes is post-pancreatectomy hemorrhage (PPH). Graft reconstruction and pancreatic fistula were also associated with increased major morbidity in their experience. It is highly recommended such cases be performed by surgeons with the specific anatomic comprehension and skillsets required not only to perform such complex resections, but also with the necessary institutional expertise and immediate availability of interventional radiology, complex endoscopy, and adequate intensive care facilities. On the other hand, PPH after pancreatectomy with AR may be a logical consequence of postoperative pancreatic fistula. To eliminate this risk, total pancreatectomy has been suggested . However, a recent study found no protective effect of total pancreatectomy on its outcomes . From the anatomical and technical point of view, there is a great difference between AR of the SMA, with respect to the CT and the hepatic artery. For example, after resection of the CT, the blood supply to the liver and pancreas head via the common hepatic artery relies on retrograde arterial perfusion of the pancreatoduodenal arcades and the gastroduodenal artery with the blood flow coming from the SMA. To improve collateral flow tributaries and reduce postoperative liver ischemia, we applied preoperative common hepatic artery embolization . We had previously described some surgical strategies for restoring liver arterial perfusion in pancreatic resections . In case of short-segment resection of the hepatic artery or SMA, reconstruction can occasionally be performed by direct end-to-end anastomosis. However, most cases of AR include longer vascular defects and complex surgical strategies to restore arterial perfusion, with any type of graft interposition or transposition . Recently, the technique of "arterial divestment" opens a great possibility for a periarterial neurolymphatic tissues dissection without the need of AR and respective reconstruction, with the risks that this implies. Arterial clearance is achieved by placing it in a plane between the uninvolved arterial wall and the tumor tissue of the affected arterial segment . The dissection plane should be placed between the periarterial nerve plexus and the arterial adventitia . 7. Conclusions In this review, recent surgical and technical aspects in LAPC were discussed, including extended pancreatic resections, PMV resections and their respective forms of vascular reconstruction, arterial resection, or alternatively arterial divestment. Furthermore, through multimodal treatment systems and appropriate surgical resection techniques, the long-term outcome after extended pancreatectomies can be similar to standard resections and considerably better than palliative care, despite the fact that we do not have the sufficient level of scientific evidence. Author Contributions Conceptualization, M.d.S. and O.M.M.; methodology, M.d.S., R.S.C., E.d.S., J.P. and O.M.M.; writing--original draft preparation, M.d.S.; writing--review and editing, M.d.S., R.S.C., E.d.S., J.P. and O.M.M. and supervision, J.P. and O.M.M. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest None of the authors of this manuscript have any direct or indirect commercial financial incentive associated with the publication of this paper. Figure 1 A 67 year old female patient with jaundice and abdominal pain. Endoscopic ultrasound biopsy confirmed poorly differentiated PDAC and a biliary stent was placed (asterisk). MDCT shows expansive pancreatic formation located in the cephalic portion, with poorly defined limits, measuring approximately 54 x 32 mm (A). Exophytic tumor (T), encompassing the SMA and distal branches (white arrow) and the spleno-mesenteric-portal confluence, extending towards the superior mesenteric vein (encasement) (B,C). Cephalically it extends towards the celiac trunk, encompassing its terminal branches (black arrow) (D). Figure 2 In extensive Kocher maneuver in combination with the Cattell-Braasch mobilizations of the cecum, right colon, right colonic flexure, and the root of the small bowel, together with the Treitz ligament, an adequate exposure of the entire infrahepatic vena cava (IVC), aorta, and the left renal vein (white arrow) is achieved. Figure 3 Identification of the superior mesenteric vessels (the blue arrow shows the superior mesenteric artery) is performed at the root of the mesentery below the transverse mesocolon to the origin from the aorta. The middle colic artery is detached at its origin from the SMA in this manner (white arrow), and the tumor-infiltrated section of the transverse mesocolon is resected to remain with the specimen. Figure 4 (A) Radical antegrade modular pancreatosplenectomy (RAMPS) proceeds in a right-to-left antegrade manner, with early parenchymal transection at the neck of the pancreas, close to the gastroduodenal artery (blue arrow) and early control of the splenic vessels (in its origin) (white arrow). The black arrow marks the common hepatic artery, and the asterisk shows a partial venous excision spleno-mesenteric confluence with direct closure (venorrhaphy). (B) Posterior RAMPS. The posterior magnitude of dissection was behind the left adrenal gland, including the Gerota fascia and the fat tissue around the left kidney. The left renal artery is shown with white arrow. Blue arrow shows the pancreas stump. Black arrow, superior mesenteric vein. Figure 5 The TRIANGLE operation (blue triangle zone) is a proper approach to achieve a complete and radical removal of the tumor and associated lymphatic or perineural extension along a region defined anatomically by the origins of the celiac trunk (white arrow), the superior mesenteric artery (SMA) (blue arrow), the portal vein (anteriorly), and superior mesenteric vein (SMV). Figure 6 (A) Autologous parietal peritoneum was harvested from the right hypochondrium. (B) Type 2 vein reconstruction, using falciform ligament patch over the spleno-portal junction (white circle). The asterisk shows the distal pancreatic stump. The blue arrow shows the superior mesenteric artery. PV, portal vein. SMV, superior mesenteric vein. Figure 7 Type 3: segmental superior mesenteric vein resection (white arrow) with primary veno-venous anastomosis. The blue arrow shows the splenic vein. The asterisk, the distal pancreatic stump. SMA, superior mesenteric artery. Figure 8 Type 4: segmental resection with interposed venous conduit. The spleno-portal confluent was complete resected. The blue arrow shows the superior mesenteric vein. The blue lines mark the cadaveric iliac vein interposed conduit of 6.5 cm long. SMA, superior mesenteric artery, which was clamped for 25 min to perform the venous anastomosis and avoid intestinal congestion. Figure 9 Venous jump graft technique. (A) Identification of the superior mesenteric vein (white asterisk) at the root of the mesentery (blue arrow). (B) Anastomosis between the superior mesenteric vein (blue arrow) and cadaveric iliac venous bank graft (black asterisk). The white arrow marks the distal segment that will be anastomosed with the portal vein or a collateral vessel. The jump graft is accessed through the transverse mesocolon (black arrow). Figure 10 Splenic artery transposition technique with respective anastomosis with proper hepatic artery. (A) The right angle shows the splenic artery being dissected from its origin in the celiac trunk (blue arrow) distally (white arrow). The black arrow shows proper hepatic artery (bulldog clamp). (B) Section towards the distal portion of the splenic artery. The white arrow shows the distal end of the splenic artery that will be ligated. The blue arrow, the portion of the splenic artery that will be anastomosed to the proper hepatic artery (asterisk). The black arrow is marking the 180deg rotation that the splenic artery will undergo to achieve a tension-free anastomosis. (C) Anastomosis between the splenic artery and proper hepatic artery. The white arrow is marking the clamp in the proximal segment of the splenic artery. The black arrow shows the 4 cm segment of the splenic artery that was rotated 180deg, with the respective anastomosis to the proper hepatic artery (blue arrow). Figure 11 (A) Arterial divestment, is achieved by placing it in a plane between the uninvolved arterial wall and the tumor tissue of the affected arterial segment. The dissection plane should be placed between the periarterial nerve plexus and the arterial adventitia. We usually perform this maneuver with cold scissors to avoid thermal damage to the arterial wall, as can be seen in the image. The white arrow shows the limit between the tumor and the superior mesenteric artery (SMA) wall. Black arrow, retracted superior mesenteric vein (SMV) (B) The white arrow is showing the tunica adventitia of the superior mesenteric artery, which has then been removed distally, to give a tumor margin: the tunica media of the superior mesenteric artery can be seen at the level of the forceps and marked with a blue arrow. Pancreas stump (black arrow). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000507 | Despite recent advances in multiple myeloma (MM), the incorporation of novel agents and measurable residual disease (MRD) monitoring in low-income countries remains a challenge. Although lenalidomide maintenance (M-Len) after autologous stem cell transplantation (ASCT) has been associated with improved outcomes and MRD has refined the prognosis of complete response (CR) cases, until now, there have been no data on the benefits of these approaches in Latin America. Here, we evaluate the benefits of M-Len and MRD using next-generation flow cytometry (NGF-MRD) at Day + 100 post-ASCT (n = 53). After ASCT, responses were evaluated based on the International Myeloma Working Group criteria and NGF-MRD. MRD was positive in 60% of patients with a median progression-free survival (PFS) of 31 months vs. not reached (NR) for MRD-negative cases (p = 0.05). The patients who received M-Len continuously had a significantly better PFS and overall survival (OS) than those without M-Len (median PFS: NR vs. 29 months, p = 0.007), with progression in 11% vs. 54% of cases after a median follow-up of 34 months, respectively. In a multivariate analysis, MRD status and M-Len therapy emerged as independent predictors of PFS (median PFS of M-Len/. no M-Len/MRD+ of NR vs. 35 months, respectively; p = 0.01). In summary, M-Len was associated with improved survival outcomes in our real-world MM cohort in Brazil, with MRD emerging as a useful reproducible tool to identify patients at an earlier risk of relapse. The inequity in drug access remains a hurdle in countries with financial constraints, with a negative impact on MM survival. multiple myeloma measurable residual disease lenalidomide drug access autologous transplant maintenance real-world study Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior CAPES/PROEX88887.335769/2019-00 This work was supported by from Coordenacao de Aperfeicomento de Pessoal de Nivel Superior--Brazil (CAPES) Finance code 001-8888.331795/2010-01; Programa de Oncobiologia 001/2017 and 004/2017; Centro Investigacion Biomedica em Red--Cancer (CIBERONC code CB//00400) of Instituto de Salud Carlos III, Ministry of Science and Innovation (Madrid, Spain), number CB16/12/00400; The International Myeloma Foundation-Black Swan Research Initiative (Los Angeles, CA) (Grant: LSHB-CT-2006-018708). A.B.S.S. was supported by a grant from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior CAPES/PROEX, number: 88887.688096/2022-00. R.M.P. was supported by a grant from the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES/DGPU), number: 000281/2016-06 and CAPES/PROEX 641/2018, Brazil, and Fundacao de Amparo a Pesquisa do Estado do Rio de Janeiro of Brazil (FAPERJ), number: E01/200/537/2018. E.S.B. was supported by a grant from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior CAPES/PROEX, number: 88887.335769/2019-00 and Fundacao de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), number: E-26/200.192/2020, Brazil. pmc1. Introduction Recent advances in the treatment of multiple myeloma (MM) based on the combination of new drugs and autologous stem cell transplantation (ASCT) have led to improved response rates and survival outcomes . For instance, bortezomib associated with lenalidomide (Len) and steroids for induction therapy, followed by continuous Len maintenance (M-Len), is currently recommended as a standard of care in MM . In different studies, this strategy achieved higher rates of a very good partial response (VGPR)/complete response (CR) associated with a lower percentage of measurable residual disease (MRD)-positive (MRD+) cases, and it achieved higher survival rates, with an acceptable toxicity profile . Although the achievement of CR has traditionally been pursued as the first goal of MM treatment, it has been repeatedly demonstrated that it is a suboptimal surrogate marker of patient progression-free survival (PFS) and overall survival (OS). Thus, CR is associated with heterogeneous outcomes, hiding a large proportion of patients that will not achieve long-term disease control and that will relapse shortly after therapy . In this regard, highly sensitive MRD monitoring has become critical to improving the assessment of the response to therapy in MM, particularly among patients that reach CR or VGPR . Indeed, a large number of studies based on different techniques and distinct sensitivity thresholds, including two meta-analyses, have shown that MRD is among the most powerful independent predictors of survival in MM , with the persistence of residual clonal plasma cells (cPCs) being consistently associated with an inferior PFS . In 2016, the International Myeloma Working Group (IMWG) established new response criteria for MM based on the bone marrow (BM) MRD status, evaluated by using eight-color next-generation flow cytometry (NGF) or next-generation sequencing (NGS) reference techniques capable of achieving a sensitivity of <10-5 . Due to the economic constraints in Brazil, as well as in other Latin American countries (LATAMC), access to new drugs and all standard routine MM diagnostic and follow-up examinations, including serum electrophoresis, immunofixation, free light-chain determinations and NGF or NGS MRD measurements, is still lacking and/or restricted to reference centers . In turn, the co-existence of dual (i.e., public and private) healthcare systems supported locally by different health insurances leads to the use of unique combinations of first-line therapeutic regimens and laboratory diagnostic and monitoring assays in MM, depending on the specific healthcare system that the patient has access to. As an example of such treatment scenarios in Brazil, the majority of patients eligible for MM transplant in public institutions have access to induction regimens with cyclophosphamide/thalidomide/dexamethasone (CTD), whereas in private centers, bortezomib/cyclophosphamide/dexamethasone (VCD) are preferentially used . Until recently, most patients received thalidomide or no maintenance after ASCT; however, since Len approval, this drug has become available to patients enrolled in the private (but not the public) healthcare system in Brazil. Despite all the above, at present, there are no data concerning the potential benefit of introducing M-Len into our current practice or its impact in real-world patients with MM, except for the survival benefits already demonstrated in the pivotal randomized clinical trials used for the approval of this drug . In addition, so far, no data from LATAMC have been reported in which NGF-MRD techniques have been used in addition to conventional response criteria in order to compare local treatments administered in different healthcare conditions/systems within the same country. In this study, we investigate the impact of continuous M-Len therapy after ASCT and MRD monitoring by carrying out NGF-MRD at Day + 100 after ASCT and identifying subgroups of patients with distinct outcomes among a series of 53 real-world patients with MM treated outside clinical trials in Brazil. 2. Material and Methods Patients and samples: Peripheral blood (PB), BM and 24 h urine samples were collected one hundred days after ASCT (Day + 100) from 53 patients with MM (26 males and 27 females, with a median age of 58 years, ranging from 40 to 70 years), diagnosed according to the IMWG criteria (Table 1). The patients treated in the Brazilian public healthcare system received an MM-oriented treatment fully funded by the government , which consisted of six cycles of induction therapy--cyclophosphamide, 300 mg/m2; dexamethasone, 40 mg (Day 1, Day 8, Day 15, Day 22); and thalidomide, 100 mg/day (CTD)--followed by ASCT and post-transplant consolidation with two additional cycles of CTD and maintenance with thalidomide (100 mg/day for 10 months), except for patients who suffered from neuropathy. The patients enrolled in the private healthcare system were supported by health insurance companies, with most having access to newly approved therapies and exams, generally restricted to individuals above poverty levels or higher-income employees . This latter group received 4 cycles of bortezomib (1.3 mg/m2 SC), cyclophosphamide (300 mg/m2) and dexamethasone (40 mg) on Day 1, Day 8, Day 15 and Day 22 (VCD), followed by ASCT and 2 additional consolidation cycles of VCD, followed by M-Len until progression. In both groups, ASCT was performed with PB hematopoietic stem cells mobilized with a granulocyte-colony-stimulating factor (G-CSF). The conditioning regimen consisted of melphalan 200 mg/m2 (or 140 mg/m2 in patients with renal insufficiency). None of the patients received bortezomib maintenance. Response assessment: To assess the conventional response to therapy vs. disease progression, all patients from both treatment groups were uniformly evaluated using the IMWG response criteria, based on electrophoresis, immunofixation (IF) in serum and urine and serum free light-chain (sFLC) measurements . CR was defined as the absence of an M-component isotype using IF and <5% PC in BM, and stringent CR (sCR) was defined as the case in which the sFLC ratio values were within the normal range (0.26 to 1.65 or 0.37 to 3.1 in patients who showed renal failure). The same criteria were applied when the IF results were associated with a discordant positive test (vs. the original M-component isotype) during follow-up (oligoclonal bands) . Minimal Residual Disease (MRD) assessment: An NGF-MRD assay was performed on BM aspiration samples (collected in tubes containing EDTA as an anticoagulant) collected from all patients with MM included in the study. For the MRD evaluation, the EuroFlow bulk-lysis and cell surface membrane and cytoplasmic lyse-and-stain standard operating procedures (SOPs) were used, in combination with a two-tube 8-color (10-antibody reagent) EuroFlow NGF-MRD antibody panel (tube 1: CD138 CD27 CD38 CD56 CD45 CD19 CD117 CD81; tube 2: CD138 CD27 CD38 CD56 CD45 CD19 CyIgk CyIgl) . For each BM sample, >=107 stained cells were measured in a FACSCanto II flow cytometer--Becton Dickinson (BD) Biosciences, San Jose, CA--using FACS Diva software (BD). For a data analysis, Infinicyt software (version 2.0, Cytognos SL, Salamanca, Spain) was used. The limit of detection (LOD) of the NGF-MRD method was calculated as 20 cPC/total number of viable cells measured x 100, and the limit of quantification (LOQ) was calculated as 50 cPC/total number of viable cells x 100 . The samples were considered hemodiluted if mast cells were <=0.002% of the total BM cells, as previously described . Statistical analyses: For all statistical analyses, SPSS software (version 21; IBM. Chicago, IL, USA) was used. The nonparametric Mann-Whitney U test was used to establish the statistical significance of the differences observed among groups for unpaired continuous variables. The chi-square test was applied for comparisons between two groups for categorical variables. The Kaplan-Meier method was used to plot survival curves, and the (two-sided) log-rank test was employed to compare PFS and OS curves (both for all patients with MM and for VGPR and CR cases separately). PFS and OS were defined as the time lapse from diagnosis to either disease progression or death by any cause or to the last follow-up visit. For multivariate analyses, the Cox regression model was used to identify variables with an independent prognostic impact on PFS. p-values < 0.05 were considered statistically significant. Ethics: All patients provided written informed consent prior to entering the study, after the study had been approved by the institutional review board. 3. Results Patient characteristics and response to therapy: Overall, 53 patients with MM-- with a median age of 58 years (range: 40-70 years; 51% women)--were studied. According to the Durie-Salmon (DS) staging system, most patients (n = 36, 68%) were in DS stage III, while their distribution according to the International Score System (ISS) was as follows: stage I, 21 patients (40%); stage II, 17 patients (32%); and stage III, 15 patients (28%). The clinical and demographic features of the patients with MM, stratified according to maintenance therapy, are shown in Table 1, while in Supplementary Table S1, the same features are shown for the whole cohort without stratification. As displayed in Supplementary Table S2, no significant differences were found between the clinical characteristics at diagnosis of the patients treated in the public health system versus those treated in the private health system, except for a greater predominance of more advanced higher ISS stages in the patients from the public health system (p = 0.03). At Day + 100 after ASCT, more than half of the patients were in CR (27/53, 51%), of whom a major fraction had also reached sCR (21/53, 40%). In the remaining cases, 21/53 (40%) were in VGPR and 5/53 (9%) in PR. As induction treatment, 27/53 patients (51%) had received CTD, and 26/53 (49%) received VCD, with CR/sCR rates of 48% (13/27) vs. 54% (14/26), respectively (p = 0.44). In turn, sCR was achieved in 37% (10/27) of patients treated with CTD vs. 42% (11/26) of those treated with VCD (p = 0.44). In addition, PR (7%, 2/27 vs. 12%, 3/26; p = 0.66) and VGPR (45%, 12/27 vs. 34%, 9/26; p = 0.57) were achieved in similar percentages of cases among patients who had received CTD vs. VCD, respectively. Minimal residual disease status at Day + 100 determined by using next-generation flow cytometry: NGF was successfully performed in all 53 patients, and none of the BM samples were inadequate or insufficient for analyses. Flow cytometry studies reached very high sensitivity levels, with a median LOD and LOQ systematically <10-5--a median of 0.0002% (range: 0.0001-0.0015%) and of 0.0006% (range: 0.0004-0.0037%), respectively. Out of all 53 BM samples investigated, 32 (60%) were MRD+ and 21 (40%) had undetectable MRD. In 10/53 samples (19%), low mast cell counts suggesting BM hemodilution were observed, which included 4/21 (19%) MRD-negative (MRD-) samples and 6/32 (19%) MRD+ specimens (p = 0.62) . A total of 31/53 (58%) cases showed concordant results between the serologic protein measurement techniques (IF and sFLC) and BM MRD, of which 16/31 (51%) were found to be positive using both methods, and 15/31 (48%) were negative. Among the (6/53, 11.3%), some had a positive IF (4/53, 7.5%) or sFLC (2/53, 3.8%); none of these 6 discrepant cases had IF+ and sFLC+ simultaneously. Conversely, among the patients who were MRD+ (16/53, 33%), some had a negative IF (4/53, 7.5%) or sFLC (4/53, 7.5%) or both (8/53, 15.1%), as shown in Supplementary Tables S3 and S4. Impact of the MRD status and lenalidomide maintenance therapy on patient outcome: After a median follow-up of 34 months from diagnosis, disease progression occurred in 21/53 (40%) patients, of whom 5/21 (24%) were MRD-, and 16/32 (50%) were MRD+ cases (p = 0.05), with the median PFS rates post-transplant not reached (NR) vs. 31 months, respectively ([HR 2.62 (95% CI: 0.94-7.29)], p = 0.05). Furthermore, 2/5 cases in the group that showed disease progression had an isolated extramedullary relapse, and in 1/5, the BM sample showed signs of being a hemodiluted sample. The median OS was not reached for any of the two MRD+ patient groups (NR vs. NR; p = 0.31) . Similar results were observed when we excluded patients with MM that did not reach VGPR or CR (5/53): disease progression was found in 19/48 (40%) of these latter patients, of whom 5/20 (25%) were 14/28 (50%) were MRD+, with the median PFS rates not reached (NR) vs. 34 months, respectively (p = 0.08). The median OS was not reached for either group (p = 0.29). M-Len therapy after ASCT was used in 18/53 (30%) MM cases, with a median time of therapy of 20.5 months. In this group, only 2/18 patients (11%) experienced disease progression compared to the 19/35 who did not use M-Len (54%), with median PFS rates of NR vs. 29 months, respectively (p = 0.007) [HR 5.78 (95% CI: 1.34-24.95)]. Of note, no deaths occurred in the group that received M-Len, while 11/35 (31%) of the patients who did not receive M-Len died, leading to significantly different median OS rates for these two groups (p = 0.009) . Among the patients with MM who did not receive M-Len, 15/35 (43%) used thalidomide maintenance, and 20/35 (57%) did not receive maintenance. Notoriously, all patients who were showed disease progression did not receive M-Len. PFS and OS analyses showed no significant differences in survival between these two MM patient subgroups (a median PFS of 42 vs. 38 months, p = 0.44, respectively, and a median OS of 37 vs. 31 months p = 0.11, respectively). More detailed data on the demographics and clinical characteristics of the patients included in the M-Len and no M-Len groups are shown in Table 1. Of note, the patients who had received M-Len had similar MRD+ rates to those who did not receive M-Len: 61% (11/18 patients) vs. 60% (21/35 patients) of MRD+ cases (p = 0.58). In spite of this, while none of the patients using M-Len who were shown disease progression, among the patients who were did not receive M-Len, disease progression was found in 43% of cases (p = 0.13). Furthermore, among the MRD+ cases, significantly different median PFS rates were found depending on whether the patient had used M-Len (NR vs. 35 months, respectively; p = 0.011). This also translated into an improved median OS among the patients who underwent M-Len vs. those who did not (NR vs. 35 months, respectively; p = 0.018), with no events among the former group of patients . Univariate and multivariate analyses of prognostic factors for PFS and OS: A univariate analysis of prognostic factors performed based on well-established prognostic factors (age, DS and ISS stages, CR status, the type of induction treatment, MRD status at Day + 100 and the use of M-Len therapy) revealed that only the MRD status at Day + 100 post-ASCT and the use of M-Len therapy had an impact on the PFS of our patients with MM. . MRD+ cases showed median PFS rates of NR vs. 31 months [HR 2.62 (95% CI: 0.94-7.29); p = 0.049], while patients treated with M-Len vs. those who had no M-Len displayed median PFS rates of NR vs. 29 months [HR 5.78 (95% CI: 1.34-24.95); p = 0.003], respectively. A subsequent multivariate analysis showed that both variables (MRD status and M-Len) were independent prognostic factors for PFS in MM, with HRs of 3.37 ((95% CI: 1.19-9.57); p = 0.014) and 7.05 ((95% CI: 1.6-30.72); p = 0.001) for patients who were MRD+ and those who did not receive M-Len, respectively. When we grouped our patients according to both variables, the median PFS rates of NR, NR, 44 months and 35 months were found for MRD-/M-Len+, MRD+/M-Len+, MRD-/M- MRD+/M-, respectively. This was associated with adverse HRs (95% confidence interval) of 2.98 (0.58-15.4) (p = 0.19) and 9.22 (2.06-41.2) (p = 0.004) for cases that did not receive M-Len and had an and patients who were MRD+, respectively (Table 2). 4. Discussion In recent decades, the treatment of MM has dramatically changed due to the introduction of novel agents in combination with new drug combinations and therapeutic schemes , frequently led by the BM MRD status. This was also associated with the improved monitoring of therapy based on newly developed highly sensitive MRD techniques . However, the incorporation of the new drugs/treatment strategies and MRD technologies by low-middle income countries has been challenging and frequently delayed, particularly in public healthcare systems . In addition, most data reported in the literature have been generated in the settings of national protocols or industry-sponsored clinical trials, resulting in limited information about the value of novel therapies and MRD monitoring technologies in real-world patient care, particularly in countries with drug access constraints. Here, we investigated the benefits of new maintenance therapies (M-Len) and highly sensitive MRD measurements in a real-world patient cohort treated in two different healthcare environments in Brazil. Overall, our findings in a real-world cohort of patients with MM confirm previous results reported in the literature based on clinical trial settings regarding the prognostic benefits on the patient outcome of both the therapy administered (i.e., M-Len) and the BM MRD status achieved with it . To the best of our knowledge, this is the first report using NGF for the MRD monitoring of therapy in MM in Latin America and one of the first real-world patient studies using such a treatment monitoring strategy . In 2019, Terpos et al. first reported the monitoring of MRD using NGF as an independent prognostic factor in real-world patients with MM from Greece, outside of clinical trials . Here, we confirm these findings and extend them by also demonstrating a significant benefit in terms of PFS and OS for patients that had access to M-Len therapy compared to those that did not have access to this drug in the ASCT settings, highlighting the need for its fast approval by the public healthcare system. Of note, the few patients treated in the private healthcare system that did not use M-Len due to a lack of approval by the insurance company showed similar results to the patients from the public healthcare system, with a significantly shorter PFS (data not shown). Even though most patients in our cohort had been diagnosed at (more) advanced stages of the disease compared with other cohorts , still, half of them reached CR at Day + 100 following ASCT, in line with previous findings . Despite this, the response did not (significantly) depend on whether they had received VCD or CTD as induction therapy or according to whether they had access to proteasome inhibitors, since only a tendency towards a better outcome among the latter group was observed, in line with other previous reports . Interestingly, in our cohort, ISS did not emerge as a relevant prognostic factor for PFS in the univariate analysis, which could be related to the relatively low number of patients in our study; the use of different maintenance regimens in different patients; and the high frequency of stage II/III cases, particularly among patients with MM treated in the public healthcare system. Extending our small cohort with a larger number of patients, preferably in a multicentric setting, would help to confirm the benefit of the inclusion of PI in the regimens used for induction therapy in our real-world settings and to confirm the prognostic impact of ISS. Regarding the NGF-MRD technique, here, we showed that the implementation of standard EuroFlow procedures and antibody panels in our environment in Brazil provided results highly comparable to those reported by other laboratories . This included an easily reachable sensitivity threshold of 2 x 10-6 (far beyond the IMWG Flow-MRD threshold criteria of 10-5) in virtually every MM case, based on the measurement of very high numbers of cells as recommended by EuroFlow (i.e., >=107 cells) . From a clinical point of view, MRD undetected by NGF was associated with a significantly better outcome, independently of therapy and other well-established prognostic factors. Furthermore, a similar impact of MRD on PFS and OS was observed when we restricted our analyses to VGPR and CR cases, although the differences did not reach statistical significance, probably due to the small number of patients. Overall, these results are fully in line with previous findings in the settings of clinical trials, as well as in the limited real-world patient series reported in the literature in which MRD was investigated by using NGF in the BM of treated patients with MM . The increased sensitivity of NGF-MRD compared to that of the consensus 10-5 IMWG threshold might be associated with an even higher probability of longer-term disease control, as pointed out by other authors who highlighted the benefit of achieving MRD negativity below the 10-6 vs. <10-5 thresholds, as reflected by a lower risk of disease progression of patients below vs. above the former threshold . In turn, this higher sensitivity might contribute to explaining the relatively high rate of discordant results observed in our study with serum protein measurements by, e.g., IF and sFLC, with a greater fraction of NGF-MRD+ but . Despite this, it should be noted that, still, there was a fraction of patients who tested positive using IF or sFLC while NGF-MRD-. This might be due to the persistence of the monoclonal protein in serum, despite the clearance of cPCs in BM, as suggested previously . In the few that relapsed, conducting complementary PET-CT imaging to search for extramedullary disease (EMD) (which could not be systematically performed here due to financial constraints) might help to explain our apparently discordant findings, at least in a subset of patients. Such discrepant could be explained by a series of factors, such as a lack of M-Len maintenance, extramedullary relapse without BM involvement or sample hemodilution . Although we do not have an explanation for two out of five patients who relapsed despite being Day + 100, the longer time interval between the MRD assessment and relapse and/or the possibility for a patchy distribution of clonal PCs in the BM at the time of the MRD assessment might also contribute to explaining such apparent discrepancies. In such cases, these false negative MRD results in BM could be mitigated via sequential MRD analyses and/or M-Len therapy. In addition to the small cohort, our study has two other important limitations: (1) the heterogeneity of the treatment induction regimens administered to the patients, which reflects real life conditions, and (2) the evaluation of MRD at a single time point (Day + 100 after ASCT). In this regard, it has previously been shown that some patients who tested MRD+ might convert to maintenance therapy with lenalidomide, while others may lose their MRD-negative status, with such kinetics showing (a favorable vs. unfavorable) an impact on patient outcome among those who initially tested as being MRD+ and MRD-, respectively . Thus, in future validation MRD studies, a sequential evaluation in larger and more homogeneous patient cohorts is recommended. Despite all the above limitations of our study, the MRD evaluation carried out using NGF at Day + 100 following ASCT emerged as a powerful prognostic factor, independently of other prognostic factors, including the therapeutic regimen administered. Altogether, these findings support the use of NGF-MRD for the re-assessment of patient risk after therapy (i.e., ASCT) for an improved therapeutic management of MM, as well as in our real-world patient settings. In addition to MRD, M-Len also emerged as an independent predictor of improved patient outcome. Four randomized studies examined lenalidomide maintenance versus placebo or no maintenance. A meta-analysis conducted on three of these studies and the Myeloma XI trial that was reported separately all provide evidence for a benefit of M-Len . However, in Latin America in general and in Brazil in particular, the incorporation of this drug into the armamentarium of anti-myeloma therapies has been delayed (i.e., Brazil's recent approval). Because of this, the great majority of patients treated in the public healthcare system environment in Brazil had no access to the drug. Consequently, they did not receive maintenance therapy or just had a short course of thalidomide therapy (based on the gratuity of this latter drug) with some benefit on PFS, but at the expense of treatment discontinuation in cases of neuropathy . Here, we report for the first time on the use of M-Len post-ASCT in a cohort of patients treated in the private healthcare insurance system in Brazil. Despite the limited number of patients, our results clearly show a benefit of M-Len in both the PFS and OS of patients with MM who had received ASCT, independently of their MRD status. These results support the well-known immunomodulatory effect of the maintained administration of lenalidomide in sustaining, or even deepening, the response and delaying relapse in MM . Of note, such benefit was independent of the type of induction therapy received by the patients (VCD or CTD), and it was particularly significant among patients who were still MRD+ after transplantation. These results are in line with previous findings suggesting that omitting this drug in patients with standard-risk cytogenetics makes them have similar outcomes to patients with high-risk myeloma . To guarantee essential anti-cancer drug access in providing the best standard of care therapy to patients is a well-known universal concern, and it still remains a challenge in practice in the public healthcare systems in Brazil and Latin America. This is mainly due to the higher costs of novel agents often used in combinations and/or administered continuously for long periods of time . In this study, we compared for the first time the outcomes of two distinct patient cohorts recruited and treated in parallel with the corresponding standard of care therapies in the public (CTD-ASCT-CTD +/- thalidomide) vs. private insurance (VCD-ASCT-Len) healthcare system environments. Our results show a significant advantage (with regard to both PFS and OS) for patients with supplementary health insurance. In these settings, our data indicate that, in our real-world cohort of patients with MM, the different triplets used as induction therapy prior to ASCT had a relatively limited impact on patient outcome compared to M-Len, with the latter emerging as the strongest independent predictor of patient outcome. Moreover, the combination of M-Len with undetected MRD at Day + 100 following ASCT identified a subset of patients with MM with very good (medium-term) outcomes, particularly when compared to patients who were MRD+, did not receive M-Len and had a significantly higher risk of (early) relapse (median PFS of 16 months). Such PFS was less than that described in clinical trials or real-world studies with VCD or lenalidomide, bortezomib and dexamethasone (RVD) as induction therapy (50 to 65 months) . Overall, the relevance of our preliminary data is of utmost importance, since it is estimated that 70% of patients with MM in Brazil to up to 90% in LATAMC are covered by the national public healthcare assistance, pointing out the need for the urgent implementation of policies and measures that will guarantee the human basic principles and rights of equity . In this regard, it should be noted that the national drug agencies have already approved the use of both bortezomib and lenalidomide for MM. Therefore, broader access to these (and also other new) drugs requires awareness and active efforts and adoption policies by local public health boards and governmental institutions, in collaboration with national and international medical (i.e., hematology) societies, including guidelines based on the use of drugs included in the WHO list of essential medicines . Thus, negotiation among governments, insurance companies and the pharmaceutical industry, with the possibility for the local production of the drug or biosimilars, is a relevant issue to be urgently addressed for an adequate balance between access to new essential drugs and limited use and, therefore, the benefit of expensive treatments that more fragile economies cannot afford . 5. Conclusions In real-world patients with MM treated in Brazil, the introduction of M-Len post-ASCT is associated with significantly improved survival outcomes, with MRD monitoring via NGF emerging in these settings as a robust and powerful tool to identify subsets of patients with different (higher vs. lower) risks of early relapse and for anticipated treatment decisions. In addition, our data show that the inequity in drug access still remains a hurdle in countries with economic constraints, particularly in the public healthcare system, which has a negative impact on the survival of patients with MM. Acknowledgments We would like to acknowledge the EuroFlow consortium for its important contribution to this study and for providing support. We thank the Binding site company for supplying Freelite chain kits. Supplementary Materials The following supporting information can be downloaded at Supplementary Table S1: Demographics and baseline clinical and laboratory characteristics of patients with multiple myeloma included in this study (n = 53); Supplementary Table S2: Distribution of clinical features and treatment regimens of patients with multiple myeloma grouped according to the healthcare (public vs. private) environment in which they were treated; Supplementary Table S3: Concordance among MRD status and serologic protein measurements (free light-chain and immunofixation techniques) in patients with multiple myeloma studied at Day + 100 after ASCT (n = 53); Supplementary Table S4: Data on the disease status obtained for each individual patient with multiple myeloma included in this study (n = 53) by using next-generation flow-MRD, serum-free light-chain and immunofixation techniques. Click here for additional data file. Author Contributions A.B.d.S.S., R.M.P. and E.d.S.B. performed the research. A.B.d.S.S., R.M.P., R.J.P.M., A.M., A.O. and E.S.C. designed the study. A.B.d.S.S., R.M.P., H.d.S.D. and R.J.P.M. provided patient data and samples. A.B.d.S.S., R.M.P., E.d.S.B., L.S.-F., J.F.-M. and G.P. collected and assembled the data. A.B.d.S.S., R.M.P., R.J.P.M., M.G.P.L. and E.S.C. analyzed and interpreted the data. A.B.d.S.S., R.M.P., R.J.P.M., A.M., A.O. and E.S.C. wrote the paper. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved (on the 27 May 2017) by the Ethics Committee of the University Hospital Clementino Fraga Filho, Federal University of Rio de Janeiro (UFRJ), Brazil (protocol code CAAE number 63221816.2.0000.5257). Informed Consent Statement Informed consent was obtained from all subjects involved in this study. Data Availability Statement The data present in this study are available upon request from the corresponding author. Conflicts of Interest A.O. is co-chair of the EuroFlow foundation and inventor of the patent "Methods reagents, and kit for detecting minimal residual disease" (PCT/NL2013/050420, filing date 14 June 2013), owned by the EuroFlow Consortium, which receives royalties from licensed patents that are collectively owned by the participants of the EuroFlow Foundation. These royalties are exclusively used for the continuation of the EuroFlow scientific collaboration and the sustainability of the EuroFlow consortium. In addition, A.O. reports an Educational and Laboratory Services Agreement from BD Biosciences (San Jose, CA, USA) and a Scientific Advisor Agreement with Cytognos/BD Biosciences; all related fees and honoraria go to USAL. A.M. reports consultancy on Janssen, Takeda, Amgen, BMS--Celgene, Sanofi and Novartis companies and receives honoraria from Janssen, Takeda, Amgen, BMS--Celgene and Sanofi companies. R.J.P.M. reports consultancy on Janssen, Takeda, Amgen, BMS--Celgene and Sanofi companies and receives honoraria from Janssen, Takeda, Amgen, BMS--Celgene and Sanofi companies. All other authors declare no conflicts of interest related to the present work. Figure 1 Illustrative example of the gating strategy used for the identification of residual clonal/aberrant plasma cells by next-generation flow. Panels show an illustrative example of a patient with multiple myeloma (MM) with minimal residual disease (MRD)-positive bone marrow (BM), in which clonal PCs (cPCs) depicted in red co-exist with a great majority of normal plasma cells (nPCs) depicted as blue dots; PC populations were identified as CD38hi and CD138+ cells (panel C); other BM cells are shown as gray dots in panels (A,B). Panel (A) shows the light scatter pattern of PCs, in which cPCs show abnormally higher FSC and SSC values than nPCs. As shown in the following panels, cPCs had aberrantly lower expressions of CD38, CD45 and CD27 than nPCs (panels B,G). In turn, CD19 and CD81 were completely lost in cPCs compared to nPCs (panels D-F), the former also showing aberrant expressions of CD56 and CD117 (panels E,F). In addition, cPCs had a restricted expression of intracellular immunoglobulin light chain kappa (CyIgk), while nPCs had a normal CyIgk:CyIgLambda (CyIgL) ratio of 1.5:1 (panel H). Figure 2 Kaplan-Meier progression-free survival (PFS--panels A-C) and overall survival (OS--panels D-F) curves of patients with multiple myeloma (MM) submitted to autologous stem cell transplantation (ASCT) and grouped according to lenalidomide maintenance (yes vs. no) and/or bone marrow MRD (MRD+ or MRD-). PFS was significantly lower in patients with MM who had minimal residual disease (MRD)-positive BM (n = 32) at Day + 100 after ASCT vs. (n = 21), with median progression-free survival of 31 months vs. not reached (panel A), respectively; no significant differences in OS were observed between these two patient groups (panel D). Patients receiving lenalidomide maintenance (M-Len) after ASCT (n = 18) showed significantly better PFS and OS than patients who did not receive maintenance therapy (n = 35), with median PFS and OS rates of not reached (NR) vs. 29 months and of NR vs. NR, respectively (panels B,E). Finally, patients with an MRD+ BM who did not receive M-Len (n = 21) had significantly shorter median PFS (35 months) and OS (35 months) rates than the other patients ( M-Len use--n = 14; MRD+ with M-Len use--n = 11; M-Len--n = 7). In panel (F), OS was equal for both groups using M-Len, independently of MRD status; thus, MRD+ M-Len and -Len curves overlap (panels C,F). cancers-15-01605-t001_Table 1 Table 1 Demographics and baseline clinical and laboratory characteristics of patients with multiple myeloma included in this study grouped according to maintenance therapy (M-Len vs. no M-Len). Variables Studied at Diagnosis M-Lenalidomide n = 18 No Lenalidomide n = 35 p-Value Age (years) 57.5 (40-67) 59 (43-70) 0.56 Gender * (% female) 61% (11/18) 45.7% (16/35) 0.22 Subtype of MM * 0.90 IgG 67% (12/18) 63% (22/35) IgA 11% (2/18) 17% (6/35) LC 17% (3/18) 17% (6/35) NS 5% (1/18) 3% (1/35) Monoclonal component (serum) 1.40 2.50 0.77 g/dl (0-11) (0-10.1) Monoclonal component (urine) 0.80 0.85 0.74 g/24 h (0.37-6) (0-15.8) Hemoglobin g/L 115 (69-146) 100 (49-152) 0.18 Creatinine mg/dl 0.8 (0.6-5.2) 0.9 (0.5-8.6) 0.16 Calcium mg/dl 9.4 (7.7-17) 9.5 (8-14) 0.98 Bone Lesions * 94% (17/18) 91% (32/35) 0.58 DS Stage * 0.14 II-A and II-B 44% (8/18) 26% (9/35) III-A and III-B 56%(10/18) 74% (26/35) ISS Stage 0.23 I 56% (10/18) 31.5% (11/35) II 22% (4/18) 37% (13/35) III 22% (4/18) 31.5% (11/35) Albumin g/dl 3.8 (1.9-6.6) 3.7 (1.4-5.0) 0.16 Beta2-microglobulin mg/L 3.1 (1.8-11.3) 3.6 (1.1-33.3) 0.88 Induction treatment * 0.001 CTD 17% (3/18) 69% (24/35) VCD 83% (15/18) 31% (11/35) Response after ASCT * 0.42 CR and sCR 56% (10/18) 49% (17/35) VGPR and PR 44% (8/18) 51% (18/35) MRD 0.59 % (7/18) 40% (14/35) MRD+ 61% (11/18) 60% (21/35) Results expressed as median (range) values or as * number of cases/total cases (percentage). LC, light chain; NS, non-secretory; DS, Durie-Salmon stage; ISS, International Staging System; CTD, cyclophosphamide, thalidomide and dexamethasone; VCD, bortezomib, cyclophosphamide and dexamethasone. The patient group without maintenance with lenalidomide (n = 35) included patients who received thalidomide maintenance (n = 15) and those who did not receive it (n = 20). cancers-15-01605-t002_Table 2 Table 2 Univariate and multivariate analyses of prognostic factors for progression-free survival (PFS) of patients with multiple myeloma (n = 53). Univariate Analysis Multivariate Analysis Median PFS (Months) HR 95th CI p-Value HR 95th CI p-Value Age at diagnosis <58 37 1 >=58 28 1.7 (0.69-4.37) 0.23 DS II-A 38 1 II-B NR 0.34 (0.06-2.06) 0.86 III-A 27 (0.08-7.88) III-B 31 (0.49-5.99) ISS I 36 1 II 23 0.79 (0.25-2.46) 0.44 III 35 (0.54-4.51) Induction therapy CTD 34 1 VCD 35 1.99 (0.79-4.99) 1.13 Maintenance therapy No 29 1 Yes NR 5.78 (1.34-24.95) 0.003 7.05 (1.6-30.72) 0.001 Status post ASCT CR 44 1 Non-CR 30 4.69 (0.18-1.17) 0.10 MRD Positive 42 1 Negative NR 2.62 (0.94-7.29) 0.049 3.37 (1.19-9.57) 0.014 MRD and M-Len + and MLen+ 1 MLen 44 2.98 (0.58-15.4) 0.19 MRD+ No MLen 35 9.22 (2.06-41.2) 0.004 CI: confidence interval, HR: hazard ratio, ISS: International Staging System; DS: Durie-Salmon stage, CR: complete response; M-Len: lenalidomide maintenance, No M-Len: no lenalidomide maintenance. 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PMC10000508 | The aim of this study was to analyze coping mechanisms and their psychological aspects during the treatment of neoplastic prostate hyperplasia. We have analyzed strategies and styles of coping with stress and self-esteem of patients diagnosed with neoplastic prostate hyperplasia. A total of 126 patients were included in the study. Standardized psychological questionnaires were used to determine the type of coping strategy by using the Stress Coping Inventory MINI-COPE, while a coping style questionnaire was used to assess the type of coping style by using the Convergence Insufficiency Symptom Survey (CISS). The SES Self-Assessment Scale was used to measure the level of self-esteem. Patients using adaptive strategies of coping with stress in the form of active coping, seeking support and planning had higher self-esteem. However, the use of maladaptive coping strategies in the form of self-blame was found to cause a significant decrease in patients' self-esteem. The study has also shown the choice of a task-based coping style to positively influence one's self-esteem. An analysis related to patients' age and coping methods revealed younger patients, up to 65 years of age, using adaptive strategies of coping with stress to have a higher level of self-esteem than older patients using similar strategies. The results of this study show that older patients, despite the use of adaptation strategies, have lower self-esteem. This group of patients should receive special care both from family and medical staff. The obtained results support the implementation of holistic care for patients, using psychological interventions to improve patients' quality of life. Early psychological consultation and mobilization of patients' personal resources may allow patients to change stress coping methods towards more adaptive forms. prostate cancer coping mechanisms QoL This research received no external funding. pmc1. Introduction Among neoplastic diseases, prostate cancer is one of the most frequently diagnosed noncutaneous cancers in the recent years. Only in the United States, in 2017, 160,000 men were diagnosed with prostate cancer . In Poland, prostate cancer is responsible for nearly 9% of all cancer-related deaths. In comparison to Europe, where the 5-year survival rate is 83.4%, Poland holds a much lower percentage of 66.6% . Symptoms associated with its diagnosis include pain and worsening of physical condition, and these are present in more than 50% of patients. The choice of prostate cancer treatment option is complex; however, the quality of sexual life is an important aspect that influences patients' quality of life. Radical prostatectomy (RP) often negatively influences the sexual functioning, which contributes to an impaired sense of masculinity . Radical prostatectomy and hormone therapy contribute to the loss of sexual function, causing the feeling of confusion and disorientation in patients. . Previous studies have shown patients who experience emotional disorders and distress to be at a higher risk of poorer treatment outcomes, and have lower adherence to treatment plan, making the overall prognosis poorer than in emotionally stable patients . It is estimated that 30% of prostate cancer patients experience some form of emotional distress, defined as general suffering, and 10% experience severe depression . Studies have indicated that men diagnosed with prostate cancer experience emotional disturbances two to five times more often when compared to the general population . Adequate social support is an important factor for reducing anxiety and depression. Its lack contributes to the deterioration of the quality of life. Patients coping with the disease on their own were found to more frequently experience depression and have worse mental well-being . As for the body image issues present among cancer patients, Serbia et al. showed that psychological intervention conducted in women with breast cancer has influenced their adaptive approach to their bodies. Not only did the patients begin to view their bodies in a more positive way, but, also, their self-confidence and willingness to cooperate has increased. The results of the study indicate that patients' approach can be dynamically changed under a psychological intervention, if properly conducted. The initial reluctance of patients to have contact with their bodies transformed into no difficulties upon physical contact with the body parts affected by surgery. Due to the mix of social and biological factors, symptoms of depression may be masked by unhealthy coping behaviors manifested in the form of psychoactive substance abuse, dangerous car driving or casual sexual contact, and, thus, are more difficult to diagnose . From the time of diagnosis through the entire treatment process, patients experience strong emotional stimuli that may negatively affect their well-being and hospitalization. An optimalization of medical treatment and quality of life of patients with cancerous prostate hyperplasia is one of the greatest challenges the modern healthcare system has to face. Patients subjected to long-term stress exposure were proven to have a weakened immune response as well as more frequent metastasis formation and recurrences of the disease . According to Dropkin's definition, body image is the changing perception of one's own appearance, functions and sensations. The experiences related to the changes in body image occur mostly on a subconscious level. Patients, after surgical prostatectomy, were found to experience pain and were surprised by the changes related to the outlook and function of the penis. Studies also indicate unfavorable changes caused by hormonal disorders, which contribute to increasing the marital distance and deterioration of the relationship . A common belief that only older men are affected by prostate cancer poses another problem when it comes to patient treatment. In younger patients, the perspective of losing full sexual and physical activity may contribute to significant reduction of the quality of life. Studies show that older patients, despite the general health deterioration by prostate cancer, can maintain their subjective well-being and immunity at a relatively satisfactory level . When discussing with their doctor, patients are reluctant to talk about the deterioration or loss of sexual function associated with the treatment process. Lack of a sensitive intimate issue discussion often led to social isolation, negatively impacting their family life . Studies evaluating the differences between different coping strategies between patients of different ages have indicated worse functioning among younger patients. Due to the cancer diagnosis, they are often forced to revise their life plans. Moreover, they often experience loss of self-independence and economic difficulties. However, younger patients tend to have greater psychological resources that can be used to actively and confrontationally deal with cancer diagnosis and treatment . There is a limited amount of research on the moderating effect of age in the context of strategies and styles for coping with stress and self-esteem in patients with prostate neoplastic hyperplasia. Its better understanding may contribute to changes in the recently used strategies. Demonstration of different coping strategies among patients of different ages will allow for a more efficient psychological intervention, integral for treatment. The objectives of this study were to:Assess stress coping strategies in relation to patients' self-esteem. Assess stress coping styles in relation to patients' self-esteem. Identify the predictors of stress coping styles and strategies that determine patients' self-esteem. Determine the influence of patients' age as moderator of the relationship between self-esteem and ways of coping with stress. 2. Materials and Methods We have conducted a cross-sectional single center study to analyze self-esteem and stress coping strategies among patients diagnosed with and treated for prostate cancer. The study included 140 patients who were qualified by a multidisciplinary board for radical prostatectomy from June to December 2021. The board consisted of oncologists, urologists, radiotherapists, cancer coordinators and a psychooncologist, who worked at the urology department of Pomeranian Medical University. The qualification was based on the results of biopsy and diagnostic imaging. Patients qualified for other treatment options including radiotherapy and/or hormone therapy were excluded from the study to maintain the homogeneity of the study group. As Polish language was the mother tongue used by all of the patients, Polish adaptations of the questionnaires were used for the study purpose. The questionnaires were provided by the psychologist at the time of hospital admission, as the patients were awaiting their surgery. All patients were provided with a proper explanation of the study and were given a possibility to withdraw at any timepoint of the study. Patients completed the questionnaires on their own in a hospital room. The questionnaires were handed in an envelope. Having filled the forms, patients were asked to seal them in an envelope and return them to the researcher. All patients have signed the informed consent form. Participants who refused to sign the informed consent form or did not fill the questionnaires completely were removed from the study. A total of 140 study participants were provided with the questionnaires, of whom 126 have returned fully completed forms. Patients were asked to fill the following questionnaires: a demographic data questionnaire, the Coping Inventory for Stressful Situations (CISS), the Rosenberg Self-Esteem Scale and the Mini-COPE questionnaire. The demographic questionnaire consisted of 9 questions asking for patients' age, place of residence, education, marital status, children, satisfaction with the relationship with wife/partner, satisfaction with relationships with children, financial situation and help from relatives and family. The scale's reliability, depending on the age group, was calculated to equal 0.81 to 0.83. An adaptation of the Mini-Cope questionnaire was provided to assess patient strategies of dispositional coping. A version by Oginska-Bulik and Hurczynski (2009) was used. The form included 28 statements assessing for 14 strategies of coping with stress. The half reliability of the questionnaire was 0.86. The internal consistency for most of the scales was assessed at a satisfactory level . In order to examine styles of coping, an adaptation of the Coping Inventory for Stressful Situations (CISS) of Strelau et al. was used. It consisted of 48 statements concerning stressful events and specific coping patterns used in specific situations. Three main coping styles were identified: task-focused, emotion-focused and avoidance-focused. The avoidance-focused style was divided into engaging in vicarious activities or seeking social contact. The survey has high accuracy and high internal consistency (0.78-0.90 in accordance with Cronbach's alpha). Finally, a Polish version of the Rosenberg self-esteem scale adapted by Laguna, Lachowicz-Tabaczek and Dzwonkowska was used. The scope of the scale was to measure the general level of patients' self-esteem. The questionnaire included 10 statements. The reliability of the scale was found to vary depending on the age of the patient, ranging from 0.81 to 0.83 . Statistical analysis was performed using IBM SPSS Statistics 25. Basic descriptive statistics analyses were calculated using the Kolmogorov-Smirnov (K-S) test, Student's t-tests for independent samples, correlation analyses with Pearson's r coefficient and a stepwise linear regression analysis. a 0.05 was considered significant; however, test statistical results of a equal to 0.05 < p < 0.1 were interpreted as significant statistical trends. 3. Results 3.1. Demographic Data A total of 126 patients diagnosed with prostate cancer participated in the study. Due to missing/incomplete data, the number of responses to specific questions differed between the questionnaires, which is noted in the tables below. The youngest patients that participated in the study were 48, while the oldest were 82 years old. A total of 109 patients were married, and 30 were assessed to be in a good financial standing, choosing a 5 on a scale from 1 to 10, 1 being the lowest. Among the study population, 40 patients had a secondary education. Specific data are presented in the tables below (Table 1 and Table 2). 3.2. Analysis of Socio-Demographic Variables in the Inventory for Measuring Coping with Stress--Mini-COPE In the analysis, we have checked whether the number of children was related to the type of coping strategy. Multiple correlations were tested using Pearson's r coefficient. As demonstrated in Table 3, three were statistically significant. The number of children was positively correlated with the strategies of using sense of humor, self-denial and self-blame. However, the strength of the reported relationships was low. As the next step, we have assessed whether relationship (marital) satisfaction was related to coping processes. A series of Spearman's rho rank correlation analyses were performed. As shown in Table 3, one correlation was statistically significant, as relationship satisfaction correlated positively with emotional support strategy. The strength of this relationship was low. The other correlations were not statistically significant. We have also tried to determine if paternal relationship satisfaction was related to the strategy of coping with stress. Pearson's r coefficient correlations were performed, however, all of them were statistically insignificant. Similar investigations were performed to assess the impact of financial situation and the choice of stress coping strategy. No statistically significant results were found. The influence of help of the relatives was also determined. Active coping strategies were more frequent among patients who received help from family members. This group of patients also had a lower tendency for psychoactive substance use and self-blame. 3.3. Stress Coping Style and Strategies, as well as Self-Esteem, Depend on the Age of the Respondents An analysis of the influence of patients' age (under or over 65) on the type of stress coping style and self-esteem was performed using a series of moderation analyses with the Process macro. The association between task-focused style and self-esteem was significantly moderated by patients' age. Based on the conditional effects, the association was found significant for patients aged <65 years (B = 2.60; SE = 0.74; t = 3.51; p = 0.001), but not significant for patients aged 65+ (B = -0.31; SE = 0.91; t = -0.34; p = 0.736). Similarly, a moderated mediation model was used to analyze patients' age as a moderator of coping strategies and self-esteem. We found a statistically significant effect of age moderation on active coping strategy and self-esteem. The correlation between these variables was statistically significant in the group of patients <65 (B = 2.46; SE = 0.65; t = 3.77; p < 0.001), while the studied relationship was insignificant among patients aged 65+ (B = 0.27; SE = 0.72; t = 0.37; p = 0.710). There was also a statistically significant effect of age moderation on the relationship between the strategy of positive re-evaluation and self-esteem, with a statistically significant association for patients up to 65 years of age (B = 2.24; SE = 0.62; t = 3.59; p < 0.001), and an insignificant association for patients aged 65+ (B = -0.99; SE = 0.75; t = -1.31; p = 0.191). We have also found a significant effect of age moderation on seeking emotional support and self-esteem. Younger patients (<65 years old) with a lower tendency for choosing a strategy for seeking emotional support had lower self-esteem (B = 2.02; SE = 0.52; t = 3.92; p < 0.001). Among patients 65+, the relationship was not significant (B = 0.14; SE = 0.59; t = 0.23; p = 0.817). The associations with the types of individual dimensions of coping with stress were evaluated. We have found a statistically significant effect of age moderation on the relationship between active coping and patients' self-esteem. The correlation was statistically significant among patients <65 years of age (B = 3.17; SE = 0.75; t = 4.23; p < 0.001), while the effect was insignificant for patients aged 65+ (B = 0.15; SE = 0.91; t = 0.16; p = 0.873). A similar association was found for the dimension of seeking support and self-esteem. The correlation was statistically significant for patients aged <65 years old (B = 2.40; SE = 0.60; t = 3.98; p < 0.001), however, it was found to be insignificant for patients aged 65+ (B = 0.27; SE = 0.69; t = 0.40; p = 0.692). A graphical presentation of all statistically significant correlations is presented in Figure 1, while the remaining insignificant correlations are presented in Appendix A. 4. Discussion In the case of cancer patients, an important aspect that should be taken into consideration is that the coping strategies do not change. Patients who tended to use specific methods of coping with difficult situations were likely to use identical strategies during cancer diagnosis and different stages of treatment . In this study, we have assessed stress coping styles and strategies used by patients diagnosed with prostate cancer. We have also tried to evaluate how individual strategies impact patients' self-esteem. Trying to determine how to support prostate cancer patients, we have used our database to analyze the influence of sociodemographic variables on coping strategies. A result worth noticing was the fact that patients who received support from family and relatives tended to use an adaptive strategy in the form of active coping. Relatives' support also correlated negatively with the use of psychoactive substances and self-blame, which are considered maladaptive strategies. Despite the weak correlations, these data provide the basis towards further investigation. In our research, we have also examined the influence of adaptive stress coping strategy on patients' self-esteem. A task-focused stress coping style was positively associated with patients' self-esteem. Patients looking for information about their disease and actively cooperating with a doctor were characterized by higher self-esteem. On the other hand, the self-esteem was lower in patients using an emotion-based style. Similar findings were observed by Shakeri et al. , as cancer patients adopting an emotion-focused style of coping experienced reduced quality of life. This was due to the fact that, both at the time of diagnosis and in the later period, the accompanying emotions were usually negative. Emotions such as regret, anger and a sense of injustice negatively affect a patient's mental sphere and may constitute a new source of stress. Social withdrawal and focus on subsequent stages of cancer treatment are a combination that may effectively increase patients' positive self-esteem, allowing a view from a different, more positive perspective . Studies have demonstrated that men use emotion-based strategies less frequently than women. This difference between male and female populations may be used at the beginning of cancer treatment, as, instead of concentrating on patients' emotion suppression, the therapy can focus on subsequent treatment analysis and mobilization of patients' personal resources . Our data support the role of adaptive styles of coping with stress among prostate cancer patients. We have found patients using task-oriented coping strategy to have higher self-esteem. Our study has also demonstrated the non-adaptive style to influence patients' self-esteem. Such patients tended to focus on their emotions as a coping method. Our results are consistent with previous studies assessing cancer patients. Among the studied styles, the strategy using avoidance was not significantly related to self-esteem. Multiple coping strategies were found to influence patients' self-esteem both positively and negatively. The first strategy that significantly related to self-esteem was active coping. Patients who were in contact with a stressor and have undertaken active steps to reduce it, initiated specific actions directly and increased their efforts to fight the disease were found to have higher self-esteem. Similar results were obtained in a meta-analysis conducted by Roesh et al., (2005), showing a positive relationship between self-esteem and active coping strategies . Another correlation that positively related to self-evaluation was a planning-based strategy. Having identified the difficult situation, action plan formulation and analysis of different strategies were found to reduce the associated stress. Patients using a planning strategy tend to analyze their resources against the source of stress, in this case, prostate cancer, indicating the secondary nature of the assessment. As a part of cancer treatment planning, patients can prepare for the upcoming treatment and its consequences, including the possible adverse effects of surgical prostate resection. The importance of patient preparation was noticed by Spendelow et al., (2017), who showed in their meta-analysis that the use of active coping strategies could reduce patients' perception of both physical and psychological pain. The authors have also indicated that the timing of a patient's recovery may be associated with specific strategies, and slower recovery was demonstrated among patients using non-adaptive strategies . Our study has also shown a positive correlation between self-esteem and strategies for seeking instrumental and emotional support, which are based on seeking information and help. For a variety of reasons, patients may check for a second opinion to confirm the diagnosis and treatment options and/or to provide further guidance. Seeking emotional support is related to the need for help in the area of enduring the hardships of treatment and understanding of family and friends. Complications associated with prostate cancer treatment often include disturbance of physiological functions, not only related to urinary incontinence and nocturia, but also negatively affecting sex function, providing additional psychological burden . Our results are consistent with the previous literature. Family support can significantly help for cancer patients and influence their treatment outcomes. A review conducted by Sukyati et al. has demonstrated that family support can even result in relapse prevention. Anxiety has a negative impact on health, lowering patients' self-confidence, causing insomnia and lowering patients' quality of life. Partners' support can cause a greater control over the emotional sphere, which significantly reduces the level of anxiety. In addition, social support has been shown to contribute to a greater acceptance of the disease and a reduction of depressive symptoms. As the last part of the study, we have evaluated the moderating effect of age on coping strategies and self-esteem. We have found some significant correlations between patients' age, their stress response and self-confidence. In patients up to 65 years old, the use of active adaptive stress coping strategies was found to correlate with higher self-esteem. However, the correlation was insignificant for older patients. The differences between the two age groups may be caused by different stages of evolutionary psychology. Patients in later adulthood are in the culmination stage of life, and their developmental tasks concentrate mostly on contribution to the well-being of future generations, while younger patients concentrate more on self-actualization and integration. Our research did not reveal sociodemographic differences between the strategies used and the support of parents, families and children, therefore, from the beginning of the study, we did not assume any subdivision of patients. A previous study by Matzka et al. found no influence of social support on patients' resilience index. Cancer diagnosis provides additional psychological burden, and even the use of adaptive strategies does not increase patients' self-esteem. Patients in their midlife (middle adulthood) using adaptive strategies of stress coping in the form of acceptance, active coping, positive reappraisal and seeking instrumental and emotional support were found to have higher self-esteem. These findings are particularly important due to the role of self-esteem in anxiety and cancer-associated stress reduction. Patients with higher self-esteem tend to have a more positive attitude, regardless of the difficulties encountered . Self-esteem and self-determination can be used as resources during patients' cancer treatment. If higher, patients can have a sense of control and power over situations in their lives, reducing negative psychological implications of cancer diagnosis and treatment . The results of a meta-analysis by Roesch et al. have shown prostate cancer patients using active coping to have lower levels of anxiety and depression and were consistent with Lzararusa and Folkman's transactional model. Patients who tend to approach the disease as a challenge more often use strategies based on active coping . There is limited research on the influence of age on cancer patients' stress coping styles and strategies. However, our findings highlight the need for further studies and provide an important direction towards working with cancer patients. In our study, among the younger group of patients, we have noticed that a task-oriented stress coping style and the use of adaptive strategies correlate with higher self-esteem. This allowed us to select a population of patients potentially able to withstand the negative emotions associated with cancer and requiring the least psychological intervention. In our study, we have also identified a group of patients that should receive special attention during psychological interventions. Among older respondents, social withdrawal and lower physical activity were more common. Our research revealed the importance of spouse/partner support, as it correlated with longer patient survival. Psychological support should be provided as a routine procedure for cancer patients and can include various adaptive stress coping strategies. Services should also consider inclusion of patients' partners in the psychological support program. The results of our study may be helpful for future clinical trials. During patient consultation, standardized questionnaires to assess strategies and styles of coping with stress and self-assessment can be used for psychological evaluation. For patients using non-adaptive coping strategies, during psychological interventions, it is important to be able to reformulate their thinking and coping strategies and to work with the patients in order to make them use adaptive forms of coping. Patients undergoing prostatectomy usually are discharged home two days post-surgical treatment, and it is often the last time they have contact with a psychologist. An introduction of an interactive clinic organized, e.g., by Canadian organization Movember, would allow patients to have better psychological care. Patients can also be provided with educational materials and online psychological consultations to ease patient-psychologist contact. The importance of psychosocial support was previously demonstrated and is supported by the Stanford Chronic Disease Self-Management Program (CDSMP) present in the United States since 2010. The objective of the program is to enhance patients' self-efficacy to have more confidence in their ability to fight against the disease. As a part of the program, during a 6-week workshop, individuals learn self-management through adaptive problem solving, activity planning, medication and symptom management, physical activity and communication with healthcare professionals. Its effectiveness was demonstrated by Salvatore et al., who showed positive effects on quality of life and health-related outcomes of cancer survivors . 5. Conclusions For the majority of patients, cancer diagnosis is a difficult and complex process. Patients diagnosed with a malignant disease present with various coping mechanisms related to their coping resources, economic situation, education and previous experience. The incidence of prostate cancer is rising, and, each year, more and more patients will face its diagnosis. Regardless of cancer staging, even for patients presenting with advanced forms of the disease, cancer diagnosis is usually shocking and followed by a range of strong emotions experienced by both patients and their families. An important aspect that should be complementary with cancer treatment is psychological help. The aim of our research was to identify stress coping styles and strategies used by prostate cancer patients. The results of this study are not only extremely important from the patients' perspective, but also for the medical personnel involved in cancer treatment. Both adaptive and non-adaptive coping styles were found among patients diagnosed with prostate cancer. Given the relatively constant nature of coping styles, we can speak of specific models used by patients throughout the treatment. Our findings seem to be consistent with theoretical assumptions, as, in the case of personal coping resources and support of loved ones, patients tend to use a task-focused coping style, favoring higher self-esteem. On the other hand, a problem-based stress coping style was found to negatively influence patients' self-esteem. We have also proved the use of adaptive stress coping strategies among prostate cancer patients to contribute to higher self-esteem. The study included two age group categories, differing in patients' attitudes and approaches towards cancer diagnosis and treatment, showing that patients aged over 65 should receive special psychological care. 6. Limitations There are several limitations to this study. The study has focused on one cancer type only. Further research is needed to assess for any differences between coping styles and strategies used by different cancer patient populations, genders and cancer diagnoses. Another limitation was that we did not compare changes of patient stress coping strategies over time. The strengths of the study included evaluation of the importance of family support, which was found to influence the use of adaptive or non-adaptive coping strategies. The study sample was also limited and included only 126 prostate cancer patients. Further studies on greater populations should be performed in order to confirm the study results and provide further knowledge on the psychological aspects of prostate cancer diagnosis and treatment. Author Contributions Conceptualization, E.S. and B.K.; methodology, E.S.; formal analysis, E.S.; investigation, M.P.; data curation, E.S., K.S.-Z., O.W. and K.T.; writing--original draft preparation, E.S. and O.W.; writing--review and editing, E.S., A.C.-G. and K.M.; supervision, B.K.; project administration, E.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of NAME OF INSTITUTE (protocol code KB-0012/91/16 of 27 June 2016, and KB-0012/173/17 of 18 December 2017). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Appendix A cancers-15-01450-t0A1_Table A1 Table A1 The influence of patients' age on coping styles and strategies and patients' self-esteem. Predictor F (1, 117) p R2 Active coping 5.07 0.026 0.039 Planning 1.95 0.165 0.015 Positive reappraisal 10.90 0.001 0.083 Acceptance 2.73 0.101 0.023 Sense of humor 0.01 0.939 0 Turning to religion 0.53 0.468 0.005 Seeking of emotional support 5.81 0.017 0.044 Seeking of instrumental support 4.10 0.045 0.032 Self-distraction 0.16 0.695 0.001 Denial 0.44 0.508 0.004 Venting 0 0.968 0 Substance use 0.71 0.403 0.005 Behavioral disengagement 0.35 0.556 0.003 Self-blame 2.43 0.122 0.017 Predictor F(1, 117) p R2 Active coping 2.43 0.122 0.017 Helplessness 6.59 0.012 0.049 Seeking of support 5.41 0.022 0.041 Avoidance 0.04 0.852 0 Predictor F(1, 116) p R2 Task 6.17 0.014 0.048 Emotion 0.09 0.763 0.001 Avoidance 0.02 0.876 0 Distraction 0.04 0.835 0 Social Diversion 0.03 0.860 0 Figure 1 Associations between the strategy of coping and patients' self-esteem. cancers-15-01450-t001_Table 1 Table 1 Demographic data. N % Marital status Bachelor 1 0.80 Married 109 87.20 Divorced 8 6.40 Widower 6 4.80 Unformal 1 0.80 Altogether 125 100 Financial situation 1 1 0.80 2 2 1.60 3 2 1.60 4 1 0.80 5 30 24.20 6 18 14.50 7 18 14.50 8 29 23.40 9 7 5.60 10 16 12.90 Altogether 124 100.0 Education Primary 11 8.80 Vocational 36 28.80 Secondary 40 32.00 Post-secondary 4 3.20 Bachelor 4 3.20 Master's and higher 30 24.00 Altogether 125 100 cancers-15-01450-t002_Table 2 Table 2 Results of the CISS, Mini-COPE and Self-Esteem-Scale questionnaires. Mean Median SD Min. Max. N CISS stress coping styles Task 3.41 3.47 0.59 1.75 4.81 124 Emotion 2.44 2.44 0.62 1 4.06 124 Avoidance 2.60 2.63 0.57 1.25 4.25 124 Distraction 2.20 2.13 0.67 1 4.25 124 Social diversion 3.21 3.20 0.78 1.40 5 124 Mini-COPE stress coping strategies Active coping 2.02 2 0.70 0 3 124 Planning 1.98 2 0.69 0 3.50 124 Positive reappraisal 1.68 1.75 0.69 0 3 124 Acceptance 1.91 2 0.67 0 3 119 Sense of humor 0.97 1 0.68 0 3 119 Turning to religion 1.03 1 0.96 0 3 124 Seeking of emotional support 1.75 2 0.86 0 3 124 Seeking of instrumental support 1.66 2 0.75 0 3 124 Self-distraction 1.54 1.50 0.79 0 3.50 124 Denial 0.83 1 0.72 0 2.50 124 Venting of emotions 1.08 1 0.65 0 2.50 124 Substance use 0.38 0 0.57 0 2.50 124 Behavioral disengagement 0.83 1 0.72 0 3 124 Self-blame 1.17 1 0.73 0 3 124 Dimensions of stress coping strategies Active coping 1.90 1.83 0.57 0.50 3 124 Helplessness 0.79 0.75 0.50 0 2.17 124 Seeking of support 1.70 1.75 0.74 0 3 124 Avoidance 1.15 1.17 0.53 0 2.50 124 Rosenberg score Self-esteem 29.98 30 3.81 16 40 123 SD--standard deviation; Min., Max.--lowest and highest value of the distribution. cancers-15-01450-t003_Table 3 Table 3 Associations between sociodemographic factors, stress coping strategies and dimensions of styles of coping. Number of Children Satisfaction with Contacts with Partner/Wife Satisfaction with Contacts with Children Financial Situation Help from Family N Mini-COPE stress coping strategies Active coping r/r -0.141 0.028 -0.079 0.138 0.179 122 p 0.124 0.769 0.398 0.129 0.049 Sense of humor r/r 0.249 0.071 0.117 -0.036 -0.025 p 0.007 0.462 0.219 0.702 0.787 Turning to religion r/r 0.121 0.095 -0.002 -0.080 0.066 p 0.197 0.326 0.982 0.393 0.483 Seeking of emotional support r/r -0.143 0.216 -0.041 -0.070 0.164 p 0.119 0.021 0.657 0.447 0.072 Seeking of instrumental support r/r 0.041 0.046 -0.143 0.019 0.108 p 0.656 0.625 0.121 0.836 0.239 Self-distraction r/r 0.145 0.009 -0.023 0.157 0.113 p 0.115 0.920 0.807 0.083 0.218 Denial r/r 0.290 0.079 0.084 -0.035 0.046 p 0.001 0.403 0.365 0.703 0.617 Venting r/r 0.055 -0.027 -0.161 0.028 -0.019 p 0.552 0.776 0.081 0.758 0.838 Substance use r/r 0.134 -0.094 0.041 -0.041 -0.226 p 0.145 0.317 0.657 0.657 0.013 Behavioral disengagement r/r 0.155 0.017 0.109 -0.069 -0.128 p 0.090 0.853 0.238 0.453 0.161 Self-blame r/r 0.220 -0.086 -0.158 -0.143 -0.232 p 0.016 0.361 0.087 0.115 0.011 Dimensions of strategies of coping with stress Helplessness r/r 0.229 -0.036 -0.006 -0.118 -0.258 122 p 0.012 0.701 0.949 0.197 0.004 Avoidance r/r 0.224 0.011 -0.039 0.074 0.069 p 0.014 0.908 0.677 0.417 0.451 CISS stress coping style Task r/r -0.077 -0.024 0.042 0.167 0.146 121 p 0.404 0.797 0.655 0.067 0.111 Emotion r/r 0.086 -0.067 -0.141 -0.081 -0.155 p 0.350 0.474 0.129 0.374 0.089 Self-esteem r/r -0.230 0.082 0.042 0.125 0.206 123 p 0.012 0.388 0.654 0.171 0.024 r/r--Pearson's correlation coefficient; p--p-value. 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PMC10000509 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050968 diagnostics-13-00968 Review Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions Elhakim Tarig 12* Trinh Kelly 3 Mansur Arian 4 Bridge Christopher 24 Daye Dania 24* El-Baz Ayman Academic Editor Suri Jasjit S. Academic Editor Caruso Damiano Academic Editor 1 Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA 2 Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA 3 School of Medicine, Texas Tech University Health Sciences Center, School of Medicine, Lubbock, TX 79430, USA 4 Harvard Medical School, Harvard University, Boston, MA 02115, USA * Correspondence: [email protected] (T.E.); [email protected] (D.D.) 03 3 2023 3 2023 13 5 96823 12 2022 11 2 2023 18 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation. artificial intelligence machine learning CT body composition prognostication risk prediction This research received no external funding. pmc1. Introduction Body mass index (BMI) has long been a key clinical metric that is used in predictive models to estimate the risk of developing chronic diseases and future mortality . Unfortunately, BMI has several shortcomings and does not account for the distribution of fat in the body and does not distinguish between excess fat, proportion of bone mass or muscle . Because BMI only measures excess weight, this measure cannot reflect the loss of muscle mass as in sarcopenia and sarcopenic obesity. Body composition metrics incorporate the proportion of body fat and skeletal muscles. Many non-invasive measures exist that analyze body composition starting from the traditional skin-fold tests to other advanced measures such as bioelectrical impedance analysis, dual-energy X-ray absorptiometry (DXA), hydrostatic (underwater) densitometry and air displacement plethysmography, among others . Despite some studies suggesting their accuracy compared to BMI, many of these latter metrics are considered inappropriate for widespread clinical implementation because they are often complex to implement, expensive, and difficult to standardize . As such, the CDC currently only recommend BMI as an indication of body composition and health risks, especially as other measures have no available reference standards or validated risk categories . Advances in CT scan automated segmentation and deep learning have opened the door for the implementation of CT body composition as a novel tool to assess health and disease risk . Multiple studies have shown the clinical importance of CT body composition in risk prognostication and treatment planning . We project that these new metrics can eventually replace BMI in many clinical applications. Many patients currently undergo a CT scan for diagnostic purposes. Much data from these scans are not being used for clinical decision-making. CT scans have the capability of providing more information, in addition to their specific clinical indication, allowing opportunistic screening for disease prognostication and primary prevention. Recently, there have been new approaches that have decreased radiation exposure per unit volume of imaging, making CT more suitable . Many targeted interventions can be applied to improve disease prevention and eventually patient outcomes. 2. Imaging-Based Body Composition Analysis CT and MRI are regarded as the gold standard for body composition analysis and can be used to quantify body composition. While these methods are costly, multiple people undergo cross-sectional imaging for other clinical indications, allowing for opportunistic assessment of body composition. CT works by taking multiple X-rays of the body from various angles while MRI uses the magnetic properties of hydrogen nuclei in the cells of the body to create images of soft tissues. Both methods allow for detailed evaluation of individual skeletal muscles and adipose tissue, although one study showed that MRI slightly underestimates visceral adiposity . There have been several attempts to compare the performance of CT and MRI in CT body composition analysis, with most studies showing a high correlation between both modalities . However, MRI voxel values are highly dependent on a number of factors related to the interactions between protons .The inconsistency in voxel values is one of the biggest challenges for MRI, thus making advancement of this approach more difficult. Despite MRI not exposing patients to ionizing radiation, the use of CT is considered quick, easy and less costly. Additionally, CT imaging is widely available compared to MRI. In a recent 2000-2016 analysis of seven US healthcare systems, CT annual imaging rates in the US have increased from 56 to 141 per 1000 person per year, while MRI increased from 16 to 64 per 1000 person per year . This shows the widespread availability of CT imaging, making it a more powerful tool for opportunistic screening, population-based analysis and large scale investigations. As a result, multiple AI-based algorithms have been developed to perform automated CT body segmentation and quantification by measuring skeletal muscle and fat, typically at the L3 vertebrae. These values are then used to estimate whole-body composition and prognosticate patients. Below, we summarize the standard metrics extracted from CT body composition algorithms and expand on their clinical applications (Table 1). 2.1. Muscle Mass Low skeletal muscle is termed sarcopenia and has been associated with worse clinical outcomes in conditions such as cancer , cirrhosis and critical illness , among others as well as postoperatively . Sarcopenia has primarily been found to be an independent predictor of survival in cancer patients . In one study, cancer patients who did not look thin or malnourished were found to have sarcopenia only through CT body composition analysis . In a recent systematic review, eight studies showed that the reduced muscle mass was mainly detected through CT body composition analysis with a high number of patients being misclassified based on BMI . CT body composition detects sarcopenia at a rate that is 27.3-66.7% higher compared to the detection of malnourishment using BMI. Sarcopenia can be difficult to assess clinically even with the use of BMI. For instance, some patients have a high proportion of fat to muscle ratio as seen in sarcopenic obesity. In another study, obese patients with a BMI > 30 mg/m were found to be sarcopenic through CT body composition . Sarcopenic obesity is the extreme of two phenotypes being low muscle mass and high BMI. It has been associated with worse clinical outcomes, especially in cancer patients . This type of abnormal body composition is not detected clinically because muscle and fat tissue quantification is required to establish the diagnosis. Multiple studies have showed that sarcopenia can occur through all ranges of patients' BMI . CT body composition can better identify patients at risk of worse clinical outcomes . To diagnose sarcopenia, the European Consensus Statement now recommends using a CT scan as the gold-standard technique , highlighting the importance of CT body composition and its potential in clinical practice. There are several ways suggested to diagnose sarcopenia on CT imaging. In a systematic review and meta-analysis of 70 studies from 15 countries that used CT to assess sarcopenia, 88.4% used skeletal muscle index (SMI) L3 to diagnose sarcopenia, five used visceral fat criteria and three used the total psoas area (TPA) criteria . SMI is determined by measuring the total skeletal muscle area (cm2) at the L3 level and dividing by the height squared (m2). Among the studies that used SMI, there were several cutoff criteria used. The three most common include: (1) the cut-offs introduced by Prado et al., which defined sarcopenia as SMI < 52.4 cm2/m2 for males and < 38.5 cm2/m2 for females, which have been used in 20 studies ; (2) the cut-offs introduced by Martin et al., which defined sarcopenia as SMI < 53 cm2/m2 if BMI >= 25 kg/m2 or SMI < 43 cm2/m2 if BMI < 25 kg/m2 in males and SMI < 41 cm2/m2 in females, and have been used in 17 studies ; (3) those introduced by Zhuang et al., which defined sarcopenia as SMI < 40.8 cm2/m2 in males and SMI < 34.9 cm2/m2 in females, and have been used in 12 studies . Of the studies that used the visceral fat criteria, most used the cut-off from the Japanese Society for the Study of Obesity which describes a visceral fat area (VFA) of >=100 cm2 as the cutoff . Of the studies that used the TPA criteria, most used the cut-off of Fearon et al. which defined sarcopenia by calculating the total cross-sectional area (mm2) of the psoas muscle at L3 and dividing by height squared (m2). Its cutoffs have an international consensus defined as <385 mm2/m2 in women and <545 mm2/m2 in men . 2.2. Skeletal Muscle Quality SMI and skeletal muscle radiation attenuation (SM-RA) obtained from CT scan allows the evaluation of myosteatosis or low muscle quality. Deposition of fat in muscles is indicative of muscle wasting. A recent study of HCC patients undergoing hepatectomy found that myosteatosis is associated with worse perioperative morbidity, mortality and long-term oncological outcomes compared to sarcopenia . Myosteatosis was also found to have an important prognostic role in HCC patients undergoing surgery and can be an independent risk factor of perioperative morbidity. Assessment of myosteatosis is important to complement other body composition metrics to predict perioperative and long-term disease outcomes. 2.3. Visceral Fat Content High visceral fat is associated with increased systematic vascular resistance, lower cardiac output, insulin resistance and higher pro-inflammatory factors promoting carcinogenesis . The most commonly implicated inflammatory markers are tumor necrosis factors, interleukin-6, adiponectin and free fatty acids which are found to directly flow through the portal vein causing liver inflammation, NASH cirrhosis and hepatocellular carcinoma . High visceral fat was also found to be an independent predictor of major cardiovascular events, cancer risk, metabolic syndrome and mortality in asymptomatic screening populations and in patients with colon cancer . This emphasizes the importance of analyzing visceral fat mass, in addition to skeletal muscle, to aid in predicting overall health and outcomes from various diseases and therapies . 2.4. Bone Density CT body composition examinations typically incorporate information on bone density, providing CT-based opportunistic screening for osteoporosis . Due to its volumetric nature, CT images may be more accurate in determining bone mineral density compared to DEXA . Thus, the development of an algorithm that is capable of segmenting CT images automatically and accurately can assist in predicting future risk of osteoporotic fractures. Pickhardt et al. used an automated, feature-based image processing algorithm to measure L1 trabecular attenuation, and the result was consistent with data from manual region-of-interest placement . Tan et al. created an automated algorithm to segment vertebral body for measurement of syndesmophytes and progression of ankylosing spondylitis . Opportunistic screening for reduced bone density can be performed simultaneously as patients undergo CT scanning for other indications . As such, CT body composition may allow for the opportunistic detection of osteoporosis and may potentially improve access to early treatment and management. 2.5. Arterial Calcifications Coronary artery calcification can be quantified using CT body composition software for opportunistic screening. Studies have shown a strong correlation between coronary artery calcification score and future cardiac events . Additionally, abdominal CT scan can quantify abdominal aorta calcifications, which are found to have positive correlation with coronary heart disease . Pickhardt et al. developed a deep-learning mask region-based convolutional neural networks (R-CNN) algorithm to segment and quantify calcified atherosclerotic plague within the abdominal aorta from CT scans . The algorithm automatically selects the L1-L4 vertebral levels to perform segmentation and quantification of aortic calcification. CT-based abdominal aorta calcification scores obtained from both semi-automated and automated methods have been shown to better predict future cardiovascular events compared to the Framingham Risk Score . 2.6. Other CT-Based Quantitative Metrics Several other studies have recently shown that many additional quantitative parameters can be extracted from CT images. CT allows the quantification of epicardial adipose tissue, which is the biologically active adipose tissue between the myocardium and the visceral pericardium that is associated with adverse cardiovascular events . Given the unreliability of creatinine excretion and eGFR equations for patients with certain body compositions, Pieters et al. developed equations that estimated creatinine production by using deep-learning body composition analysis of CT images . Abdominal CT biomarkers, such as pancreatic CT attenuation, fat content and fractal dimension, can also be assessed with deep learning, and in particular can aid in the diagnosis of type 2 diabetes mellitus . Additionally, CT scans allow for the segmentation of organs at risk, which is imperative for planning radiotherapy . Deep learning methods have been developed to automate organ segmentation, such as in the parotid gland , prostate , adrenal gland , mammary glands and multiple other multi-organs . Other emerging targets for CT-based analysis using automated segmentation include the detection and assessment of intracranial internal carotid artery calcification . Cui et al. developed an automated segmentation algorithm using dense V-networks for small gross tumor volumes in lung cancer from 3D planning CT images . Lin et al. proposed a 3D UNet-based deep learning model for automated segmentation and detection of renal tumors . Their newly created model has shown promising results with high levels of accuracy. Bilic et al. reviewed and analyzed around 75 state of the art automated liver and liver tumor segmentation algorithms from CT scans and found that the best liver segmentation algorithm achieved a dice score of 0.963, but for liver tumor segmentation the highest achieved was a dice score of 0.739, indicating further research need in this area . With new advances in deep learning and image segmentation, we envision that new metrics will be made available over the coming years to be used in clinical practice to improve patient disease screening and management. 3. Clinical Applications of CT Body Composition 3.1. Cancer Sarcopenia is associated with increased morbidity and mortality in multiple types of cancer including pancreatic cancer , esophageal cancer , lung cancer , colorectal liver metastasis and melanoma , among others. In a recent systematic review of CT body composition in abdominal malignancy, seven studies showed that low muscle mass was associated with a worse clinical outcome . Sarcopenia was linked to adverse therapeutic and clinical outcomes including higher postoperative infections, systematic inflammation, chemotherapy toxicity and mortality in patients with abdominal malignancy . In another multi-center retrospective study of preoperative CT body composition analysis in lung cancer patients undergoing lobectomy, skeletal muscle mass was an independent predictor of postoperative complications and increased hospital length of stay (LOS) . Interestingly, low thoracic muscle mass was more effective than biological age in predicting postoperative events . In the same population, sarcopenic obesity was an independent predictor of hospital LOS and postoperative complications. This highlights the role of CT body composition in identifying cancer patients who carry a high risk of worse clinical outcomes prior to surgery. Similar results have been reported in patients with hepatocellular carcinoma (HCC) . CT body composition has been found to be predictive of patient outcomes in those receiving chemotherapy, radiotherapy, radio-frequency ablation, embolization, hepatectomy and liver transplant . In a recent study evaluating the prognostic factors associated with overall survival in elderly patients with HCC receiving trans-arterial chemoembolization (TACE), the detection of muscle depletion and visceral adiposity was found to be independently associated with poor survival outcomes . The same study found no relationship between BMI and survival . Interestingly, the response to the first TACE session was better in those with low muscle mass and high visceral fat compared to those with normal body composition . However, the former group had lower overall survival. As such, assessment of body composition may be an important clinical consideration for HCC patients undergoing TACE. Similarly, Faron et al. evaluated the role of sarcopenia to predict overall survival in those receiving yttrium-90 (Y90) trans-arterial radioembolization (TARE) . Sarcopenia was found to be an independent prognostic marker of overall survival and can provide prognostic value in patients receiving Y90 TARE . Another study assessed sarcopenia before and after treatment with TARE and found it to be predictive of post-TARE progressive HCC disease . Similarly, HCC patients with sarcopenia undergoing radiofrequency ablation therapy were found to have a lower survival rate compared to nonsarcopenic patients . In HCC patients undergoing hepatectomy, sarcopenia was associated with high rates of post-surgical complications . One study showed that the 5-year survival rate was lower in those with sarcopenia compared to non-sarcopenic patients (58.2% vs. 82.4%, p = 0.0002) . Additionally, having sarcopenia was associated with a worse tumor stage and microvascular invasion . Another study showed that patients with sarcopenia have higher rates of morbidity and mortality after hepatectomy , similar to those who have diminished functional reserves . When considering hepatectomy, it is important to assess the future liver remnant (FLR), the volume of liver to be left behind after resection . Those with small FLR have a higher risk of post-hepatectomy liver failure . Many of these patients undergo portal vein embolization (PVE) prior to hepatectomy so as to divert portal venous blood and trophic factors to the non-embolized section of the liver leading to liver hypertrophy of the non-resected liver segments. Those with insufficient hypertrophy are at increased risk of post-hepatectomy liver failure . A recent study evaluated the role of CT body composition in predicting liver remnant hypertrophy following PVE in patients with colorectal liver metastasis. The study found that patients with sarcopenia had impaired liver hypertrophy after PVE . Another study also found that the quantity and quality of skeletal muscle were associated with the degree of liver hypertrophy after PVE . Low muscle mass on CT body composition was found to be an independent predictor of poor liver hypertrophy after PVE and increased the risk of post-hepatectomy liver failure . These studies suggest that the assessment of CT body composition prior to PVE may be important for identifying patients at risk of post-hepatectomy complications. In addition to the prognostic association of sarcopenia with poor performance status, cancer progression and overall survival, it has also been linked to chemotherapy toxicity and response to therapy . A recent retrospective study found decreased survival rates in sarcopenic patients receiving sorafenib chemotherapy for HCC compared to nonsarcopenic patients . Additionally, sarcopenic patients were found to have a lower response to chemotherapy and lower disease control compared to nonsarcopenic patients . Another study found sarcopenia to be associated with early dose chemotherapy toxicity . These results raise the question of possible future adjustments of chemotherapy dose based on the amount of skeletal muscles that a patient has, to avoid extensive toxicity . 3.2. Liver Disease Studies have shown an association between CT body composition and severity of liver disease . Liver cirrhosis is strongly associated with sarcopenia . The distribution of body fat is a major predictor of complications and outcomes in patients with cirrhosis, both before and after liver transplantation . Therapy for liver disease is also associated with alterations in body composition. For instance, transjugular intrahepatic portosystemic stent (TIPS), a standard therapy in many patients with portal hypertension, is associated with improved fat-free mass and fluid-free body weight . Artu et al. utilized CT scans to measure body composition in patients post-TIPS placement and found an improvement in sarcopenia and decreased visceral-to-subcutaneous fat ratio following intervention . Additionally, Pang et al. were able to demonstrate that pre-TIPS blood ammonia had a positive association with post-TIPS BMI . These studies demonstrate the importance of CT body composition analysis before and after treatments in liver disease. In addition to its association with response to therapies, CT body composition can also be used to predict the etiology of liver disease. Zou et al. developed a deep learning algorithm using Google's DeepLabv3+ in which body composition was automatically extracted . Their study showed that patients with NAFLD cirrhosis had decreased muscle mass and a significant increase in visceral and subcutaneous fat compared to those with non-NAFLD cirrhosis. The study also showed higher levels of accuracy of CT body composition compared to that of BMI in distinguishing the two patient populations. These findings highlight the potential role of CT body composition in risk prediction and stratification in liver disease. 3.3. Inflammatory Bowel Disease (IBD) Analysis of abdominal CT body composition can also aid in disease prognostication in patients with Crohn's Disease and ulcerative colitis (IBD). IBD is a gastrointestinal inflammatory disorder associated with malabsorption resulting in low skeletal muscle mass, decreased bone mineral density and therefore a dynamic change in body composition especially in patients with Crohn's disease . Abdominal CT-based opportunistic screening has been utilized in several studies for prognostication in IBD. Changes in CT body composition metrics in patients with IBD are correlated with disease duration and severity . The pathogenesis of Crohn's disease is associated with increased visceral adiposity as identified through CT body composition. In patients with increased visceral adiposity, studies have reported a more complicated disease course , higher postoperative complication rates and higher rates of disease recurrence , Grillot J et al. also reported worse Crohn's disease outcomes with sarcopenia and visceral adiposity . Another similar study found that muscle volume is strongly associated with hospital length of stay and that both, muscle volume and visceral adiposity, are strongly associated with intestinal resection rates . These results highlight that early screening and detection of body composition changes in patients with Crohn's disease may help in risk stratification and may inform early nutritional and pharmacological interventions, potentially improving patients' outcomes and quality of life . 3.4. Kidney Disease Paradoxically, higher BMIs are associated with better survival in patients with chronic kidney disease (CKD) . However, due to the limitations of BMI, it is not fully known whether the increase in survival is associated with levels of adipose tissue or lean mass. Patients with CKD tend to have fluid retention that cannot be differentiated with BMI. Lin et al. showed, through using a body composition monitor-multifrequency bioimpedance spectroscopy device, that a high lean tissue index, not high BMI or high fat tissue index, predicted a lower risk of adverse outcomes in CKD patients . These findings illustrate the importance of body composition analysis and its association with outcomes in patients with kidney disease. Fully automated CT-based body composition analysis shows great promise as it can detect total muscle mass and quantify muscle wasting which is frequently seen in this patient population . It has been already shown that body composition analysis can accurately predict urinary creatinine excretion, creatinine clearance, and glomerular filtration rate (GFR) . A recent study showed that machine-learning CT body composition analysis can estimate creatinine excretion with a high degree of accuracy . These fully automated body composition analyses can validate Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation results and replace burdensome 24-h urine collection with spot urine collection, paving the way for integrated diagnostics that use multidisciplinary data for better patient care . Furthermore, there have been recent efforts to fully automate kidney segmentation by measuring kidney, cortex and medulla volumes, which will provide a wide range of clinical applications such as evaluating renal donor suitability and prognosticating outcomes . Other studies have found a correlation between high visceral adipose tissue and poor outcomes in patients with kidney disease . Sarcopenia was also found to have a strong association with increased mortality and morbidity in patients with this condition . Other studies have shown that skeletal muscle and visceral adipose tissue derived from CT scans are stronger predictors of renal disease prognosis and can outperform established clinical parameters for risk stratification . In summary, utilization of CT body composition to accurately quantify muscle mass and calculate visceral-to-subcutaneous fat ratio has the capability of aiding prognostication in patients with renal disease. 3.5. COVID-19 Several studies have shown the association between CT body composition parameters and the severity of COVID-19 disease. Hocaoglu et al. and Ufuk et al. utilized CT to measure pectoralis muscle volume and density. They found that low pectoralis muscle density correlated with increased COVID-19 severity and worse outcomes . Chandarana et al. showed that CT-derived muscle adipose tissue measurements at the L3 vertebral level were significantly higher in patients with more severe symptoms of COVID-19; consequently, those patients had a higher risk of hospitalization . Similarly, Bunnell et al. performed body composition segmentation using an in-house automated algorithm trained specifically at the L4 vertebral level and found that COVID-19 patients with high visceral adipose tissue/subcutaneous adipose tissue ratio and high intermuscular adipose tissue have worse outcomes . Another study analyzed paravertebral muscle at the 12th thoracic vertebra in COVID-19 patients and found that muscle loss is a predictor of intensive care admission in COVID-19 patients. Taken together, these findings suggest that CT body composition analysis can help predict adverse clinical events and outcomes in patients with COVID-19. 3.6. Cardiovascular Diseases Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide . CT-based opportunistic screening can help detect cardiovascular diseases pre-symptomatically, thus allowing early preventative care to decrease future adverse clinical events and healthcare costs. O'Connor et al. showed that the abdominal aortic calcification score using semiautomated CT quantifications is a better predictor of cardiovascular events than the Framingham risk score (FRS) . Other studies have shown that controlling the progression of abdominal aortic calcification was associated with decreased risk of mortality, coronary artery disease, stroke and heart failure . By detecting aortic calcification early using CT-based opportunistic screening, appropriate interventions can be applied to those patients to address their underlying risk and prevent future cardiovascular mortality. Similarly, Pickhardt et al. defined several automated CT-based body composition biomarkers that can predict major cardiovascular events, including quantification of aortic calcification, muscle density, visceral/subcutaneous and liver fat and bone mineral density. These metrics outperformed clinical parameters such as the FRS and BMI for risk prediction . Recently, Magudia et al. described a retrospective study of 9752 outpatient routine CT scans of black people and white people with no recent history of cancer or cardiovascular diseases . Using a fully automated AI approach, the SMA, VFA and SFA were extracted from the L3 vertebra, then adjusted to age, race and sex, and associated with subsequent myocardial infarction and the risk of stroke within 5 years from the scan. Interestingly, the VFA had a significant association with the risk of developing MI (HR 1.31, p = 0.04) and Stroke (HR 1.46, p = 0.04) while BMI, weight, SFA and SMA had no association. This suggests the importance of incorporating SFA instead of BMI in cardiovascular risk models. By providing a better assessment of a person's cardiometabolic profile, CT-based body composition analysis shows great promise than established clinical parameters in improving pre-symptomatic detection and risk-stratification of patients vulnerable to adverse cardiovascular events and can augment the current risk prediction models. 3.7. Critical Illness CT body composition also plays a role in improving care in critically ill patients. Toledo et al. demonstrated that critically ill patients with sarcopenia have a lower 30-day survival, higher hospital mortality, and higher complication rates . Weijs et al. reported that sarcopenia on CT, during early stages of a critical illness, is strongly associated with a high risk of mortality in mechanically ventilated critically ill patients . Early identification of at-risk patients can help inform any necessary interventions for better outcomes in this critically ill population. 3.8. Contrast Dose Adjustment Iodinated contrast dosing is currently calculated based on total body weight, regardless of adipose and muscle content. However, patients with various body composition indexes, such sarcopenic obesity and athletes with high muscle content, can suffer from overdosing or underdosing. To alleviate this concern, CT body composition analysis has been shown to allow appropriate contrast dosing for each patient during the process of CT scanning . 4. CT Body Composition Analysis--Technical Considerations In this section, we discuss a number of technical considerations associated with the creation of computational methods for body composition analysis from CT. The first step in CT body composition analysis is identification of the most appropriate location for extracting body composition parameters, followed by the segmentation of the structures of interest. Although most use a single axial CT image slice, commonly located at the level of the L3 vertebra, some discussed the benefit of 3D-based analysis of CT body composition. Selecting a single slice for analysis simplifies the process of machine learning model development both by reducing the annotation burden required for training and validating the model, and reducing the complexity of the segmentation model itself. Furthermore, using a single slice eliminates potential variability in volumetry due to different spatial extents of scans, which may otherwise complicate analysis. However, single slice analysis is an imperfect proxy for overall body composition and small shifts in the location and angle of the chosen slice introduce significant variability in the measurements, particularly when slice selection is an automated process with its own error rate . By contrast, 3D analysis provides a more comprehensive characterization of body composition. Koitka et al. described a fully automated U-Net 3D neural network for volumetric body composition analysis using every fifth axial slice from abdominal CT scans to include multiple body regions . The network produced an excellent result with a Sorensen Dice coefficient of 0.9553 for segmentation and an intra-class correlation coefficient of 0.99 on tissue volumetry. Adipose tissue is especially sensitive to the angle cut of the slice image; therefore, its measurements can change dramatically from one slice to another. Although this is insignificant with population studies, it remains a bias for individual predictions and decision making especially when analyzing individuals over time . Shen et al. showed that in group studies, the use of an appropriate single slice analysis compared to volumetric body composition analysis requires 17% and 6% more subjects for estimating whole body muscle and fat, respectively . As such, with large scale investigations the use of a single slice analysis is appropriate since it decreases the cost and complexity of the analysis whereas the power of the study can easily be increased with a higher number of subjects. That said, for individual decision making and small-scale investigations, the use of 3D-based analysis remains a better choice as it provides a topographic information of various tissues and accurately distinguishes individual variability. The wealth of information obtained from 3D-based analysis introduced the concept of "extended body composition" that entails the measurement of multiple organs in the body and can identify the exact individual phenotype for better decision making and treatment selection . Because a single slice ca not provide the same detailed measurements of various tissues in the body, the choice of slice location becomes crucial for accurate estimation of whole body composition and predicting patient outcomes. Shen et al. showed that CT scans around the L3 lumbar vertebra have a strong association with the composition of subcutaneous fat tissue, visceral tissue and skeletal muscles in the body . Similarly, other studies also showed the accuracy of CT body composition analysis at the level of the third lumbar vertebra (L3) and have established a fully automated deep-learning system for L3 selection and body composition analysis . Others found an excellent correlation between T12 and L3 for estimating body composition and argued against the need for abdominal CT imaging specially when chest imaging is the only option available . Another recent study showed that the aggregation of skeletal muscle from different vertebral levels can better prognosticate and predict patient outcomes . Following the choice of location for CT body composition analysis comes the role of segmentation for biomarkers' extraction and analysis. Segmentation is executed either manually or by using automated segmentation techniques. For manual segmentation, trained image analysts or board-certified radiologists determine the region-of-interest, then select slices and distinguish each body compartment (muscle, visceral fat, subcutaneous fat) using anatomic knowledge and tissue-specific Hounsfield Unit ranges, then each slice is manually segmented . Since analysts must review and segment each selected slice, the process of manual CT body composition analysis becomes challenging in a large dataset as it requires time and expertise. This limits large scale investigations from being easily performed to expand its clinical value. To overcome this issue, the new mainstay technique for CT body composition analysis uses automated segmentation. Automated and accurate CT-scan segmentation of subcutaneous fat tissue, visceral fat tissue and skeletal muscle through artificial intelligence has been reported by multiple studies . Segmentation of multiple tissues can be obtained accurately using the same neural network which provides a faster computation speed of analysis with great accuracy. Studies have reported that the analysis of CT body composition takes around 15 min/scan for a human analysis, vs. <1 s/scan with the use of neural networks . This higher speed of analysis has made automated machine learning-based analysis the preferred method for large-scale investigations. Multiple studies have established automated machine learning algorithms for CT body composition analysis . Convolutional neural networks, and in particular the U-Net architecture, a well-established convolutional neural network (CNN) architecture for various medical image segmentation tasks, are the foundation of most methods. Notable examples are summarized below. Paris et al. established a new convolutional neural network (CNN), AutoMATiCA, for the segmentation of body composition that quantifies Skeletal Muscle (SM), intermuscular adipose tissue (IMAT), Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT) at the L3 vertebral body. The algorithm is a combination of four separate neural networks representing four different body compartments. Their results suggest that the algorithm may be generalizable to other populations for body composition calculation . Similarly, Hsu et al. developed a CNN model based on the U-Net architecture to quantify VAT, SAT and SM at the L3 level, with results consistent with the results obtained through manual segmentation . CNNs were also adapted for the development of automated segmentation in the work of Weston et al. The algorithm performs as well as expert manual segmentation . Bridge et al. developed a fully machine-operated algorithm to segment body composition from an abdominal CT scan . The method is broken down into two steps: (1) automatically identify and select a slice at L3 vertebral level from a full CT scan; and (2) segment body composition using a U-Net-based segmentation network. Dice score results were comparable between the AI-based segmentation and manual segmentation . They later extended the same approach to three thoracic levels (T5, T8, and T10) . Many other works have similarly demonstrated successful segmentation of body composition using automated approaches . With further advancement in this field, it became evident that there is a need to establish reference ranges and adjust for body composition values based on demographic variables such as age and gender. Recent studies performed population-scale CT body composition analysis and established age-, sex-, and race-specific reference curves for CT body composition metrics, analogous to reference ranges for the Z-scores used in DEXA scans . CT body composition reference parameters were found to be different across demographic groups, unlike the traditional reference ranges for BMI and weight metrics. In the same work, the derived CT body-composition Z-scores were found to be predictive of patient survival, further strengthening the value of CT body composition analysis in clinical care . 5. Future Directions CT imaging provides physicians with many datapoints, beyond the scan's clinical indications. The plethora of data available from CTs have sometimes been viewed unfavorably due to the concern of incidental findings triggering unnecessary workups. However, there has also been a concordant rise in interest of CT-based opportunistic screening due to its ability to identify at-risk patients and avoid future adverse events . While CT imaging allow for a whole range of body composition analyses, such as quantifying bone mineral density for osteoporosis or analyzing visceral fat for metabolic syndrome, the additional data are often not utilized in routine clinical care . This under-utilization was likely due to the labor-intensiveness of manual or semi-automated body composition analyses, especially when outside the clinical indication of the scan. With the recent innovations in fully automated methods of CT body composition analyses, this technique is now more readily accessible. Beyond the traditional CT body composition metrics presented in this article, the rise in fully automated AI-based methods for analyzing CT scans has further expanded our capabilities through additional organ-specific segmentation and detection . For instance, new methods are now available to determine abdominal organ volume for organomegaly , to stage liver fibrosis and to detect tumors , among others . These new methods present a paradigm shift in how clinicians will be able to use cross-sectional imaging for clinical management, revolutionizing the state-of-the-art care that patients can receive. Despite the promising potential that fully automated AI-based CT body composition analysis brings to the field, its application remains dependent on robust data analysis and large-scale investigations to validate its clinical importance and strengthen its value in the clinical arena. For instance, generating sufficiently large datasets across multiple sites and patient populations will be necessary and is one of the main obstacles to clinical implementation. This is now more feasible in today's era whereby a vast quantity of medical imaging data are generated daily and are accessible. In fact, the fully automated methods that have started to replace manual or semi-automated methods are making analyses less labor-intensive without compromising accuracy . Transitioning to a less labor-intensive approach will be crucial as it can be very challenging to generate the quantity of labeled data needed to both validate the approach and generalize to unseen data. Further efforts to increase the scale of investigations will, therefore, speed the era of implementing CT body composition analysis into routine clinical care. The clinical use of AI-based body composition analysis is not only dependent on large-scale data but also on heterogenous data that are reflective of our current populations. There is a need to establish international parameters and reference ranges that guide body composition analyses in order to produce generalizable solutions for both research and clinical use. Efforts to include population reference curves that are adjusted for several demographic variables have already begun to be implemented and have been shown to have a great correlation and equivalency to manual methods . Establishing international parameters is a key step in AI's large-scale use. As a community, we will need to use demographic-conscious adjustments to allow these methods to become effective and generalizable. The use of fully automated AI-based CT body composition analysis has great potential to revolutionize the future of medical care both within and outside of radiology. We envision that AI-based CT body composition analysis will play a crucial role in future treatment algorithms as they are widely implemented in every CT scan that is performed. Furthermore, the fully automated methods reduce the burden of analyzing clinical scans for incidentalomas and creates adequate risk assessment and prognostication that can better inform patient care. With the wider use of these automated systems, we will be able to generate more data and better be able to guide decision making, treatment planning, preoperative optimization, risk mitigation and ultimately improve patient outcomes by personalizing care without additional exposure to radiation. Despite the great promise that this new technique presents, the vast clinical potential of CT-based body composition analysis still faces many challenges prior to widespread implementation . For instance, there are legal liability issues with adopting fully automated AI systems. Who will be responsible for any errors that may harm patients? How can we ensure the privacy of the data? The commercialization of AI-based systems also raises ethical and equity concerns that have been covered in detail by a joint European and North American multi-society statement . There are multiple ways to address these issues. The implementation of AI-based body composition analysis can begin with common problems that have ample clinical data. Multi-center consortia such as the Opportunistic Screening Consortium in Abdominal Radiology (OSCAR) can be created to clinically implement automated systems. Furthermore, studies assessing the validity of these fully automated systems and adjusting for various demographic features will aid in their widespread and equitable implementation . Establishing body composition parameters and reference ranges based on age, sex and race is of utmost importance. It is also worth noting that there have been other new measures used to assess abdominal obesity. For instance, waist-to-height ratio (WHtR) has been shown to be a better screening tool than BMI and waist circumference for predicting cardiometabolic risk . Other measures such as body shape index (ABSI), conicity index (CI) and body roundness index (BRI) are newer central obesity indexes, and data show that some of those measures are better suited for specific populations . Other novel measures include the lipid accumulation product (LAP), which uses triglyceride and waist circumference; and the triglyceride-glucose index (TyG index), which utilizes fasting blood glucose and fasting triglyceride . Despite the usefulness of those measures, the literature is sparse on how they fare with CT-based body composition techniques. Given that these methods are cheap, future studies showing how they compare to CT-based body composition may be warranted, especially for predicting obesity-related metabolic disorders. Moreover, the use of these clinical data in conjunction with CT-based AI models will be an interesting direction, since their incorporation may aid in strengthening the analysis of body composition, which aims to better prognosticate patients for better clinical decision making and improved patients' outcomes. 6. Conclusions Advances in deep learning have led to excellent speed and accuracy in analyzing body composition on CT scan. Several fully automated CT-based body composition analyses have been developed and have shown great promise toward potential widespread investigations and clinical implementation. Multiple studies have shown the great potential of CT body composition analysis, especially in identifying patients at risk of complications. This can potentially improve the current risk prediction models and contribute to better clinical outcomes. CT body composition analysis can potentially help us personalize and tailor therapy by selecting safer alternative approaches to decrease complications and mitigate risk. Further studies are still needed to validate existing models and ensure their generalizability prior to widespread clinical use. Nonetheless, this review provides the current state of the art applications of CT body composition and suggests future directions and considerations to guide novel investigations and widespread clinical implementation. Author Contributions Conceptualization: T.E., K.T., A.M. and D.D.; investigation: T.E., K.T., A.M., D.D. and C.B.; writing--original draft preparation: T.E., K.T. and A.M.; writing--review and editing: T.E., A.M, C.B. and D.D.; supervision and project administration: D.D. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Population-scale machine learning-based CT body composition analysis for better risk prediction and prognostication. Body composition metrics can be extracted automatically from abdominal CT scans using machine learning-based segmentation approaches. Population scale CT body composition analysis can help establish age-, sex-, and race-specific Z-scores and reference curves for each metric. Patient-specific CT body composition metrics can be adjusted based on the reference curves prior to incorporation into risk prediction or prognostication models to aid in improved clinical decision-making. diagnostics-13-00968-t001_Table 1 Table 1 Summary of the standard metrics analyzed from CT body composition: Several metrics can be obtained from CT body composition analysis using unique ways of technical calculations. Slice identification is commonly done with the support of DenseNet or ResNeXt which is a multi-class natural image classification architecture that can help find the optimal slice. CT body composition analysis is then performed using a tissue segmentation model, commonly based on the U-Net model which is highly effective for medical image segmentation. Each metric has an important value in the clinical arena guiding risk prediction and prognostication with the potential to optimize patients outcomes. CT Body Composition Metrics Analysis Method Terminology of an Abnormal Value Clinical Applications Skeletal Muscle Index (SMI) (in cm2/m2) Localization and Segmentation of Skeletal muscle at the appropriate location (commonly L3) followed by calculation of the total skeletal muscle cross-sectional area divided by height squared, resulting in SMI calculation Sarcopenia Predict postoperative outcomes and the risk of various disease outcomes including cancer, cirrhosis, Inflammatory bowel disease, kidney disease, Severe COVID-19 and critical illness . Skeletal Muscle Density (in HU) After muscle segmentation, calculation of the mean muscle radiation attenuation of a muscle tissue excluding adipose tissue. This gives a muscle density expressed in Hounsfield units (HU). A higher attenuation indicates a low muscle density. Myosteatosis or low muscle quality or muscle fat infiltration Associated with poor metabolic function and worse perioperative morbidity and mortality. Can predict the risk of long-term oncological outcomes specially in those receiving treatments. It's also an independent predictor of mortality in necrotizing pancreatitis, COVID-19 and those undergoing hemodialysis . Adipose Tissue - Subcutaneous (SAT) - Visceral (VAT)(in cm) CT slice from an appropriate location is segmented and a region of interest(ROI) pass through the abdomen separating the abdominal wall from fat in a smooth manner due to the high difference in density and intensity, thus separating SAT from VAT. Automated analysis of a ROI that includes all similar grey pixels of VAT then results in a sizable area. - Visceral adiposity - Subcutaneous adiposity - Sarcopenic Obesity - Ratio of Visceral- fat (V/S) (cm3/cm) Predictor of major cardiovascular events, nonalcoholic fatty liver cirrhosis, kidney disease, cancer, metabolic syndrome, severe COVID-19 and mortality in asymptomatic screening population Bone Mineral Density (BMD) (in HU) The mean vertebral BMD is measured by placing a ROI commonly in L1-L3 vertebral bodies at the coronal, sagittal and axial images. Automated analysis of the cortical and trabecular area/BMD is obtained in HU. - Osteopenia - Osteoporosis Can accurately screen for osteoporosis and predict future risk of osteoporotic fractures. 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PMC10000510 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050972 diagnostics-13-00972 Article Evaluation of the Diagnostic Performance of a SARS-CoV-2 and Influenza A/B Combo Rapid Antigen Test in Respiratory Samples Dinc Harika Oyku Conceptualization Methodology Formal analysis Investigation Resources Data curation Writing - original draft Writing - review & editing 1 Karabulut Nuran Conceptualization Methodology Validation Investigation Data curation Writing - review & editing 2 Alacam Sema Conceptualization Methodology Validation Investigation Data curation Writing - review & editing 2 Uysal Hayriye Kirkoyun Conceptualization Methodology Validation Investigation Data curation Writing - review & editing 3 Dasdemir Ferhat Osman Investigation Resources Data curation Writing - review & editing 4 Onel Mustafa Validation Investigation Resources Data curation Writing - review & editing 3 Tuyji Tok Yesim Conceptualization Methodology Validation Investigation Resources Data curation Writing - review & editing 4 Sirekbasan Serhat Software Formal analysis Resources Data curation Writing - review & editing 5 Agacfidan Ali Validation Investigation Resources Data curation Writing - review & editing 3 Gareayaghi Nesrin Investigation Resources Data curation Writing - review & editing 6 Cakan Huseyin Software Formal analysis Investigation Resources Data curation Writing - review & editing 7 Eryigit Onder Yuksel Investigation Resources Data curation Writing - review & editing 8 Kocazeybek Bekir 4* Baraniak Anna Academic Editor 1 Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Bezmialem Vakif University, Istanbul 34093, Turkey 2 Department of Medical Virology, Basaksehir Cam and Sakura City Hospital, Istanbul 34480, Turkey 3 Department of Medical Microbiology, Istanbul Medical Faculty, Istanbul University, Istanbul 34093, Turkey 4 Department of Medical Microbiology, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul 34098, Turkey 5 Department of Medical Laboratory, Eldivan Vocational School of Health Services, Techniques Cankiri Karatekin University, Cankiri 18100, Turkey 6 Blood Center Istanbul Sisli Hamidiye Etfal Training and Research Hospital, Istanbul 34360, Turkey 7 Department of Biology and Microbiology, Faculty of Arts and Sciences, Canakkale Onsekiz Mart University, Canakkale 17100, Turkey 8 Health Vocational School Anesthesia, Istanbul Health and Technology University, Istanbul 34452, Turkey * Correspondence: [email protected] 03 3 2023 3 2023 13 5 97210 2 2023 01 3 2023 03 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). This study aimed to evaluate the performance characteristics of a rapid antigen test developed to detect SARS-CoV-2 (COVID-19), influenza A virus (IAV), and influenza B virus (IBV) (flu) compared with those of the real-time reverse transcription-polymerase chain reaction (rRT-PCR) method. One hundred SARS-CoV-2, one hundred IAV, and twenty-four IBV patients whose diagnoses were confirmed by clinical and laboratory methods were included in the patient group. Seventy-six patients, who were negative for all respiratory tract viruses, were included as the control group. The PanbioTM COVID-19/Flu A&B Rapid Panel test kit was used in the assays. The sensitivity values of the kit were 97.5%, 97.9%, and 33.33% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load below 20 Ct values. The sensitivity values of the kit were 16.7%, 36.5%, and 11.11% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load above 20 Ct. The kit's specificity was 100%. In conclusion, this kit demonstrated high sensitivity to SARS-CoV-2 and IAV for viral loads below 20 Ct values, but the sensitivity values were not compatible with PCR positivity for lower viral loads over 20 Ct values. Rapid antigen tests may be preferred as a routine screening tool in communal environments, especially in symptomatic individuals, when diagnosing SARS-CoV-2, IAV, and IBV with high caution. antigen tests influenza A influenza B rapid test SARS-CoV-2 This research received no external funding. pmc1. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus which caused coronavirus disease 2019 (COVID-19). The SARS-CoV-2 virus was first detected in Wuhan, China, at the end of 2019, and it was quickly announced as a pandemic by the World Health Organization (WHO) . The COVID-19 pandemic continues to have a major impact on healthcare and social systems worldwide . Vaccination remains the most promising approach to controlling the COVID-19 pandemic . However, because of the highly contagious nature of SARS-CoV-2, the lack of long-term immunity or a single, fully effective treatment against COVID-19 has resulted in a global pandemic, initiating a public health crisis that began in 2020 and remains active to this day . Respiratory tract infections are important public health threats worldwide. Among pathogens, viruses including rhinoviruses, respiratory syncytial viruses, adenoviruses, influenza viruses, and parainfluenza viruses are responsible for most upper respiratory tract infections and some lower respiratory tract infections . The SARS-CoV-2 which caused COVID-19 was recently added to the list of existing respiratory viruses. Influenza viruses and COVID-19 share very similar symptoms; however, the incubation period of SARS-CoV-2 is longer (2-14 days) than the flu caused by influenza viruses . There is growing concern about the possibility of a simultaneous outbreak of SARS-CoV-2 and influenza viruses, especially in the winter season . It can be difficult to distinguish COVID-19 from common viral infections based on clinical symptoms. Common viral infections exert non-specific clinical signs and symptoms, and it is important to differentiate COVID-19 from common viral infections to avoid misdiagnosis. A misdiagnosis may delay an accurate diagnosis and may result in further transmission throughout the community . Since the clinical and epidemiological features of COVID-19 are similar to those of influenza, optimal management of these respiratory tract infections is crucial, as they are predicted to continue to circulate together . Effective surveillance and diagnostic capacities must be provided, allowing us to monitor this and other respiratory viruses; this will form the basis of decisions regarding appropriate clinical management of the diseases involved . Seasonal influenza (influenza A virus (IAV), and influenza B virus (IBV)), especially IAV, affects up to 10% of the adult population and 20% of children annually and displays substantial morbidity . Early diagnosis of influenza viruses is critical, as current antiviral strategies are only effective in the early stages of the disease . Therefore, differential diagnoses of SARS-CoV-2, IAV, and IBV are important, ensuring effective patient management and treatment. Microbiologic diagnostic tests are used to differentiate between individuals with and without infectious diseases. Most infectious diseases have a "gold standard," or benchmark test, against which alternative diagnostic tests can be assessed . The two statistical criteria most frequently used to evaluate the performance of an alternative test relative to the gold standard are sensitivity and specificity . Sensitivity is a test's ability to correctly classify an individual as "diseased". Specificity is a test's ability to correctly classify a person as healthy. Sensitivity and specificity are inversely proportional, meaning that as the sensitivity increases, the specificity decreases . A high sensitivity rate is vital when the test is used to identify a serious but treatable disease (e.g., COVID-19 or flu). The positive predictive value determines how many of the positive findings are true positives. The negative predictive value determines how many of the negative findings are true negatives. If the values rise toward 100, the test approaches the gold standard . Molecular diagnostic tests based on the nucleic acid amplification test (NAAT) are the standard methods used to detect most viral respiratory tract infections . According to the Centers for Disease Control and Prevention (CDC) and the WHO, the "gold standard" for clinical diagnostic detection of SARS-CoV-2 is laboratory-based NAATs . The Infectious Diseases Society of America (IDSA) recommends rapid influenza molecular assays over rapid influenza diagnostic tests (RIDTs) for detecting influenza viruses in respiratory specimens of outpatients. The IDSA recommends using RT-PCR or other molecular assays to detect influenza viruses in respiratory specimens of hospitalized patients . However, this technology can be relatively labor intensive and time consuming; laboratories often require specific infrastructure and trained staff to perform these tests . This can become resource intensive; therefore, it may be beneficial to introduce automated or semi-automated molecular technologies that can be used at or near the point of care . Many antigen-specific point-of-care (POC) test methods have been invented and used separately to detect SARS-CoV-2 and influenza A and B . Although the CDC defines molecular tests for the detection of SARS-CoV2 and other respiratory infections such as IAV and IBV as the gold standard, it remains necessary to develop a multiplex POC device or rapid antigen tests for simultaneous early detection. Therefore, a POC kit or rapid antigen test that can detect multiple viruses from a single specimen using a single device would be very useful and would significantly decrease the turn-around time of the test. However, the WHO points out that the selection of tests should be based on proven performance (sensitivity and specificity) in the context of the intended use to optimize the testing strategy . Although rapid, point-of-care molecular tests can shorten the diagnostic time, their use may be limited due to the high cost of these tests . Many healthcare providers need a rapid test that is easy to use and inexpensive. Therefore, various rapid antigen tests have been developed to provide an alternative POC test with high sensitivity at a reduced cost . Today, combo antigen tests have been developed for rapid diagnosis of SARS-CoV-2 and influenza cases. Although the sensitivity and specificity of these newly introduced tests have been determined by studies performed by the manufacturers, they may differ in routine practice and in their use among the general population. Therefore, we aimed to investigate the sensitivity, specificity, negative predictive value, positive predictive value, and kappa (k) values of the SARS-CoV-2/IAV/IBV combo antigen test by detecting SARS-CoV-2 and IAV/IBV antigens qualitatively, using nasopharyngeal swab samples stored in appropriate conditions. 2. Materials and Methods Nasopharyngeal and throat swab samples, taken from patients who applied to the relevant departments of different centers (Istanbul University-Cerrahpasa; Basaksehir Cam, and Sakura Hospital, and Istanbul University) with clinical suspicion, were transferred to medical microbiology laboratories in viral nucleic acid buffer (VNAT) (BioNAT, Antalya, Turkey) for routine examinations. Samples that were positive for SARS-CoV-2, IAV, or IBV according to the rRT-PCR were included in our study as the samples of the patient group. We recorded their cycle of threshold (Ct) in which the viral load exceeded the detectable threshold. Archived samples were included as the control group; these samples were negative for common viral respiratory tract infections. The sample sizes of the patient and control groups were calculated using the G Power V.3.1.9.4 analysis program. As a result of this calculation, the sample size of 100 SARS-CoV-2, 100 influenza A, and 24 influenza B positive cases (the study group), and 76 negative cases for viral respiratory tract viruses (the control group) was deemed acceptable. Viral nucleic acid extractions from the nasopharyngeal and throat swab samples with suspicion of IAV and/or IBV were performed on a Zybio EXM 3000 (Zybio, Shenzhen, China) device using the Rapid Nucleic Acid Extraction Kit (Bioeksen, Istanbul, Turkey). The detection of viruses from the extracted nucleic acids was performed using the Respiratory RT-qPCR MX-24S panel Kit (Bioeksen, Istanbul, Turkey) on a Bio-Rad CFX96 Touch instrument (Hercules, CA, USA). Double Gene RT-qPCR kit (Bio-speedy, Bioeksen, Istanbul, Turkey) on a Bio-Rad CFX96 Touch instrument (Hercules, CA, USA) was used to detect SARS-CoV-2. The PanbioTM COVID-19/Flu A&B Rapid Panel (Nasopharyngeal) test is a rapid chromatographic immunoassay used for the qualitative detection of specific SARS-CoV-2, influenza A, and influenza B antigens present in human nasopharyngeal specimens, which is achieved using a single device. This lateral flow test (LFT) is based on immunochromatography and indicates the presence of the SARS-CoV-2 antigen with a colored line. The test contains a membrane strip precoated with antibodies specific to the nucleocapsid antigen of SARS-CoV-2, influenza A, and influenza B which was used to detect viruses. The PanbioTM COVID-19/Flu A&B Rapid Panel (Nasopharyngeal) test referred to as the combo test was performed according to the manufacturer's instructions . Before the research began, a total of 300 nasopharyngeal swab samples (100 SARS-CoV-2, 100 IAV, 24 IBV, 76 control) stored in a viral nucleic acid buffer (VNAT, BioNAT, Turkey) and under appropriate conditions were brought to room temperature. First, 300 mL of the vortexed sample was taken and mixed with the extraction buffer included in the test kit. It was vortexed for a few seconds to achieve homogenization. The nozzle cap was tight to the extraction buffer tube and four drops of the extracted sample were dispensed vertically into the sample well of the instrument. The results appeared as a band(s) of color after 15 min and were subsequently interpreted. All clinical specimens were studied in the Istanbul University-Cerrahpasa, Cerrahpasa Medical Faculty, Microbiology laboratory and Serology unit and the results were evaluated qualitatively. The test was conducted by two specialists who were blinded to avoid any observer bias. The results were interpreted as negative when only one band appeared on the C (control) line. The results were interpreted as positive when bands appeared on both the C and the tested lines (COVID-19, SARS-CoV-2; Flu A, influenza A; and Flu B, influenza B) . The test was interpreted as invalid if no band appeared or if the bands only appeared on the tested lines but not on the C line. To evaluate the level of agreement between rRT-PCR and LFA, statistical evaluation was performed by accepting the rRT-PCR method as a gold standard. Statistical analysis was conducted using the IBM SPSS 20.0 (IBM Corp., Armonk, NY, USA) package program. Frequency (n), percentage (%), and mean values were determined. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), likelihood, and accuracy values were calculated. Cohen's kappa coefficient was used to assess the level of agreement between rRT-PCR and an antigen test; concordance was based on a value >0.6. 3. Results The patient group was aged 1-81 and the control group was aged 1-76. There was no significant difference between the groups in terms of age and gender (p < 0.05). The sensitivities of LFA-based immunochromatographic card tests targeting SARS-CoV-2, IAV, and IBV antigens were evaluated in samples with viral loads <=20 Ct (Ct range: 6-20) and >20 Ct (Ct range: 21-35). When the PanbioTM COVID-19/Flu A&B Rapid Panel test was evaluated for SARS-CoV-2, the sensitivity value was 97.5% in samples with a viral load lower than 20 Ct. In samples with a viral load above 20 Ct values, the sensitivity value was 16.7%. When evaluated regardless of viral load, it was shown that the sensitivity, specificity, positive predictive value, and negative predictive values were 49%, 100%, 100%, and 60.3, respectively. When IAV cases were evaluated, the sensitivity value was 97.9% in samples with a viral load of lower than 20 Ct, and 36.5% in samples with a viral load above 20 Ct. When evaluated regardless of viral load, it was shown that the sensitivity, specificity, positive predictive value, and negative predictive values were 66%, 100%, 100% and 69.1, respectively. When IBV cases were evaluated, the sensitivity was 33.3% in samples with a viral load of below 20 Ct, while the sensitivity was 11.1% in values above 20 Ct. When evaluation was carried out regardless of viral load, the sensitivity, specificity, positive predictive value, and negative predictive values were 25%, 100%, 100%, and 80.9, respectively. The sensitivity, specificity, PPV, NPV, and kappa values of the kit tested are given in Table 1. The positivity and negativity levels according to the Ct values of SARS-CoV-2, IAV, and IBV cases are shown in Figure 2, Figure 3 and Figure 4. In the analysis performed to evaluate the level of agreement between rRT-PCR, which is the gold standard method in the diagnosis of COVID-19, and the rapid antigen test used, Cohen's kappa coefficient was 0.98 for the Ct below 20. For the diagnosis of IAV and IBV, Cohen's kappa coefficient was 0.98 and 0.46 for the Ct below 20, respectively (Table 1). When Ct values were evaluated according to ROC curve analysis, significant results were obtained for SARS-CoV-2, IAV, and IBV at 20, 22, and 15 Ct values, respectively (p < 0.05). The relationship between sensitivity and specificity is given in Table 2 based on ROC curve analysis. 4. Discussion In our study, we performed a sensitivity analysis using the PanbioTM COVID-19/Flu A&B test, which is an LFA-based rapid antigen test and compared the performance of the kit with the rRT-PCR method used to detect SARS-CoV-2, IAV, and IBV. Sensitivity below 20 Ct was 97.5%, 97.9%, and 33.3% for SARS-CoV-2, IAV, and IBV, respectively. Above 20 Ct, the sensitivity was 16.7%, 36.5%, and 11.1% for SARS-CoV-2, IAV, and IBV, respectively. The specificity of the test was 100% for all viruses. Ct values are inverse to the viral RNA copy numbers; therefore, a lower Ct value indicates a high viral load . However, studies have reported that the time from symptom onset and Ct values affect the sensitivity of rapid antigen tests used to detect the presence of SARS-CoV-2 in nasopharyngeal samples . This study demonstrated that the sensitivity of the rapid antigen test is higher at a lower Ct value. Several factors that may affect the sensitivity of the rapid antigen tests include methodology differences, the severity of the infection, and the sample types. Most of the studies included stored specimens and had no information related to the time from symptom onset. Oh et al. evaluated the sensitivity of the STANARD Q COVID-19 Ag test with RT-PCR in diagnosing COVID-19 and concluded that the differences mainly originated from different methods of RT-PCR. The Ct values were not comparable between the RT-PCR tests. Lee et al. made sure to use fresh swab specimens and correctly recorded the time from symptom onset values. The sensitivity of rapid antigen tests is known to decline when using stored specimens, as seen in the study of Parvu et al. . The sensitivity of the rapid antigen test in their study declined from 75.3% (in fresh specimens) to 70.9% (in frozen specimens). Meanwhile, Igloi et al. reported that the sensitivity of their Q Ag rapid antigen test for COVID-19 increased for specimens collected within 7 days of symptom onset and the sensitivity of the Q Ag rapid antigen test increased to 99.1% when the Ct value of the E gene was <25. In a similar study conducted by Kim et al. , the Ag test sensitivity increased with Ct <= 30 and for specimens collected 1 to 5 days post-symptom onset. They suggested that Ct values of rapid-antigen-test-positive specimens may not accurately indicate patient status, while Ct values may vary with the specimen quality and may not correlate with the presence of SARS-CoV-2 antigens. Therefore, the performance of the rapid antigen test was evaluated by grouping the samples that were found to be positive for SARS-CoV-2, IAV, and IBV in the symptomatic period by rRT-PCR as <=20 Ct and >20 Ct. For SARS-CoV-2 and IAV, the sensitivity of the rapid antigen test was 97.5% and 97.9%, respectively, when the Ct value was below 20, and a very significant decrease in sensitivity was detected when the Ct value was above 20. For IBV, the same result with SARS-CoV-2 and IAV was obtained when the kit's sensitivity was evaluated according to the Ct values. However, despite the low Ct value in the rapid antigen test, a very low sensitivity rate was found for the diagnosis of IBV. When the compatibility between the PanbioTM COVID-19/Flu A&B rapid panel test and rRT-PCR for the detection of SARS-CoV-2, IAV, and IBV viruses was evaluated, different results were obtained by the viruses. SARS-CoV-2 and IAV showed strong coherence with Cohen's kappa value (0.98), which was an almost perfect match. In contrast, IBV showed moderate coherence. The rapid antigen test used in the present study may be preferred as an alternative to rRT-PCR in the early phase diagnosis of SARS-CoV-2 and IAV since it has a sensitivity of over 97% and a specificity of 100%. In a study conducted by Widyasari et al. in which the performance of a COVID/FLU combo antigen test was compared to an rRT-PCR SARS-CoV-2, IAV, and IBV combo antigen test, the sensitivity values were 93.1%, 92.2%, and 91.18%, respectively. The researchers used a STANDARD Q COVID/FLU Ag Combo test (Korea), a rapid chromatographic immunoassay used for the qualitative detection of specific SARS-CoV-2, influenza A, and influenza B antigens present in human nasopharyngeal specimens. The test is performed using a single device. They reported a Cohen's kappa index value of 0.940 and a Cohen's kappa value of 0.941 and 0.928 for influenza A and influenza B, respectively. These values indicated substantial agreement between the Ag Combo test and rRT-PCR. The researchers also restricted the duration from symptom onset and the Ct value of RdRp for SARS-CoV-2 and analyzed the sensitivity of the Q Antigen combo test used to detect the presence of SARS-CoV-2 in the samples according to the different durations from symptom onset and Ct values. The sensitivity of the Q Ag combo test reached up to 100% within a week (0-6 days). However, when used to assess samples collected at the duration from symptom onset > 7 days, the sensitivity of the Q Antigen combo test decreased significantly. When the sensitivity values of samples with Ct values of RdRp <= 20 were evaluated, the sensitivity of the combo antigen test was higher than the samples with Ct values between 20 and 30. They concluded that the Q Antigen combo test has a very high sensitivity and specificity for the detection of SARS-CoV-2, influenza A, and influenza B in a single sample with a single device. They considered the Q Antigen combo test a considerably useful tool for the detection and differentiation of SARS-CoV-2, influenza A, and influenza B, providing benefits such as cost-effectiveness, easy handling, and the ability to detect multiple viruses using a single device with a short turnaround time . In addition, it has been shown that symptom onset is also effective in the diagnostic performance of rapid antigen tests; the sensitivity of the Q Antigen combo test was 100% when the samples were collected within one week (0-6 days). As expected, when the specimens were collected at >7 days, the sensitivity of the Q Antigen combo test decreased significantly . Similarly, the sensitivity, specificity, positive predictive, and negative predictive values of a different combo antigen test (newly developed antigen test QuickNavi-Flu+COVID-19 Antigen test) for the detection of SARS-CoV-2 from nasopharyngeal samples were 80.9%, 99.8%, 98.7%, and 95.8%, respectively. The sensitivity reached 88.3% in symptomatic cases. However, the fact that the sensitivity was over 95% for Ct values below 20 regardless of symptoms, and for Ct values 25-29, the sensitivity decreased to 46.2%. The sensitivity of their kit decreased with increasing Ct values. For Ct values >= 30, the sensitivity also decreased to 25.0% in asymptomatic cases. The researchers concluded that the QuickNavi-Flu+COVID19 Antigen test indicated a desirable sensitivity and specificity for SARS-CoV-2 detection using both nasopharyngeal and anterior nasal samples, especially in symptomatic patients. The sensitivity, specificity, positive predictive values, and negative predictive values of the studied kit were compatible with <=20 Ct results, except those relating to influenza B. The sensitivity values differed between symptomatic and asymptomatic cases in the 25-29 Ct value range. For the studied nasopharyngeal and anterior nasal specimens, the median Ct values were lower for the symptomatic cases compared to the asymptomatic cases. This may have been caused by the difference in sensitivities between the symptomatic and the asymptomatic cases in this Ct range . In our previous study, SARS-CoV-2 RNA-positive respiratory tract samples with viral loads of <25 Ct (cycle of threshold), 25-29 Ct, 30-35 Ct, and <35 Ct, a total of 205 patient samples were studied by the lateral flow method using twelve commercial rapid antigen tests from different companies, and their performance was evaluated. We also reported that the sensitivities of the kits decreased in proportion to the increase in Ct values . Therefore, the data obtained from different studies are compatible with our study, except for that of influenza B. As a result of the Roc curve analysis of this study, we showed that the influenza B test is more sensitive when detecting patients with a Ct value of 15 and below (p = 0.03). For SARS-CoV-2 and IAV, we also showed that it was more sensitive when detecting patients with a Ct of 20-22, which is consistent with other study results (p < 0.00, p: 0.02, respectively). Therefore, it should be considered that negative antigen results may be associated with viral load in patients with suspected symptoms. COVID-19 and influenza have similar symptoms, and these similarities make differential diagnosis very difficult. The PanbioTM COVID-19/Flu A&B Rapid test was developed to detect SARS-CoV-2, influenza A, and influenza B using nasal or oropharyngeal swabs and the total test time is about 15-20 min. Thus, it is possible to identify infected individuals very early and to take precautions to prevent the spread of the three viruses detected by this combo rapid antigen test. Firstly, it is important to understand the meaning of Ct values. The Ct values show the number of amplification cycles required for the target gene to exceed a threshold level in an rRT-PCR assay . The Ct values are correlated with SARS-CoV-2 accumulation and the clinical presentation of patients. These values may be regarded as a surrogate for the determination of viral load . Our study has several limitations. We included patients who presented to the hospital with clinical symptoms, but patients who were not clinically suspected to be referred to hospitals were excluded from the study. The patients were not recruited during the COVID-19 outbreak, which led to a drastic decline in influenza transmission, and there may be clinical differences in symptoms of patients with COVID-19. Additionally, laboratory parameters may be different due to the predominant strains of the SARS-CoV-2 virus and influenza virus strains circulating at different time points. Another limitation of our study is the small number of patients diagnosed with influenza B among the included cases. Sample insufficiency for this virus might have negatively affected the sensitivity of the test. However, one of the factors affecting sensitivity might be the antigenic target in the LFA-based test. Although SARS-CoV-2, IAV, and IBV share many symptoms, they are also highly contagious. Since the differential diagnosis of these viruses is difficult due to non-specific symptoms, it is necessary to develop clinically validated LFA-based antigen tests with high sensitivity and specificity rates that enable the differentiation of SARS-CoV-2 and influenza viruses in a single test. Antigen tests are advantageous compared to molecular methods in that they give faster results, are easier to use, and have lower costs. On the other hand, we used specimens of patients that were positive for SARS-CoV-2, IAV, and IBV in the symptomatic period. The specificity of the PanbioTM COVID-19/Flu A&B test was 100% for SARS-CoV-2, influenza A, and B, as reported in many similar studies . A diagnostic test with very high specificity will rule out healthy individuals and will also eliminate false-positive results. This means additional tests will not be used for false-positive results. In conclusion, this kit demonstrated high sensitivity to SARS-CoV-2 and IAV for viral loads below 20 Ct values, but the sensitivity values were not compatible with PCR positivity for lower viral loads over 20 Ct values. However, the results of this test should be approached with extreme caution because the PanbioTM COVID-19/Flu A&B Rapid Panel test kit is prone to produce false negatives for the higher Ct values in response to low viral loads during the detection of SARS-CoV-2, INF-A, and INF-B. Rapid antigen tests may be preferred as a routine screening tool in communal environments, especially in symptomatic individuals, when diagnosing SARS-CoV-2, IAV, and IBV with high caution. There is a clear correlation between lower Ct values and the presence of clinical signs, which is especially evident in symptomatic patients, but the diagnostic value of these rapid antigen tests will remain controversial unless their sensitivity reaches a satisfactory level for non-symptomatic patients with high Ct values in rRT-PCR. However, it is very important to perform these tests in the first days of symptom onset (the early stage) when the viral load is high. Author Contributions Conceptualization, H.O.D., N.K., S.A., H.K.U., Y.T.T. and B.K.; Methodology, H.O.D., N.K., S.A., H.K.U., Y.T.T. and B.K.; Software, S.S. and H.C.; Validation, N.K., S.A., H.K.U., M.O., Y.T.T., A.A. and B.K.; Formal analysis, H.O.D., S.S., H.C. and B.K.; Investigation, H.O.D., N.K., S.A., H.K.U., F.O.D., M.O., Y.T.T., A.A., N.G., H.C. and O.Y.E.; Resources, H.O.D., F.O.D., M.O., Y.T.T., S.S., A.A., N.G., H.C. and O.Y.E.; Data curation, H.O.D., N.K., S.A., H.K.U., F.O.D., M.O., Y.T.T., S.S., A.A., N.G., H.C. and O.Y.E.; Writing-original draft, H.O.D.; Writing-review & editing, H.O.D., N.K., S.A., H.K.U., F.O.D., M.O., Y.T.T., S.S., A.A., N.G., H.C., O.Y.E. and B.K.; Visualization, B.K.; Supervision, B.K.; Project administration, B.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Clinical Research Ethics Committee (protocol code: 622465 and date of approval: 17 February 2023). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper. Data Availability Statement Data of this study are available from the corresponding author upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The PanbioTM COVID-19/Flu A&B Rapid Panel (nasopharyngeal) test results. The control line (C) begins to appear around 3-4 min following the application of the sample-buffer mixture on the device. The other line will also appear next to the test lines when the samples contain antigens of influenza B (Flu B line), influenza A (Flu A line), or SARS-CoV-2 (COVID-19 line). One line on the C marker indicates that the test is negative. Two lines--one on C and one on either Flu-B, Flu-A, or COVID-19 markers--indicate that the test is positive either for SARS-CoV-2, influenza A, or influenza B. Figure 2 Comparison of SARS-CoV-2 rapid antigen test results in rRT-PCR Ct values. Figure 3 Comparison of influenza A rapid antigen test results in rRT-PCR Ct values. Figure 4 Comparison of influenza B rapid antigen test results in rRT-PCR Ct values. diagnostics-13-00972-t001_Table 1 Table 1 Evaluation of the diagnostic performance of lateral flow tests study on nasopharyngeal swab samples of patient groups with viral loads of <=20 Ct and >20 Ct diagnosed with SARS-CoV-2, IAV, and IBV via rRT-PCR. Sensitivity (%) Specificity (%) PPV (%) NPV (%) Kappa SARS-CoV-2 <=20 Ct (n = 40) 97.5 100 100 98.7 0.98 >20 Ct (n = 60) 16.7 100 100 60.3 0.18 Total (n = 100) 49 100 100 59.8 0.45 IAV <=20 Ct (n = 42) 97.9 100 100 98.7 0.98 >20 Ct (n = 58) 36.5 100 100 69.7 0.41 Total (n = 100) 66 100 100 69.1 0.63 IBV <=20 Ct (n = 15) 33.3 100 100 88.4 0.46 >20 Ct (n = 9) 11.1 100 100 90.5 0.18 Total (n = 24) 25 100 100 80.9 0.34 PPV: Positive predictive value, NPV: negative predictive value, Ct: cycle threshold, and INF: influenza. diagnostics-13-00972-t002_Table 2 Table 2 Evaluation of diagnostic performance according to Ct values of tests including ROC curve analysis. ROC Curve Parameters SARS-CoV-2 Influenza A Influenza B AUC 0.928 0.907 0.801 95% CI (min-max) 0.877-0.980 0.849-0.94 0.522-1 p <0.001 0.029 0.03 Cut-off 20 22 15 Sensitivity (%) 79.6 81.8 83.3 Specificity (%) 98 94.1 88.9 AUC: Area under the curve and CI: confidence interval. 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PMC10000511 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050831 diagnostics-13-00831 Case Report Subcapsular Biloma following Endoscopic Retrograde Cholangiopancreatography and Endoscopic Biliary Sphincterotomy: A Case Report with a Mini Review of Literature Pentara Natalia Valeria 1* Ioannidis Aristidis 2 Tzikos Georgios 2 Kougias Leonidas 1 Karlafti Eleni 34 Chorti Angeliki 2 Tsalkatidou Despoina 2 Michalopoulos Antonios 2 Paramythiotis Daniel 2 de Haas Robbert J. Academic Editor 1 Department of Radiology, AHEPA General University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece 2 1st Propaedeutic Department of Surgery, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece 3 1st Propaedeutic Department of Internal Medicine, AHEPA Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece 4 Emergency Department, AHEPA University General Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece * Correspondence: [email protected] 22 2 2023 3 2023 13 5 83129 1 2023 13 2 2023 17 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). A biloma is a loculated, extrahepatic, intra-abdominal bile collection. It is an unusual condition with an incidence of 0.3-2% and is usually a result of choledocholithiasis, iatrogenic injury or abdominal trauma causing disruption to the biliary tree. Rarely, it will occur spontaneously, resulting in spontaneous bile leak. We herein present a rare case of biloma as a complication of endoscopic retrograde cholangiopancreatography (ERCP). A 54-year-old patient experienced right upper quadrant discomfort, following ERCP, endoscopic biliary sphincterotomy and stenting for choledocholithiasis. Initial abdominal ultrasound and computed tomography revealed an intrahepatic collection. Percutaneous aspiration under ultrasound guidance of yellow-green fluid confirmed the diagnosis, indicated infection and contributed to effective management. Most likely, a distal branch of the biliary tree was injured during the insertion of the guidewire through the common bile duct. Magnetic resonance image/magnetic resonance cholangiopancreatography contributed in the diagnosis of two seperate bilomas. Even though post ERCP biloma is an unusual complication, differential diagnosis of patients with right upper quadrant discomfort following an iatrogenic or traumatic event should always include biliary tree disruption. A combination of radiological imaging for diagnosis and minimal invasive technique to manage a biloma can prove to be successful. biloma bile leakage endoscopic retrograde cholangiopancreatography percutaneous drainage This research received no external funding. pmc1. Introduction The term "biloma" was first introduced by Gould and Patel in 1979 in order to describe a loculated, encapsulated, extrahepatic biliary collection of bile . However, the term was extended to include any intra-abdominal bile collection, external to the biliary tree and although many of them are encapsulated, the current definition does not require it to be as such . Biloma is a rare condition with an incidence of 0.3% to 2.0% and is usually presented in patients aged 60 to 70 years old . Biloma formation is most commonly a result of choledocholithiasis, iatrogenic injury and abdominal trauma, causing disruption to the biliary tree and furthermore bile leakage into the peritoneal cavity . Although it is not common, bile leakage could also occur spontaneously, known as spontaneous bile leak (SBL), which is usually a diagnosis of exclusion . ERCP is a combined endoscopic and fluoroscopic operation, incorporated with contrast material injection, allowing for radiologic imaging and if necessary therapeutic interventions. Some ERCP indications are obstructive jaundice, biliary or pancreatic ductal system condition treatment or biopsy, pancreatitis of unknown cause, nasobiliary drainage and biliary stenting among many others . ERCP complications include post-ERCP pancreatitis (PEP) with a frequency of 3.5% which is the most common complication, and infections, such as cholangitis, gastrointestinal bleeding and duodenal or biliary perforations . 2. Case Report Our patient, a 54-year-old female, had a history of chololithiasis after an ultrasound exam of the abdomen thirty years ago, due to non-specific abdominal pain, which revealed multiple echogenic shadowing stones within the gallbladder. During a recent visit to her personal physician, she was advised to have a magnetic resonance image (MRI) scan in order to evaluate the current state of her reported history of chololithiasis. MRI revealed multiple calculi in the gallbladder as well as within the common bile duct. The patient had a surgical history of right leg amputation due to an accident and was not taking any medication. The diagnosis was followed by ERCP. During this procedure, a guidewire under fluoroscopy was passed into the common bile duct, and contrast was injected, highlighting multiple filling defects (>4). Endoscopic papillary balloon dilation of the common bile duct was performed resulting in the gradual exit of bile duct stones. Subsequently, a plastic stent 10 fr-9 cm was placed in the common bile duct to ensure bile drainage . During the first day of her hospitalization, the patient started complaining of pain radiating to her back. Ultrasound examination of the abdomen revealed a collection of fluid with thickened hyperechoic walls compressing the liver parenchyma. The possibility of a tear of the biliary tree was considered. An abdomen computed tomography (CT) scan revealed a well-circumscribed subcapsular collection (5.7 x 3.5 cm) with an air-fluid level in segment VII of the liver, containing a contrast agent that was previously used in ERCP. It was firstly attributed to an intrahepatic biloma as a complication of the previously performed ERCP. Laboratory workup showed elevated white cell count (13,630 per microliter) and CRP at 231.3 mg/L. However, liver function tests (LFTs) remained within normal levels during the first two days: alanine transaminase(ALT) of 20.0 IU/L, aspartate transaminase (AST) of 32 IU/L, g-GT of 10.0 IU/L, and bilirubin of 0.39 IU/L. Antibiotic treatment was initiated, Piperacillin/Tazobactam (4 + 0.5) g x 4 and Amikacin 375 mg x 2. Percutaneous drainage of the biloma was scheduled, as it was deemed necessary in order to fully manage this complication. On the third day of admission, a CT exam was repeated, revealing an increase in size of the forenamed subcapsular collection, as well as a rounded water-attenuation fluid collection with an air-fluid level in contact with the previous one. Differential diagnosis included an extension of the already existing collection or a completely different one . Percutaneous drainage of the biloma was performed under ultrasonography guidance. After the injection of 15 cc of lidocaine 1%, the collection was punctured through an intercostal approach with an 18 G Chiba needle. Aspiration of yellow-green fluid confirmed the diagnosis and the correct placement of the needle. An Amplatz superstiff guide wire was then inserted through the needle, and finally, an 8 F pigtail drainage catheter was placed in the collection. Injection of contrast was performed through the pigtail catheter, which opacified the subcapsular collection. Contrast material leak in the peritoneal cavity was not identified . Reduced drainage throughout the next days (ninth to twelfth day of admission), a repetitive CT scan and a magnetic resonance image/magnetic resonance cholangiopancreatography (MRI/MRCP) revealing minimal change in the size of the biloma strengthened the case of two separate bilomas . Percutaneous drainage was once more performed under ultrasound guidance, inserting a second 8 Fr pigtail drainage catheter, which passed through the first biloma and ended inside the second one. Contrast injection indicated no communication between the two bilomas . A sample of the drained fluid was collected, followed by laboratory analysis indicating E. coli infection. Follow-up CT showing both drainage catheters revealed capsular ring enhancement, designating inflammation and abscess formation. However a significant reduction in the size of the bilomas was detected . Over time, the amount of bile drainage decreased. The patient was discharged from the hospital after twenty-two days of hospitalization and came back seven days later in order to remove the two pigtails based on a follow-up CT, which revealed further size reduction of the bilomas and of the two pigtails' drainage, which stopped. Thirty-eight days later, the patient came back in order to have a cholocystectomy. She had an uncomplicated postoperative course and was discharged from the hospital. Twenty days after her release, she underwent successful ERCP in order to remove the stent that was previously placed in the common bile duct and has been carefully monitored ever since. 3. Discussion There are only some cases reported in the literature of this complication after ERCP . A study by Enns et al. of ERCP-related perforations showed that the incidence of ERCP-related perforations is less than 1%. Clinical presentation is variable, ranging from an incidental finding on imaging to right upper quadrant discomfort, abdominal fullness, nausea, vomiting, fever, jaundice, peritonitis without fever, or even severe biliary sepsis . Reported causes of biloma formation following ERCP consider modalities of the endoscopic procedure, meaning the injection of contrast medium through the catheter inducing high pressure in proximal biliary ducts, the modification of the biliary epithelium by persistent cholangitis, or both . In our case, the most likely scenario is that a distal branch of the biliary tree was injured by the tip of the guidewire. Its formation is thought to be via two mechanisms based on the pace of bile leakage. Secondary to slow leakage bile acids, which are known to have detergent and tissue destroying properties, cause mild inflammation in the neighboring abdominal tissues or liver parenchyma, prompting fibrosis and encapsulation. Additionally, rapid bile leaks could result in biliary peritonitis, where encapsulation may be present as a result of inflammatory adhesions . Taking into account bilomas' variable clinical presentation, radiological imaging was shown to be the foundation of diagnosis. Ultrasound exam, due to its non-invasiveness and rapid evaluation, is usually the primary medical imaging, revealing a wide range of findings from anechoic, well-circumscribed collections to large, complex fluid with multiple fine internal septa, but most frequently a cystic lesion . Smaller bilomas can be missed, making abdominal CT the optimal method for its identification, usually showing a well-circumscribed, hypo-attenuated collection with clear margins and a density of less than 20 Hounsfield units . Even though CT imaging has the benefit of providing us with useful information, such as the biloma's location and surrounding structures, it is not the most effective diagnostic imaging modality to distinguish between differential diagnoses, such as postoperative hematoma, seroma, abscess, lymphocele, liver cyst or pseudocyst, making MR imaging and MRCP in some cases required . A biloma typically produces a variable signal on T1-weighted images and high signal intensity on T2-weighted images, corresponding to the signal intensity of gallbladder fluid . High T1 signal intensity and low T2 signal intensity material within the collection indicates concentrated bile layering . MRI combined with MRCP provides convenient anatomical details of the extrahepatic bile ducts, sometimes identifying the location of the leakage . Rim enhancement could be present as a consequence of reactive inflammation . Hepatobiliary cholescintigraphy, which is a diagnostic nuclear medicine procedure using a radiotracer called Tc-99 m iminodiacetic acid to evaluate the biliary system, also known as HIDA scan, is considered an exceptionally effective radiological modality. Its profitability is based on the fact that the radiotracer follows the bilirubin metabolic pathway and is eventually excreted into the bile ducts, making it a beneficial tool in the diagnosis of gallbladder and biliary tree pathology . The HIDA scan can reveal whether an active biliary leak is present and also helps to guide additional therapy . Single positron emission computed tomography (SPECT) could also provide helpful details concerning the location of a possible active leak . Invasive imaging techniques, such as ERCP and PTC, are useful where management is needed . Imaging guided percutaneous transhepatic biliary drainage has both diagnostic and therapeutic roles by determining the proximal extent of biliary duct injury and providing fluid for laboratory analysis to confirm the diagnosis which is often required. In our case, percutaneous drainage of the biloma was performed under US guidance, preventing surgery. A study by Fatima et al. concluded that most biliary perforations can be managed nonoperatively, and when operative treatment is required, the mortality rate increases. Nonetheless, further surgical management may be needed if percutaneous drainage is unsuccessful, multiloculated lesions are present or bile leaks are ongoing . When it comes to blood testing, results vary from patients with no abnormalities to raised inflammatory markers and abnormal liver function tests. When a biloma is infected, blood cultures may unveil Gram-negative bacteremia. The most typical organisms found in the microbiological culture of biloma fluid are Enterobacteriaceae, followed by Enterococcus species . Author Contributions Conceptualization, N.V.P. and A.I.; methodology, A.C. and G.T.; software, N.V.P.; investigation, G.T. and D.T.; resources, N.V.P. and D.T.; data curation, A.C. and D.T.; writing--original draft preparation, N.V.P. and L.K.; writing--review and editing, L.K. and E.K.; visualization, A.I.; supervision, D.P.; project administration, A.I., D.P. and A.M. was the Director of the Department of Surgery and provided his permission for this study. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical review and approval were waived for this study due to Informed consent was obtained from the patient and all sensitive data was made anonymous. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient to publish this paper. Data Availability Statement The data and materials/figures used in the current study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Endoscopic retrograde cholangiopancreatography fluoroscopy images. (a) Cannulation of the common bile duct and cholangiogram which shows intraluminal filling defects consistent with stones (green arrows). (b) Filling defects in the gallbladder (green arrows). (c) Biliary stent deployed (green arrows). Figure 2 (a,b) Computed tomography scan of the abdomen: (a) axial, (b) sagittal and (c) coronal section showing a subcapsular collection as well as a rounded water-attenuation fluid collection with an air-fluid level in contact with the previous one (green arrows). Figure 3 Contrast opacification of the subcapsular collection through the 8F pigtail catheter (green arrow). Previously placed stent in the common bile duct (black arrow). Figure 4 (a) Abdominal computed tomography scan, (b) magnetic resonance image/T2-weighted image of the abdomen and (c) magnetic resonance cholangiopancreatography of the abdomen revealing two separate bilomas. Figure 5 (a,b) Contrast opacification of the subcapsular collection through the 8F pigtail. Figure 6 Computed tomography of the abdomen (a) axial (b) coronal and (c) sagittal section showing both pigtail drainage catheters as well as a capsular ring enhancement of the biloma (green arrow). Reduction in size of the two bilomas can also be seen. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Gould L. Patel A. Ultrasound detection of extrahepatic encapsulated bile: "Biloma" Am. J. Roentgenol. 1979 132 1014 1015 10.2214/ajr.132.6.1014 108953 2. Copelan A. Bahoura L. Tardy F. Kirsch M. Sokhandon F. Kapoor B. Etiology, Diagnosis, and Management of Bilomas: A Current Update Tech. Vasc. Interv. Radiol. 2015 18 236 243 10.1053/j.tvir.2015.07.007 26615164 3. Faisaluddin M. Bansal R. Iftikhar P.M. Arastu A.H. A Rare Case Report of Biloma After Cholecystectomy Cureus 2019 11 e5459 10.7759/cureus.5459 31656709 4. Balfour J. Ewing A. Hepatic Biloma StatPearls [Internet] StatPearls Publishing Treasure Island, FL, USA 2022 5. Yadav A. Condati N.K. Mukund A. Percutaneous Transhepatic Biliary Interventions J. Clin. Interv. Radiol. ISVIR 2018 2 27 37 10.1055/s-0038-1642105 6. Yousaf M.N. D'Souza R.G. Chaudhary F. Ehsan H. Sittambalam C. Biloma: A Rare Manifestation of Spontaneous Bile Leak Cureus 2020 12 e8116 10.7759/cureus.8116 32542169 7. Meseeha M. Attia M. Endoscopic Retrograde Cholangiopancreatography StatPearls Publishing Treasure Island, FL, USA 2022 8. Kwon C. Song S.H. Hahm K.B. Ko K.H. Unusual complications related to endoscopic retrograde cholangiopancreatography and its endoscopic treatment Clin. Endosc. 2013 46 3 10.5946/ce.2013.46.3.251 23424711 9. Dupas J.L. Mancheron H. Sevenet F. Delamarre J. Delcenserie R. Capron J. Hepatic subcapsular biloma. An unusual complication of endoscopic retrogade cholangiopancreatography Gastroenterology 1988 94 1225 1227 10.1016/0016-5085(88)90017-0 3280390 10. Alkhateeb H.M. Aljanabi T.J. Al-azzawi K.H. Alkarboly T.A. Huge biloma after endoscopic retrogade cholangiopancreatography and endoscopic biliary sphincterotomy Int. J. Surg. Case Rep. 2015 16 7 11 10.1016/j.ijscr.2015.08.039 26402876 11. Jafari A. A rare case of hepatic subcapsular biloma after laparoscopic cholecystectomy and subsequent endoscopic retrograde cholangiopancreatography Caspian J. Intern. Med. 2018 9 198 200 29732041 12. Szary N.M. Al-Kawas F.H. Complications of endoscopic retrograde cholangiopancreatography: How to avoid and manage them Gastroenterol. Hepatol. 2013 9 496 504 13. Harshna V.V. Ronald S.A. Imaging and Intervention of Biliary Leaks and Bilomas Dig. Dis. Interv. 2017 1 014 021 14. Weerakkody Y. Jones J.B. Reference Article Available online: (accessed on 1 September 2022) 15. Snyder E. Banks K.P. Hepatobiliary Scintigraphy StatPearls [Internet] StatPearls Publishing Treasure Island, FL, USA 2022 16. Fatima J. Baron T.H. Topazian M.D. Houghton S.G. Iqbal C.W. Ott B.J. Farley D.R. Farnell M.B. Sarr M.G. Pancreaticobiliary and Duodenal Perforations After Periampullary Endoscopic Procedures: Diagnosis and Management Arch Surg. 2007 142 448 455 10.1001/archsurg.142.5.448 17515486 |
PMC10000512 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050975 foods-12-00975 Article Effects of Addition of Tea Polyphenol Palmitate and Process Parameters on the Preparation of High-Purity EPA Ethyl Ester Ding Xuyang 1 Liu Fujun 2 Zheng Rui Methodology Validation 1 Pei Xuechen 1 Wang Ziye 1 Zhou Dayong 134 Yin Fawen 134* Nikolaou Anastasios Academic Editor Silva Paula Academic Editor Mantzourani Ioanna Academic Editor 1 School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China 2 Liao Fishing Group Limited Company, Dalian 116000, China 3 National Engineering Research Center of Seafood, Dalian 116034, China 4 Collaborative Innovation Center of Seafood Deep Processing, Dalian 116034, China * Correspondence: [email protected] or [email protected]; Tel.: +86-411-86323453 25 2 2023 3 2023 12 5 97501 2 2023 19 2 2023 22 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). High-purity eicosapentaenoic acid (EPA) ethyl ester (EPA-EE) can be produced from an integrated technique consisting of saponification, ethyl esterification, urea complexation, molecular distillation and column separation. In order to improve the purity and inhibit oxidation, tea polyphenol palmitate (TPP) was added before the procedure of ethyl esterification. Furthermore, through the optimization of process parameters, 2:1 (mass ratio of urea to fish oil, g/g), 6 h (crystallization time) and 4:1 (mass ratio of ethyl alcohol to urea, g/g) were found to be the optimum conditions in the procedure of urea complexation. Distillate (fraction collection), 115 degC (distillation temperature) and one stage (the number of stages) were found to be the optimum conditions for the procedure of molecular distillation. With the addition of TPP and the above optimum conditions, high-purity (96.95%) EPA-EE was finally obtained after column separation. EPA high purity ethyl esterification urea complexation molecular distillation column separation National Natural Science Foundation of China32230080 Dalian Science and Technology Innovation Fund Project2022JJ11CG008 This research was financially supported by the National Natural Science Foundation of China (32230080), the Dalian Science and Technology Innovation Fund Project (2022JJ11CG008). pmc1. Introduction Long-chain omega-3 polyunsaturated fatty acids (n-3 LC-PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are important components in healthy diets. So far, their health benefits have been widely reported, which include reducing triacylglycerols , anti-inflammation , anticancer activities and alleviating Alzheimer's disease . n-3 LC-PUFAs are sold as soft gel capsules, aqueous emulsions and mixtures with vegetable oils, which are usually called omega-3 products. The commercial production of highly enriched n-3 LC-PUFAs is at present a major challenge for research. Single fractionation processes do not discriminate between different PUFAs. Therefore, several methods for preparing enriched fractions of n-3 LC-PUFAs have been developed, including controlled winterization , molecular distillation , urea complexation and column separation . Urea complexation is used to separate fatty acids based on the degree of unsaturation , molecular distillation is a method suitable for removing impurities and column separation can further increase the purity of the obtained product . So far, commercial omega-3 products contain a high purity of total n-3 LC-PUFAs, but not EPA or DHA. As the most abundant omega-3 fatty acid in the central nervous system, DHA is important for the health of babies and pregnant women . Moreover, a moderate intake of EPA can effectively alleviate age-related cognitive impairment in older adults . Due to the fact that the bioactivities of most bioactive substances (vitamins, n-3 LC-PUFAs, sterols and amino acids) are strongly connected to their purities , the enrichment of EPA and/or DHA from marine oils has attracted considerable attention. The produced high-purity EPA or DHA is conducive to developing nutritious foods which are suitable for different consumer groups. Recently, the industry trend has shifted toward producing DHA via microalgae species. The proposed design is for a plant to cultivate Schizochytrium cells in the upstream process, and then extract and purify the algal oils in the downstream process . Such DHA-rich algal oil is a triacylglycerol, similar to the form of DHA found in breast milk. Thus, high-purity DHA can be successfully collected from algal oils by urea collateralization . Comparatively, the development of mature technology to produce high-purity EPA is urgently needed. In addition, EPA and DHA are easily oxidized and degraded during the production process (esterification, evaporation and distillation), and adding antioxidants may effectively inhibit the related oxidation . Thus, with the addition of antioxidants, it is possible to improve product purity. Given this, in order to prepare EPA ethyl esters (EPA-EE) from fish oils, which are mainly used to produce a high quality of free EPA, an integrated technique consisting of ethyl esterification, urea complexation, molecular distillation and column separation was applied. Furthermore, through the addition of tea polyphenol palmitate (TPP, a kind of antioxidant), as well as the optimization of process parameters, high-purity EPA ethyl ester was successfully obtained. This study provides fundamental data for the commercial production of high-purity EPA from fish oils. 2. Materials and Methods 2.1. Materials and Chemicals Fish oil without added antioxidants was purchased from Qingdao Seawit Life Science Co, Ltd. (Qingdao, China). Food-grade tea polyphenol palmitate (TPP) was purchased from Guangzhou Shengtong Trading Co., Ltd. (Guangzhou, China). Urea was purchased from Shanghai Macklin Biochemical Co, Ltd. (Shanghai, China). BF3-methanol (14%, w/w, g/g) was purchased from Aladdin Bio-Chem Technology Co., Ltd. (Shanghai, China). Gas chromatography (GC)-grade n-hexane and methanol were purchased from Shanghai Macklin Biochemical Co, Ltd. (Shanghai, China). Sodium hydroxide (NaOH), ethyl ethanol (C2H5OH), sulfuric acid (H2SO4) and hydrochloric acid (HCl) were purchased from Damao Chemical Reagent Co, Ltd. (Tianjin, China). 2.2. Effects of TPP Added during the Ethyl Esterification Process According to our previous studies, TPP exerts the strongest antioxidant effect among various antioxidants, including bamboo leaves, rosemary extract, vitamin E, ascorbyl palmitate, TPP, vitamin C and tea polyphenol . Therefore, TPP was selected to be added during the ethyl esterification process. 2.2.1. The Preparation of Samples Supplemented with TPP before the Ethyl Esterification Process A mixture of fish oil (50.0 g) and 30% (m/v, g/mL) NaOH-H2O solution (150 mL) was refluxed for 2 h in an 80 degC water bath. Then, 3 mM hydrochloric acid was added to adjust the pH value to 1. Subsequently, 30 mL of water was added to above mixture, which was further extracted 3-5 times with 100-200 mL of n-hexane until the n-hexane layer was colorless. The n-hexane extract liquor was evaporated by rotary vacuum evaporation at 35 degC. Then, 20.0 g of evaporated residue was weighed, and 12 mg of TPP was added at its maximum allowable amount (600 mg/kg) permitted by the Chinese Standard GB 2760-2014 . To the mixture was added 18.0 g of H2SO4-ethyl ethanol (2%, v/v, mL/mL) and it was placed into an 80 degC water bath. After 2.5 h, 50 mL of water was added, and the mixture was extracted 3-5 times with 100-200 mL of n-hexane until the n-hexane layer was colorless. Finally, after rotary vacuum evaporation at 35 degC, an ethyl-esterified fish oil sample supplemented with TPP before the ethyl esterification process was obtained. 2.2.2. The Preparation of Samples Supplemented with TPP after the Ethyl Esterification Process TPP was added directly to the product of ethyl-esterified fish oil at its maximum allowable amount (600 mg/kg) permitted by the Chinese Standard GB 2760-2014 . Thus, an ethyl-esterified fish oil sample supplemented with TPP after the ethyl esterification process was obtained. 2.2.3. Accelerated Storage Experiment The ethyl-esterified fish oil samples supplemented with TPP before or after the ethyl esterification process were placed in an air oven at 60 degC. These samples were taken at regular intervals of 2 days until 6 days. 2.2.4. Peroxide Value According to the Chinese Standard GB 5009.227-2016 , the peroxide value (POV) was detected as follows: 2.0 g of ethyl-esterified fish oil was accurately weighed and dissolved in 30 mL of chloroform-acetic acid (2:3, v/v, mL/mL) mixed solution. Subsequently, 1 mL of starch indicator (1%, m/v, g/mL) and 1 mL of saturated potassium iodide solution were added. After shaking for 30 s, the mixture was placed in the dark for 3 min. Then, 100 mL of deionized water was added, which was further titrated by using 2 mM sodium thiosulfate (Na2S2O3) standard solution until it became colorless. POV (meq/kg) was calculated by the following formula:POV = (V - V0) x c x 0.1269 x 100/m where V (mL) and V0 (mL) are the volumes of Na2S2O3 standard solution consumed in the titrating ethyl-esterified fish oil sample and the blank reagent, respectively. c (mM) is the concentration of Na2S2O3 standard solution. The value 0.1269 is equivalent to 1.00 mL Na2S2O3 standard titration solution [C(Na2S2O3) = 1.000 M]. m is the quantity (g) of fish oil and 100 is the conversion factor. 2.2.5. Thiobarbituric Acid Reactive Substances According to the methods reported by John et al. and Wang et al. , the thiobarbituric acid reactive substances (TBARS) of ethyl-esterified fish oil samples were detected with slight modifications. Briefly, 0.1 g of ethyl-esterified fish oil was mixed with 2.5 mL of mixed liquor (196 mL of distilled water, 4.17 mL of concentrated hydrochloric acid solution, 0.75 g of thiobarbituric acid and 30 g of trichloroacetic acid), which was then heated for 10 min in boiling water. After cooling to room temperature, the mixture was centrifuged at 3000x g for 10 min. The obtained upper layer liquid was measured at 532 nm. The malondialdehyde concentration was converted to TBARS (ppm) by the following formula:TBARS = A532 x 2.77 where A532 is the absorbance value of the reaction mixture at 532 nm, and 2.77 is the conversion coefficient of malondialdehyde concentration into TBARS. 2.2.6. EPA Content and DHA Content According to the Chinese Standard GB 5009.168-2016 , the EPA content and the DHA content were detected as follows: 5 mg of fish oil was mixed with 200 mL of 1 mg/mL triundecylin dissolved in chloroform. Then, 2 mL of 0.5 M NaOH-CH3OH was added. The mixture was refluxed for 5 min in an 80 degC water bath. The reaction was carried out by adding 2 mL of BF3-CH3OH (14%, w/w, v/v). After 2 min, the reaction solution was extracted with n-hexane (1.5 mL). Before gas chromatography (GC) analysis, n-hexane containing fatty acid methyl ester (FAME) was filtrated through a 0.22 mm filter. The specific parameters of GC analysis were as follows : the initial temperature was 100 degC (13 min) and raised (10 degC/min) to 180 degC (6 min); then, the temperature was raised (1 degC/min) to 215 degC (20 min); finally, the temperature was raised (5 degC/min) up to 230 degC (12 min). The carrier gas comprised nitrogen, hydrogen and air. The inlet temperature and the temperature of the detector were 270 degC and 280 degC, respectively. Shunt injection was adopted, with a shunt ratio of 5:1, and the injection volume was 1 mL. The EPA or DHA content C0 (mg/g) in fish oil was calculated by the following formula:C0 = [Fi x Ai x rc11 x Vc11 x 1.0067/(AC11 x m)] x FFAMEi-FA x 10 where Fi is the influence factor of fatty acid methyl ester; Ai is the peak area of fatty acid methyl ester in the sample; AC11 is the peak area of triundecylin in the sample; rc11 is the concentration of glycerol triundecylin solution (mg/mL); Vc11 is the volume of triundecylin added (mL); 1.0067 is the conversion coefficient of triundecylin to methyl triundecylin; m is the quantity of raw fish oil (mg); 10 is the coefficient of converting the content into the content in the sample per g; FFAMEi-FA is the conversion coefficient of fatty acid methyl ester to fatty acid. 2.2.7. EPA-EE Content and DHA-EE Content Standard solutions of EPA-EE and DHA-EE with different concentrations were prepared with n-hexane as the solvent, which were then filtered by 0.22 mm filter membranes. The detection method was the same as that described in Section 2.2.6. The standard curves (x: concentration, mg/mL; y: peak area) of EPA-EE and DHA-EE were plotted as y = 725.55x + 4.33 (R2 = 0.9992) and y = 507.95x + 6.65 (R2 = 0.9997), respectively. A certain quantity of ethyl fish oil product was mixed with 3 mL of n-hexane. The detection method was the same as that described in Section 2.2.6. The formula for calculating the EPA-EE (or DHA-EE) content C1 (mg/g) in the product was as follows:C1 = 3 x x/m where m is the quantity of ethyl-esterified fish oil product (g), x is the concentration of EPA-EE (or DHA-EE) in the sample (mg/mL) and 3 is the n-hexane volume (mL). 2.2.8. Esterification Efficiency In the process of esterification, the esterification efficiency e (%) of EPA or DHA was calculated by the following formula:e = [(C1 x m1)/M1]/[(C0 x m0)/M0] x 100% where m1 is the quantity of ethyl fish oil products (g); C1 is the content of EPA-EE (or DHA-EE) in ethyl-esterified fish oil products (mg/g); M1 is the molar mass (mg/mmol) of EPA-EE (or DHA-EE); m0 is the quantity of raw fish oil (g); C0 is the content of EPA or DHA in raw fish oil (mg/g); M0 is the molar mass (mg/mmol) of EPA (or DHA). 2.3. Parameter Optimization of Urea Complexation According to the procedure described by Zheng et al. , urea complexation was performed with a slight modification. Briefly, 2 g of ethyl-esterified fish oil and urea were dissolved in 95% ethyl alcohol. The mixture was placed into a 60 degC water bath and stirred continuously until it formed a uniform solution. Mass ratios of urea to oil (g/g), including 0.5:1, 1:1, 1.5:1, 2:1 and 2.5:1, as well as mass ratios of ethyl alcohol to urea (g/g), including 2:1, 3:1, 4:1, 5:1 and 6:1, were changed by using different amounts of urea (or 95% aqueous ethyl alcohol). Subsequently, the urea inclusion compounds were allowed to crystallize at 4 degC for different times, including 2, 4, 6, 8 and 10 h. Nonurea complexation fraction (NCF, liquid phase) was obtained by filtration on a Buchner funnel under suction, and the ethyl alcohol in NCF was removed by rotary vacuum evaporation at 35 degC. Then, an appropriate amount of water was added to remove the urea residue. Finally, the upper layer was extracted with n-hexane. N-hexane in the extract liquor was removed by rotary vacuum evaporation at 35 degC. Thus, based on the EPA-EE content and the DHA-EE content of the product, the appropriate parameters were obtained, including the mass ratio of urea to oil, the mass ratio of ethyl alcohol to urea and the crystallization time. 2.4. Parameter Optimization of Molecular Distillation Molecular distillation was performed in a KDL2 distiller (UIC GmbH, Hannover, Germany). The instrument contains a condensing surface of 2 dm2 and an evaporation surface of 5 dm2. The operation pressure was maintained at 0.3 mbar and the feed temperature was kept at 20 degC. The rotor speed was set at 200 rpm. The condenser temperature was set at 3 degC and the feeding flow was 1.0 +- 0.1 mL/min. The distillates and residues were obtained at different distillation temperatures (110 degC, 115 degC, 120 degC, 125 degC and 130 degC) and different stages of distillation (stage one, two or three). Thus, based on the EPA-EE content and DHA-EE content of distillates and residues, the appropriate parameters, including distillation temperature and the number of stages in distillation, were obtained. 2.5. Column Separation The column separation was used for the further purification of EPA-EE. The separation was performed on a C18 column (4.6 x 250 mm, 15 mm, R2021040801) by isocratic elution with 92% (v/v, mL/mL) methanol-water as the mobile phase. The flow rate was 0.3 mL/min. The wavelength of detection was 220-270 nm. The injection volume was 140 mL.EPA-EE existed in the effluents from 49 min to 61 min. The purity of EPA-EE was measured through the GC method described in Section 2.2.7. 2.6. Statistical Analysis The results were calculated from parallel measurements and are given as means +- standard derivations. SPSS version 16.0 software (SPSS Inc., Chicago, IL, USA) was applied for the statistical analysis. Differences between means were evaluated by one-way ANOVA (post hoc test: SNK) or independent samples t-tests. Comparisons that yielded p values < 0.05 (or 0.01) were considered significant. 3. Results 3.1. Effects of TPP Added during the Ethyl Esterification Process Due to the high levels of PUFAs, including EPA and DHA, fish oils are more likely to be oxidized in the process of ethyl esterification. Such oxidation will cause the decrement of nutrients, the deterioration of flavor and the generation of potentially toxic compounds . POV and TBARS have been widely used to monitor the primary and secondary oxidation product in oils , respectively. As shown in Figure 1A,B, the POV and TBARS values increased significantly with the extension of storage time, which indicated that all oil samples had undergone gradual oxidation. Importantly, adding tea polyphenol palmitate (TPP) before ethyl esterification (TPP-B) was more effective than adding TPP after ethyl esterification (TPP-A). For example, after 6 days of storage, the POV (or TBARS) values of the TPP-B and TPP-A groups were 67.89 meq/kg (or 4.30 mg MDA/kg) and 73.24 meq/kg (or 4.86 mg MDA/kg), respectively. Our previous study also indicated that adding TPP into the ethanol solvent during the extraction process was more effective than adding it into Antarctic krill (Euphausia superba) oil after the extraction process , consistent with the experimental results in this section. The EPA-EE content, DHA-EE content and esterification efficiency were also calculated, and their values gradually decreased over storage time . Obviously, both EPA-EE and DHA-EE in the TPP-B groups decreased more slowly. For example, after 6 days of storage, the EPA-EE contents (or DHA-EE content) of the TPP-B and TPP-A groups were 383.91 mg/g (or 242.74 mg/g) and 366.91 mg/g (or 225.62 mg/g), respectively. Furthermore, TPP added before the ethyl esterification process could also effectively improve the esterification efficiency. For example, the ethyl esterification efficiency of EPA increased from 64.05% to 71.97%, and the corresponding efficiency of DHA increased from 76.24% to 84.88%. It is widely known that some vegetable oils such as sesame oil and hemp seed oil are rich in natural antioxidants. Many studies have shown that these natural antioxidants are effective in protecting oils from oxidation. For example, Shen et al. found that compared with oils extracted from red and white quinoa seeds, oil extracted from black quinoa seed contained higher PUFAs . PUFA contents in red, white and black quinoa seeds are significantly different. The synergistic extraction of natural antioxidant components during oil extraction can also indirectly affect the oxidative stability of PUFA in oils. By contrast, tocopherol (vitamin E) and phytosterol contents in black quinoa seed oil are significantly higher than those in white and red quinoa seed oil. Nehdi et al. reported that compared with the stripped seed oil, the non-stripped seed oil shows higher oxidative stability . This is mainly due to the fact that the stripped seed oil contains a low amount of tocopherol . Similarly, adding TPP into crude fish oil before ethyl esterification is more effective than adding TPP into ethyl-esterified fish oil after ethyl esterification. 3.2. Optimization of Urea Complexation Conditions Urea complexation is a useful technique for removing saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) . Briefly, the oils obtained from ethyl esterification are mixed with urea-ethanol solution. SFAs and MUFAs are easily combined with urea to form a complex. After low-temperature crystallization at 4 degC, the complexes of SFAs-urea and MUFAs-urea can be removed by filtration . The liquid (non-urea-complexed fraction) is enriched with polyunsaturated fatty acids (PUFAs) . In the process of urea complexation, both higher and lower urea/oil ratios will lead to lower PUFA content in the product. Briefly, the complexation of urea to SFAs and MUFAs is uncompleted at a lower urea/oil ratio . Meanwhile, SFAs and MUFAs are fully complexed at a higher urea/oil ratio. Unfortunately, parts of PUFAs are also inevitably "hidden" in the cavity of urea complex . Crystallization time is another important factor affecting complexation efficiency. It is easily understood that the complexation efficiency of SFAs and MUFAs is too low after a short crystallization time. However, the extension of crystallization time will lead to an increase in impurities (urea) and stronger degradation of EPA-EE in the products . Finally, the ethyl alcohol/urea ratio is also a vital factor affecting complexation efficiency in the process of urea complexation. Briefly, urea cannot dissolve sufficiently in ethyl alcohol at a lower ethyl alcohol/urea ratio . However, at a higher ethyl alcohol/urea ratio, lower complexation efficiency will be caused by the dissolution of SFAs and MUFAs in ethyl alcohol . The effect of the above three parameters on the EPA-EE content of ethyl-esterified fish oils is shown in Figure 3. Apparently, the EPA-EE content initially increased and then decreased as the values of each parameter increased. Under the conditions of 2:1 mass ratio of urea to fish oil (g/g), 6 h crystallization time and 4:1 mass ratio of ethyl alcohol to urea (g/g), the maximal EPA-EE content of 543.08 mg/g was obtained. Similar results have also been reported by other researchers. For example, Tang et al. found that the DHA-EE content of microalgae oils after urea complexation first increased, exhibited the maximum content of 604 mg/g at a 2:1 urea/oil ratio (g/g) and then decreased with the increment in this ratio . Similarly, Zhai et al. reported that the maximal EPA-EE content (802 mg/g) of fish oil was obtained at a 4:1 ethyl alcohol/urea ratio (g/g) . Huang et al. reported that the content of ethyl linoleic acid of bran oil was first increased and then decreased as the ratio increased from 5:1 to 15:1 (95% ethyl alcohol/urea ratio, g/g), and the maximal ethyl linoleic acid content (379.9 mg/g) was obtained . 3.3. Optimization of Molecular Distillation Conditions 3.3.1. Effect of Temperature on the Efficiency of Molecular Distillation Molecular distillation is one of the most effective purification methods to separate substances according to the difference in vapor pressure . In particular, the combination of the urea complexation and molecular distillation methods can result in a significant improvement in the total concentration of PUFA (EPA and DHA) ethyl esters of marine oils . Compared with other parameters, the temperature is widely regarded as the most influential variable in the process of molecular distillation . In order to further improve the content of EPA-EE, as well as reduce the content of DHA-EE in the products, the fish oils obtained from urea complexation were subjected to molecular distillation. As shown in Figure 4, the effect of temperature on the EPA-EE content and the DHA-EE content in distillates and residues after one-stage distillation was evaluated. It was obvious that compared with residues, distillates contained more EPA-EE and less DHA-EE. Particularly, the contents of EPA-EE in distillates were significantly higher than those of DHA-EE. Similarly, Zheng et al. found that the content of EPA-EE in residue after molecular distillation decreased from 254.4 mg/g to 173.7 mg/g, indicating its easy transportation to the distillate . Generally, the residues were collected in industrial production and some related research. For example, Fang et al. reported that after molecular distillation and urea complexation, the content of total PUFA increased from 307.2 mg/g (in crude fish oil) to 834.2 mg/g (in residue) . Wen et al. reported that the content of total PUFA increased from 635 mg/g (in crude fish oil) to 789 mg/g (in residue) after molecular distillation . These findings were not consistent with our results, mainly due to the different requirements (high purity of total PUFA-EE or EPA-EE) for the products. Furthermore, the results in this section clearly indicate that the EPA-EE and DHA-EE contents in distillates first increased, exhibited the maximum contents at the temperatures of 115 degC (EPA-EE) and 120 degC (DHA-EE), and then decreased with the increment in the distillation temperature. These results are consistent with other published findings. For example, Magallanes et al. reported that the content of EPA-EE in the distillate reached the maximum value (121.14 mg/g) at 120 degC, and then decreased (e.g., 99.74 mg/g at 140 degC) with the increase in distillation temperature . Similarly, Liang et al. reported that the EPA-EE content in distillate first increased, exhibited the maximum contents (155 mg/g) at the temperature of 130 degC, and then decreased with the increment in the distillation temperature . Based on the differences in vapor pressures, various kinds of ethyl fatty acids can be separated from marine oils . Under a certain vapor pressure, as distillation temperature increases, improvements in EPA-EE and DHA-EE contents are easily achieved . However, ethyl fatty acids are a kind of heat-sensitive substance with poor oxidation stability. Obviously, a high temperature will promote the occurrence of an oxidation reaction . 3.3.2. Effect of Distillation Stages on the Efficiency of Molecular Distillation Molecular distillation is applied industrially to obtain fish oil and other products (free fatty acids, vitamin E and vitamin A) . In many cases, the separation achieved in one-stage molecular distillation is incomplete and cannot meet the requirements , and thus, it is worth exploring multiple-stage schemes. In order to produce high-purity EPA, the distillate obtained from molecular distillation also requires subsequent chromatographic column separation. Obviously, such distillate should contain more EPA-EE and less DHA-EE. As shown in Figure 5, under the distillation temperature of 115 degC, the highest EPA-EE content and the lowest DHA-EE content in distillates were obtained. Moreover, compared with distillates derived from two-stage (EPA-EE, 649.47 mg/g; DHA-EE, 260.55 mg/g) and three-stage (EPA-EE, 608.81 mg/g; DHA-EE, 295.54 mg/g) distillations, the distillate derived from one-stage distillation contained more EPA-EE (667.81 mg/g) and less DHA-EE (230.56 mg/g). Other researchers reported similar results. For example, Sosa et al. reported that compared with fatty acid ethyl esters (FAEEs) (756.3 mg/g) in distillates from two-stage distillation, FAEEs (863.4 mg/g) in distillates from one-stage distillation were more abundant . Zhang et al. reported that a high purity (929.8 mg/g) of PUFA-EE was obtained from Schizochytrium limacinum oil after one-stage molecular distillation . Furthermore, it is essential to consider that two-stage (or more) molecular distillation performed with one or more types of distillation equipment are usually expensive . Given this, the highest content of EPA-EE in distillates, as well as the lowest possible costs, can be easily obtained from one-stage molecular distillation at the temperature of 115 degC. 3.4. The Purity of EPA-EE Obtained from Column Separation The combination of urea complexation and molecular distillation can effectively increase EPA-EE content, as well as decrease DHA-EE content. However, it fails to produce high-purity EPA-EE. Therefore, column separation was applied in this study to separate EPA-EE from the above mixture obtained from the combined treatments of urea complexation and molecular distillation . As shown in Figure 6, high-purity (96.95%) EPA-EE was produced from the technological process consisting of ethyl esterification, urea complexation, molecular distillation and column separation. 4. Conclusions In the present study, based on the analysis of EPA ethyl ester (EPA-EE) contents, the optimum conditions of 2:1 (mass ratio of urea to fish oil, g/g), 6 h (crystallization time), 4:1 (mass ratio of ethyl alcohol to urea, g/g), distillate (fraction collection), 115 degC (distillation temperature) and one stage (the number of stages) to produce high-purity EPA-EE were obtained. Furthermore, the results of peroxide value, thiobarbituric acid reactive substances and esterification efficiency clearly indicate that adding tea polyphenol palmitate (TPP) before the procedure of ethyl esterification could effectively improve the purity and inhibit the oxidation. Thus, the technique with the addition of TPP to produce high-purity EPA-EE, which consisted of saponification, ethyl esterification, urea complexation, molecular distillation and column separation, was successfully applied. Acknowledgments We would like to express our thanks to all those who participated in the present research. Author Contributions Conceptualization, X.D.; Methodology, R.Z. and X.D.; Validation, R.Z. and X.P.; Formal Analysis, X.D. and F.Y.; Investigation, F.L. and Z.W.; Resources, F.Y. and R.Z.; Data Curation, X.D.; Writing--Original Draft Preparation, X.D.; Writing-- Review and Editing, F.Y.; Visualization, D.Z.; Supervision, F.Y.; Project Administration, D.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data are contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Effect of TPP added before or after the process of ethyl esterification on POV (A), TBARS (B), EPA-EE content (C) and DHA-EE content (D) of ethyl-esterified fish oils stored at 60 degC for different times. Values of different groups with different uppercase letters (A-D) or lowercase letters (a-d) are significantly different at p < 0.05; The asterisks (*) indicate the significant differences between the two groups with the same storage time at p < 0.05. The asterisks (**) indicate the significant differences between the two groups with the same storage time at p < 0.01. Figure 2 Effect of TPP on the esterification efficiency of fish oil in ethyl esterification. The asterisks (**) indicate the significant differences between the two groups supplemented with the different sample at p < 0.01. Figure 3 Effect of mass ratio of urea to fish oil (A), crystallization time (B) and mass ratio of ethyl alcohol to urea (C) on EPA-EE content of fish oils in the process of urea complexation. Values with different lowercase letters (a-d) in each panel are significantly different at p < 0.05. Figure 4 Effect of distillation temperature on EPA-EE content (A) and DHA-EE content (B) in distillates and residues after one-stage distillation. Values with different lowercase letters (a-d) or uppercase letters (A-D) are significantly different at p < 0.05. Figure 5 Effect of the number of stages in distillation on EPA-EE content and DHA-EE content in residues ((A) 85 degC; (C) 100 degC; (E) 115 degC) and distillates ((B) 85 degC; (D) 100 degC; (F) 115 degC). Values with different lowercase letters (a-d) or uppercase letters (A-D) are significantly different at p < 0.05. Figure 6 The purity of EPA-EE detected with GC in distillates after treatment with column separation. The asterisks (**) indicate the significant differences between the two groups at p < 0.01. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000513 | Esophageal adenocarcinoma (EAC) is a severe malignancy with increasing incidence, poorly understood pathogenesis, and low survival rates. We sequenced 164 EAC samples of naive patients (without chemo-radiotherapy) with high coverage using next-generation sequencing technologies. A total of 337 variants were identified across the whole cohort, with TP53 as the most frequently altered gene (67.27%). Missense mutations in TP53 correlated with worse cancer-specific survival (log-rank p = 0.001). In seven cases, we found disruptive mutations in HNF1alpha associated with other gene alterations. Moreover, we detected gene fusions through massive parallel sequencing of RNA, indicating that it is not a rare event in EAC. In conclusion, we report that a specific type of TP53 mutation (missense changes) negatively affected cancer-specific survival in EAC. HNF1alpha was identified as a new EAC-mutated gene. esophageal adenocarcinoma TP53 HNF1alpha SMAD4 GVMQ7_UNP University of BolognaRFO2019 This research was funded by a GVM grant Q7_UNP to S.M. and was partially funded by the University of Bologna, grant RFO2019 to E.B. pmc1. Introduction Esophageal adenocarcinoma (EAC) is a severe malignancy with increasing incidence in Western countries over the past few decades and a relatively high mortality since overall prognosis remains bleak and the 5-year survival rate is just 35-45% . EAC develops from the cells that release mucus and other fluids and may arise according to the widely accepted sequence gastroesophageal reflux disease (GERD) /intestinal metaplasia/dysplasia/ adenocarcinoma . In clinical practice, complete endoscopic evaluation of GERD symptoms includes evaluation of erosive esophagitis and its complication and inspection for BE with multiple biopsies when present . BE is relatively common in the general population, with a 1-2% prevalence (up to 10% in those with reflux symptoms) , but only about 1% of patients progress to cancer each year . The ability to treat pre-invasive, dysplastic lesions with endoscopic resection and/or ablation instead of more extensive and invasive procedures such as chemotherapy with or without radiotherapy and esophagectomy, which have associated co-morbidities and poor 5-year survival rates, makes early diagnosis highly clinically relevant . In a recent study on a large series of EAC cases submitted to surgery (without neoadjuvant treatment), a diagnostic algorithm which separated adenocarcinomas with glandular architecture from other rare histotypes, and further graded the former and subtyped the latter, was adopted . This morphologic distinction has proven to have a significant prognostic impact on its own or dichotomized into lower and higher risk carcinomas, especially when coupled with stage. Indeed, the stage plus histotype combination showed a high discriminating power for 5-year cancer-specific survival, ranging from 87.6% in the stage II lower risk group to 14% in the stage IVA higher risk group . Given the histological differences observed in EAC, it is of great interest to investigate the underlying biology of the tumor and to understand the molecular alterations correlated with those distinctive patterns which provide strong prognostic factors. Indeed, several genomic studies have included EAC in a group of tumors with one of the most frequent rates of copy number alterations (CNAs), somatic structural rearrangements, and elevated mutation frequency, with different mutational signatures and epigenetic mechanisms giving rise to significant inter and intra-tumor heterogeneity . Large-scale sequencing studies have revealed distinct mutational signatures in EAC, and the presence of multiple CNAs was possibly correlated to a worse outcome; however, an exhaustive correlation with clinical outcomes and specific histotypes has not yet been provided. In a large genomic study, Secrier et al. identified three distinct molecular subtypes of molecular signatures: (i) an enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) a dominant T > G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) a C > A/T mutational pattern with evidence of an aging imprint. However, the clinical characteristics of the three subgroups did not differ significantly . In EAC, a number of potential driver mutations have been described, with many of the mutations occurring in tumor suppressor genes (e.g., TP53, SMAD4, and ARID1A). The overall picture is of genomic instability and significant heterogeneity between patients. The accumulation of structural variants appears to be a gradual process throughout the disease's natural history . According to the Cancer Genome Atlas , EACs contain molecular changes similar to the chromosomal instability (CIN) subtype of stomach cancer. This suggests that EAC treatment may be improved by grouping them with CIN stomach cancers. Genomic alterations may also represent effective targets for therapy, i.e., frequent alterations of genes that regulate the cell cycle may be treated with existing drugs. Moreover, one-third of the EACs studied harbor an alteration to the ERBB2 gene, which encodes the HER2 protein and may be targeted with HER2 inhibitors. However, the overall genomic heterogeneity and the rearrangements occurring during tumor progression make it difficult to define valuable prognostic molecular signatures underlying biology that drive tumor onset and development . We coupled a deep sequencing analysis of the most commonly mutated genes in EAC with the recent novel classification based on histological subtypes in order to stratify patients based on clinical and molecular features for better personalized care. We evaluated the genetic alterations of cancer-related genes that we found recurrently mutated in a previous study on a small group of EAC cases . Herein we analyzed specimens of 164 naive patients (without chemo-radiotherapy and not subjected to neoadjuvant treatments) using next-generation sequencing approaches. Moreover, we characterized the presence of novel gene fusion transcripts, as markers of genomic alterations, in a number of these cases for which we had RNA available from tumor specimens. Molecular data were correlated with the histological subtypes and the clinical outcomes. 2. Materials and Methods 2.1. Sample Recruitment The DNA samples were extracted from the surgical samples obtained at the following centers: Istituto Europeo di Oncologia (IEO), Milano, and IRCCS Ospedale San Raffaele, Milano, Ospedale di Verona, Verona, for a total of 164 samples. The inclusion criteria consisted of the presence of adenocarcinoma of the esophagogastric junction; no neoadjuvant treatment (chemo-radiotherapy-naive EACs); and full clinical medical history and follow-up up to 60 months after surgery. All of the surgical resections were formalin-fixed paraffin-embedded (FFPE), re-evaluated by gastrointestinal pathologists, and classified according to the EACSGE histological classification . The cases analyzed for mutation analysis of TP53 only have been previously described and they were re-classified according to the EACSGE classification. 2.2. Custom EAC Panel: Library Preparation, Hybridization, Sequencing, and Bioinformatic Analysis DNA was extracted from two 40 mm-thick, FFPE sections using a QIAMP DNA FFPE Tissue Kit (Cat. 56404; Qiagen, Hilden, Germany) according to the manufacturer's protocol. Dual-index paired-end libraries were prepared using a Lotus DNA library prep kit (Cat. 10001074; Integrated DNA Technologies IDT Inc., Coralville, IA, USA) according to the manufacturer's instructions. The protocol followed three major steps: an enzymatic preparation (with fragmentation to obtain 300-350 bp DNA fragments) where end-repair and dA-tailing were performed, the ligation of stubby adapters was performed, and PCR amplification for 11 cycles with indexing primers was performed (to incorporate sample-unique indexing sequences and P5 and P7 sequences to attach to the flow-cell). After purification, the single DNA libraries were run on 3% agarose gel to confirm the appropriate size and quantified using a Qubit dsDNA BR Assay Kit (Cat. Q33265; ThermoFisher Scientific, Vilnus, Lituania). Five hundred ng of each library preparation was pooled into groups of 16 samples to perform hybridization and enrichment for selected gene regions. This step was performed using an xGen Lockdown probe pool and an xGen hybridization capture of DNA libraries kit (IDT), according to the protocols. Each pool of 16 samples was hybridized to the capture probes for 16 h at 65 degC. xGen Lockdown Probes were individually synthesized, including 5' biotinylated oligos, and were assembled in a custom panel of 26 genes for target capture. The genes selected for this study are listed in Figure 1. The hybridized regions were then captured with streptavidin magnetic beads and, after non-bound products' removal, a post-capture PCR of 11 cycles was performed. The enriched library pools were checked for quantity and size with a Qubit dsDNA HS Assay kit (Cat. Q33230; Thermo Fisher Scientific, Waltham, MA, USA) and 2100 Bioanalyzer High Sensitivity DNA (Agilent Technologies, Santa Clara, CA, USA), respectively. Each pool was normalized to 1.3 pM and then sequenced on an Illumina NextSeq 500 platform (Illumina San Diego, CA, USA) at 150 bp paired ends. Data analysis was performed with an in-house pipeline . In particular, Fastq files containing raw reads were checked using FastQC v.0.11.8) and aligned using BWA (bio-bwa.sourceforge.net v.0.7.17-r1188) to the human reference (hg19). PCR-duplicated reads were marked and removed using Picard. Putative somatic variants, including SNPs and small insertions/deletions (indels), were identified using GATK software (software.broadinstitute.org/gatk/ v.4.0.10). The raw mutation calls were filtered to exclude false calls based on base quality, allele frequency of mismatched bases, and possible occurrences of strand bias. The identified mutations were further annotated and prioritized with Ensembl VEP (www.ensembl.org/Tools/VEP v.94). 2.3. RNA Analysis RNA was extracted from the FFPE samples (five for each EACSGE subgroup). The samples were then selected among the ones with good quality RIN scores and DV200 > 40%. Starting from 100 ng of 27 RNA, libraries were prepared using a TruSight RNA Pan-Cancer Panel Kit (Illumina, San Diego, CA, USA; 1385 cancer-associated genes), following the manufacturer's protocol. On twenty-two of the libraries that passed the protocol quality checks, paired-end RNA sequencing was performed (Reagent Kit v3-150 cycles, MiSeq, Illumina, San Diego, CA, USA) and raw sequencing data were converted to FASTQ file format and analyzed by combining FusionCatcher (FC(1)), STAR-Fusion (SF), and two Basespace applications [RNA-Seq Alignment v.1.1.0 (RSA) and TopHat Alignment v.1.0.0 (THA); Illumina, San Diego, CA, USA]. The reference Homo sapiens UCSC hg19 (RefSeq and Gencode gene annotations) was used for all the aligners. We retained the fusions detected by at least three tools and we introduced further criteria to retain or reject fusions detected by two tools or one tool [see PCT application No. PCT/EP2021/065692 (10 June 2021): Method to identify linked genetic fusions]. The gene fusions were confirmed with Sanger sequencing, as previously described . 2.4. Immunohistochemistry Analysis Immunohistochemistry (IHC) analysis was performed automatically with a Benchmark XT(r) immunostainer (Ventana Medical Systems) HNF1alpha antigen. The immunohistochemical analysis was validated through positive controls (as an external positive control put on the slide according to Bragoni et al. ) and negative controls (by omitting the primary antibody). Cases carrying predicted damaging variants in HNF1alpha and cases with no variants in the gene were evaluated by IHC from FFPE surgical specimens. IHC was performed for HNF1alpha and scoring was carried out by two independent expert pathologists, blindly with respect to the mutation status. IHC analysis for SMAD4 and p53 was carried out as described previously . Evaluation of SMAD4 immunostains was performed by two expert pathologists. For each case, the percentage of neoplastic cells with SMAD4 preserved or lost immunosignal was collected. 2.5. Statistical Analysis The kh2 test or Fisher's test (an expected number less than five) and the Mann-Whitney test were used to analyze categorical and continuous variables, respectively. The correlations were analyzed with Spearman's rho coefficient. Survival analysis was performed using the Kaplan-Meier method and the log-rank test. p-values < 0.05 were considered significant. Data were analyzed using SPSS (version 15.0) (SPSS Inc., Chicago, IL, USA) and Prism (GraphPad Software Inc., San Diego, CA, USA). Univariate and multivariate (forward stepwise conditional method) Cox regression analyses were performed to estimate the effects of clinical, genetic, and pathological parameters on CSS. In the stepwise procedure, significance levels of 0.05 for entering and 0.10 for removing the respective explanatory variables were used to determine the independent risk factors. For the power calculations, we used G*Power version 3.1.9.6 . 3. Results 3.1. Genetic Alterations Identified in the EAC Samples A total of 337 variants were identified across the whole cohort of 164 EAC cases . All of the FFPE samples achieved good sequence representation with average coverage among samples of 700x. Examples of identified mutations are reported in Figure 1B. Point mutations were the most frequent variations (82.21%), followed by insertions and deletions (17.78%). TP53 was the most frequently altered gene, with 110/164 cases carrying at least one mutation in this gene (67.1%). Out of the 110 variants in the TP53 gene, there was a prevalence in missense (77) vs. loss of function (LOF, including premature stop codons, splice site alterations, and frameshift variants) (33) variants. Five cases carried two variants in TP53. Most of the mutations have already been reported in the "TP53 database" accessed on 10 October 2022) and were functionally analyzed: 76 out of 77 missense changes (98.7%) in TP53 found in our EAC cohort were functionally damaging (Supplementary Table S1). Alterations in other genes occurred at a lower frequency, with ATM (18%), MSH6 (11%), PI3KCA (9%), APC and SMAD4 (8%), and CDKN2A and SMARCA4 (7%) being the most frequently hit genes. The majority of the samples carried concurrent variants in different genes . 3.2. HNF1alpha Mutations in EAC We found seven variants in the HNF1alpha gene, encoding for a tumor suppressor protein; in seven cases , the gene that we previously found mutated in a small number of EAC cases . The mutations mapped to the DNA binding domain (three single nucleotide substitutions and one frameshift indel variant) and to the transactivation domain (two single nucleotide substitutions and one frameshift indel variant) of HNF1alpha. The missense variants were predicted to be damaging according to the prediction program MCAP (MCAP score > 0.7; accessed on 15 November 2022) . In six out of sevem cases, HNF1alpha variants occurred in association with other gene alterations . We evaluated via IHC analysis the protein expression profiles of the available samples carrying the different HNF1alpha variants vs. a case without mutations (the control). Compared to the control sample, decreased staining was observed in the patients with HNF1alpha damaging variants. The decrease in staining correlated to an increased frequency of the variant alleles in the tumor, as detected by NGS data analysis . 3.3. Correlation of Variants in Different Genes As already reported in many studies, we found a variety of genetic alterations in the 164 samples analyzed via NGS, with TP53 being the most mutated gene. To evaluate whether mutations co-occurred significantly in specific genes, we performed a correlation analysis between the damaging variants identified in the different oncology-related genes, using Spearman's rho coefficient. We identified several statistically significant positive correlations between the presence of mutations in specific genes, as well as several negative correlations, as reported in Supplementary Table S3. TP53 mutations, as an example, correlated positively with CDKN2A (0.162, p = 0.035) but correlated negatively with ATM (-0.147, p = 0.047), HNF1alpha (-0.166, p = 0.031), and MET (-0.195, p = 0.011). HNF1alpha on the other hand, correlated positively with PIK3CA (0.248, p < 0.001), CTNNB1 (0.281, p < 0.001), and RET (0.161, p = 0.034), suggesting that specific genes were concurrently mutated in these tumors. We also assessed in the COSMIC project COSU535, containing data on 409 EAC cases, and the presence of co-occurring variants between genes and found mutations of TP53 and APC (21/409, 5%), TP53 and CDKN2A in 25/409 (6%), and TP53 and SMAD4 in 30/409 (7%) in the same samples, reinforcing the concept of the genetic heterogeneity of EAC. 3.4. Evaluating Associations between Genetic Variants and Histopathological and Clinical Phenotypes In order to connect the presence of genetic variants with clinical and/or morpho-functional characteristics, we performed further analyses taking into account cancer-specific survival (CSS), recurrence, and the EACSGE classification, introduced by Fiocca et al. . This classification was based on morphological features of esophageal/esophagogastric junction adenocarcinoma, which divided the cases into two main categories with a different prognose: lower risk, including glandular well differentiated (GL WD), mucinous muconodular carcinoma (MMC), and diffuse desmoplastic (DDC) subgroups; and higher risk, including glandular poorly differentiated (GL PD), diffuse anaplastic (DAC), invasive mucinous carcinomas (IMC), and mixed (MIX) subgroups. This analysis provided significant data only for TP53, since the number of mutations in this gene was high enough to allow a statistical association to different parameters. We estimated the clinical outcomes in relation to the presence of TP53 variants and to the specific types of TP53 variants, i.e., missense variants or LOF variants. Poor survival and recurrence were significantly associated with TP53 mutations (p = 0.039; Supplementary Table S4A; p = 0.031, Supplementary Table S4B, respectively). Considering the EACSGE classification in the lower risk and higher risk groups, the presence of TP53 mutations and the higher risk group were significantly associated (p = 0.022; Supplementary Table S4C). These data prompted us to extend the analysis to include additional EAC cases for which we had genetic material and the TP53 mutation status, the clinical parameters, and the morphological classification according to EACSGE for a total of 202 individuals. The overall results are presented in Figure 2A,B and Supplementary Table S5A,B. We could show that cancer-specific survival was negatively affected by the presence of missense mutations in the higher risk cases (p = 0.001, Supplementary Table S5A), as also shown by Kaplan-Meier curve analysis . Considering the different subclasses of the higher and lower risk groups, we could observe how the statistical association was mainly driven by the GD-PD classes in the presence of missense variants in the TP53 gene . TP53 mutations and age also showed a significant association, as reported in Supplementary Table S5C (p = 0.029, Kruskal-Wallis test). We investigated whether the presence of the different types of TP53 variants (missense and LOF) could be detected by immunohistochemical analysis of the tumor specimens. We evaluated the presence of different types of variants and the staining pattern observed for p53 in terms of overexpression or loss of staining (Supplementary Table S6), according to our previously reported methods , in which missense variants were associated with p53 staining. We found a significant association between the type of mutations and patterns of p53 staining also for LOF variants vs. cases without TP53 variants . 3.5. SMAD4 Expression Loss and EAC Survival We recently reported that SMAD4 loss of immunoreactivity was not an infrequent event in EAC, even in absence of gene mutations . Therefore, we extended the analysis to a larger sample of EAC tissues from the EACSGE consortium and correlated it with genetic, histopathological, and clinical data . First, for the group of cases where we had the TP53 status and p53 immunostaining, we evaluated whether any correlation with the SMAD4 immunostaining pattern was significant. Indeed, we found that the presence of LOF variants in TP53 correlated with SMAD4 loss of staining in the corresponding tumor tissue (as defined in the Materials and Method section, p = 0.008, Supplementary Table S8). Therefore, we investigated whether any loss of SMAD4 immunostaining was relevant or whether a more informative SMAD4 loss cut-off value could be identified. Through ROC curve analysis (Supplementary Table S9), loss of immunostaining in at least 35% of neoplastic cells resulted to be the best discriminator with the greatest sensitivity and specificity. Applying this cut-off value in our case series, 85 cases were defined as SMAD4 loss cancers out of the 245 EAC cases from the entire EACSGE consortium . When considering the EACSGE histopathological classification, the SMAD4 pattern of immunostaining was significantly correlated with CCS and disease-free survival. SMAD4 loss was correlated with poor CSS and disease-free survival in EACSGE higher risk cases but not in lower risk cases (p = ns). Post-hoc analysis revealed that the study had 0.772 power to detect a 0.25 effect size . 3.6. Univariate and Multivariate Cox Regression Analysis Univariate and multivariate Cox regression analyses were performed to estimate the effects of clinical, genetic (TP53), SMAD4 loss (cut-off > 35), and pathological parameters on CSS. As reported in Supplementary Table S9A, the univariate Cox regression analysis showed a statistical association for age, stage, lymph node status, and EACSGE risk (p = 0.028, p = 0.001, p < 0.001, and p = 0.003, respectively), whereas in the multivariate analysis, only age, lymph node ratio, and EACSGE risk retained significance (p = 0.005, p < 0.001, and p = 0.023, Supplementary Table S9B). 3.7. Gene Fusion Analysis from RNA Sequencing Twenty-two samples, with RNA quality compatible with massive parallel sequencing were sequenced at high coverage for 1385 oncology-relevant genes. Data analysis was performed with an in-house pipeline which is based on the combination of data obtained using four independent tools for fusion detection, e.g., FusionCatcher, STAR-Fusion, RNA-Seq Alignment v.1.1.0, and TopHat Alignment v.1.0.0. From the 64 candidate fusions identified by combining the results of the four tools, the pipeline retained eight after filtering analysis. The selected gene fusions were selected by two to four tools (Supplementary Table S10). The eight gene fusions were identified in six different EAC cases, but we could confirm with an independent method (Sanger sequencing) six gene fusions in four cases (4/22, 18.2%, Supplementary Table S10). Interestingly, in the two cases carrying two different gene fusions, one of the rearrangements was the same, the CYP2C19-CYP2C18 fusion on chromosome 10 . The other gene fusions involved the GIPC1-DNAJB1 rearrangement in one case and PI4KA-MAPK1 in the other case. The GAIP-interacting protein C-terminus (GIPC1) is a regulator of autophagy and cellular trafficking and its overexpression is associated with poor survival in several cancers . DNAJB1 encodes for a molecular chaperone involved in protein folding and autophagic mechanisms. The DNAJB1-PRKACA fusion transcript has been identified in many cases of fibrolamellar hepatocellular carcinoma . The gene encoding for the phosphatidylinositol 4-kinase alpha (PI4KA) was detected in two different gene fusion EAC samples . PI4KA plays a critical role in regulating tumorigenesis by activating tumor-promoting signals such as the RAS pathway . The gene fusion IQCE-DGKB involved an IQ motif containing E gene, which is important in limb morphogenesis and also acts as regulator of Hedgehog signaling and the gene for diacylglycerol kinase beta (DGKB). The diacylglycerol kinases are key regulators of the intracellular concentration of the second messenger diacylglycerol (DAG) and play a key role in cellular processes. This gene has been found in other fusions with different genes in prostate cancer . All of the detected gene fusions involved oncology-related genes, but they have not been reported in esophageal adenocarcinoma. 4. Discussion Esophageal adenocarcinoma represents a substantial health concern in Western countries due to its increasing incidence and poor prognosis. Rapid advances in high-throughput NGS have highlighted high EAC intratumor heterogeneity, with many structural genomic rearrangements and mutations arising even clonally , and epigenetic dysregulation of specific genes giving rise to tumor entities that may behave very differently in terms of progression and resistance . Therefore, there is an increasing interest in defining molecular biomarkers for patient stratification and prognosis . In our study, we focused our attention on a panel of cancer-related genes previously found recurrently mutated in a small cohort of EAC cases. In the 164 novel cases assessed, the EAC samples presented mutations in different genes, including HNF1alpha. HNF1alpha is a transcription factor, regulates epithelial to mesenchymal transition, and is considered a tumor suppressor . In concordance with its role as a tumor suppressor, the majority of the variants were LOF, with a remarkable decrease in protein expression in the tumor specimens compared to cases with no mutations in this gene. HNF1alpha mutations were associated with other mutations in most of our cases, as we observed this for several genes, concurrently mutated in the same samples. However, we did not address the overall mutational signatures, in terms of specific nucleotide changes as detected with programs such as Signature Mutational Analysis (Sigma) or Mix , but only whether specific genes showed concurrent or mutually exclusive mutations. Regarding the identified gene mutations, TP53 was the most frequently mutated gene, as reported in previous studies . Indeed, TP53 is the most mutated gene in the group of chromosomally unstable carcinomas of the esophagus and of the esophageal junction and tumors that are histologically predominantly intestinal. Thus, it is not surprising that in our classification, they are mainly GD-PD with TP53 mutations, but it is remarkable that in GD-PD, this finding has prognostic significance. Moreover, we evaluated the effect of specific types of mutations (missense changes vs. loss of function) in correlation with histological and clinical data and could observe that in the cases classified as "higher risk" according to the EACSGE classification, the presence of damaging missense variants in TP53 negatively affected cancer-specific survival, It is however worth noting that TP53 mutations are early events in the progression from esophageal dysplasia to cancer ; therefore, the early identification of specific types of variants, i.e., damaging amino acid substitutions, might be of critical importance, especially from the perspective of selecting the most efficient approach for targeted therapies. It is important to note that missense changes in p53 can alter protein folding, structure, and therefore DNA-binding and transcriptional activity. Targeting mutant p53 with missense changes is indeed an active research field in order to induce p53 activity similar to the wild-type protein . Mutations that led to a loss of p53 proteins (such as nonsense and frameshift variants, LOF) were frequently associated with the loss of SMAD4 expression. The SMAD4 tumor-suppressor gene is pivotal for the downstream signaling of bone morphogenetic proteins (BMPs) . Notably, SMAD4 has been reported as frequently lost in gastrointestinal cancer . SMAD4 loss is associated with non-canonical BMP signaling leading to a more metastatic phenotype, poor prognosis, and poor response to treatment . A previous study showed that SMAD4 mutations or homozygous deletions were associated with significantly poorer prognosis in EAC . A recent study in preclinical models of EAC development showed that SMAD4 inactivation was sufficient per se to initiate tumorigenesis in a high-grade dysplastic esophagus in vivo . Moreover, inhibition of the overactive non-canonical BMP signaling in SMAD4-negative tumors decreased malignancy and improved survival . Notably, SMAD4 expression status resulted in being a prognostic factor in our cohort of cases when connected to the EACSGE classification, allowing us to discriminate patients with a worse prognosis into the higher risk group. Nevertheless, when using multivariate Cox regression analyses for CSS and different variables, these associations with TP53 or SMAD4 status were not so well-defined, whereas age, lymph node status, and EACSGE risk still retained a significant correlation. Therefore, further studies in independent and large samples are warranted in order to evaluate the clinical-pathological correlation with specific types of TP53 mutations and SMAD4 expression. A limit of our study is that on the tumor DNA extracted from paraffin-embedded tissue biopsies, we performed a targeted analysis of a discrete number of oncology-related genes and did not perform a whole exome or whole genome analysis. Thus, we were not able to also evaluate the presence of copy number alterations (CNAs), because our target gene panel was designed to test for single nucleotide or small insertion/deletion variants. Nevertheless, we observed a number of gene fusion transcripts (18.2%) using a high throughput RNA sequencing approach involving oncology-related genes. Gene fusion products can become ideal therapeutic targets, as observed in other cancers . The identified gene fusions have not been reported previously in EAC and in three cases out of the four carrying the identified gene fusions, TP53 was mutated. Although the number of cases for which RNA was available was too small to drive statistically significant conclusions, we suggest that this analysis would add an additional step toward understanding the molecular complexity of EAC, in accordance with other studies investigating the structural rearrangements in EAC . In this view, we suggest that the investigation of molecular markers together with a histopathological analysis can provide relevant clinical information for patient stratification, treatment, and prognosis. The development of therapies targeting specific pathways, based on the status of molecular biomarkers, will improve EAC clinical management. 5. Conclusions In our study on EAC, we were able to correlate EAC histological classification, clinical outcomes, and molecular phenotypes. First, we identified loss-of-function mutations in HNF1alpha, a tumor suppressor gene with a likely role in tumor progression. Next, we showed that TP53 missense mutations are associated with higher risk cases, and in this sub-group, they could contribute to a poorer outcome (CSS). TP53 truncating mutations were associated with SMAD4 loss, and SMAD4 loss itself was a frequent event in EAC, correlated with lower CSS and disease-free survival in higher risk cases. Therefore, we showed that combining molecular and histological analyses could be a successful strategy to better stratify patients. This could contribute to identifying those patients with a worse prognosis and to selecting a tailored therapy based on molecular markers. Acknowledgments The present study was developed and performed in the framework of the EACSGE group (Esophageal Adenocarcinoma Study Group Europe) research program. Esophageal Adenocarcinoma Study Group Europe (EACSGE)--Coordinator: Sandro Mattioli University of Bologna, Bologna, Italy: Sandro Mattioli, Marialuisa Lugaresi, Antonietta D'Errico, Deborah Malvi, Elena Bonora, Federica Isidori, Isotta Bozzarelli, Arianna Orsini, Erica Cataldi-Stagetti; Antwerp University Belgium,: Kausilia K. Krishnadath; University of Genova, Genova, Italy: Roberto Fiocca, Luca Mastracci, Federica Grillo; University of Helsinki, Helsinki, Finland: Jari Rasanen, Ari Ristimaki, Henna Sodestrom; IRST-IRCCS Meldola Oncology Institute, Meldola, Italy: Giovanni Martinelli, Anna Ferrari; European Institute of Oncology, Milan, Italy: Uberto Fumagalli Romario, Stefano De Pascale, Luca Bottiglieri; Humanitas Clinical and Research Center-IRCCS, Rozzano, Italy: Paola Spaggiari; University of Verona, Verona, Italy: Giovanni De Manzoni, Simone Giacopuzzi, Anna Tomezzoli; University Vita-Salute San Raffaele Milan, Italy: Riccardo Rosati, Paolo Parise, Luca Albarello. Supplementary Materials The following supporting information can be downloaded at: Table S1: TP53 variant classification according to TP53 database. Table S2: Degree of staining for HNF1alpha, % of variant alleles in tumors, tumor staging and lymph node status for the samples mutated in HNF1alpha. Table S3: Correlation analyses for the different gene mutations found in 164 EAC cases. Table S4: Cancer-specific survival and recurrence for the different types of TP53 mutations. Cross tabulation analysis using Chi-square test with Pearson's correction, degrees of freedom = 3). Table S5. Cancer-specific survival, TP53 mutations and EACSGE classification. Table S6: Correlations between TP53 mutations and p53 immunostaining. Table S7: Spearman's correlation coefficient for TP53 mutation types and p53 immunostaining patterns (IHC).TP53 mutations: 0 = wild-type, 1 = missense, 2 = LOF, p53 immunostaining: 0 = normal expression, 1 = overexpression, 2 = null expression). Table S8: Correlation between TP53 LOF mutations and loss of SMAD4 immunostaining. (Mann-Whitney's test; grouping variable: type of TP53 mutations). Table S9: Cox regression analyses for CSS and clinical, genetic, pathological variables. Table S10: Gene fusions detected in EAC samples. Click here for additional data file. Author Contributions Conceptualization, E.B., A.O., R.F. and S.M.; methodology, A.O., I.B., L.M., D.M., A.D., A.F., F.I. and E.C.-S., software, A.O., F.I. and M.L.; validation, L.M. and M.L.; formal analysis, M.L.; investigation, A.O., I.B., L.M., D.M., A.D., A.F., F.I., E.C.-S. and M.L.; resources, P.S., A.T., L.A., A.R., L.B., R.R., U.F.R., G.D.M., J.R., S.M. and K.K.K.; data curation, A.D., M.L., R.F., A.O. and E.B.; writing--original draft preparation, A.O., I.B., L.M. and E.B.; writing--review and editing, K.K.K., S.M., G.M. and R.F.; visualization, D.M., L.M., R.F. and A.D.; supervision, S.M. and the EACSGE Consortium; funding acquisition, E.B. and S.M. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study received approval (# L3P1223) from the Ethical Committee "Comitato Etico IRST IRCCS AVR (CEIIAV)"--Italy (Reg. Sper. 109/2016 Protocol 7353/51/2016) on 5 December 2016. Informed Consent Statement Written informed consent was obtained from all of the patients before inclusion in the study. Data Availability Statement All data are available from the authors upon request. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Gene variants identified in 164 EAC cases. (A) Variants identified in the EAC cohort; in red "missense"; in blue "LOF (frameshift and stop codon)". (B) Representation of two TP53 mutations (visualized using Integrative Genomic Viewer, IGV): a missense (p.Arg248Trp) and a frameshift (p.Met160TrpfsTer10). The display shows individual forward (F) sequence reads in red and reverse (R) reads in blue. Selected positions are covered by a high number of aligned sequenced reads and both mutations can be seen in approximately half of the F and R reads. (C) Mutations in the HNF1alpha gene were identified in the EAC samples and mapped to the different protein domains. (D) Examples of the immunohistochemical patterns observed in a control sample (i.e., no HNF1alpha mutations) vs. cases carrying different alterations in the HNF1alpha gene. In particular, we showed the expression pattern in two cases with the HNF1alpha p.Arg168His variant or the p.His505Asn; the decreased staining suggested that the misfolded proteins might be degraded. Scale bar 500 mm. Figure 2 Cancer-specific survival of EAC cases with TP53 missense variants and p53 expression profiles. (A) Data are shown according to the higher and lower risk groups. (B) Data are shown for the EACSGE morphological subgroups. (C-E) Immunohistochemical patterns for p53 immunostaining in the EAC cases with different types of variants of TP53: (C) control case with no variant in TP53 vs. loss of function (LOF) (D,E). Scale bar 100 mm. Figure 3 SMAD4 expression patterns and correlation with survival. (A) Immunohistochemical patterns observed for SMAD4 expression. Intense preserved SMAD4 immunostain in a sample of differentiated glandular adenocarcinoma (i) and in a sample of mucinous muconodular adenocarcinoma (ii). A sample of glandular adenocarcinoma with preserved (right side) and complete loss of SMAD4 expression in the same neoplastic gland (iii). Complete loss of SMAD4 in glandular adenocarcinoma with retained expression in the squamous epithelium overlying cancer (iv). Scale bar, 100 mm. (B) Cancer-specific survival and (C) disease-free survival of EAC cases with loss of SMAD4 staining (in >35% of the neoplastic area) in EACSGE higher risk cases. Figure 4 Reconstruction of the different gene fusions identified and validated in the EAC samples. The breakpoints in the gene transcripts and corresponding protein regions and domains are indicated for the genes involved in each gene fusion (A-D). Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000514 | Extrahepatic spread is a well-known negative prognostic factor in patients with advanced hepatocellular carcinoma (HCC). The prognostic role of different metastatic sites and their response rate to systemic treatment is still being debated. We considered 237 metastatic HCC patients treated with sorafenib as first-line therapy in five different Italian centers from 2010 to 2020. The most common metastatic sites were lymph nodes, lungs, bone and adrenal glands. In survival analysis, the presence of dissemination to lymph nodes (OS 7.1 vs. 10.2 months; p = 0.007) and lungs (OS 5.9 vs. 10.2 months; p < 0.001) were significantly related to worse survival rates compared with all other sites. In the subgroup analysis of patients with only a single metastatic site, this prognostic effect remained statistically significant. Palliative radiation therapy on bone metastases significantly prolonged survival in this cohort of patients (OS 19.4 vs. 6.5 months; p < 0.001). Furthermore, patients with lymph node and lung metastases had worse disease control rates (39.4% and 30.5%, respectively) and shorter radiological progression-free survival (3.4 and 3.1 months, respectively). In conclusion, some sites of an extrahepatic spread of HCC have a prognostic impact on survival in patients treated with sorafenib; in particular, lymph nodes and lung metastases have worse prognosis and treatment response rate. hepatocellular carcinoma liver cancer metastases sorafenib systemic therapy radiation therapy outcome This research received no external funding. pmc1. Introduction Primary liver tumors are the sixth most common cancer and the third cancer-related cause of death worldwide with more than 900,000 new cases/year and 830,000 deaths/year. Among liver tumors, hepatocellular carcinoma (HCC) represents by far the most frequent histological type . Despite the improvement in therapeutic strategies, the overall survival for advanced HCC patients remains poor. According to Barcelona Clinic Liver Cancer, advanced HCC (BCLC-C) is defined by the presence of macrovascular invasion (MVI), extrahepatic spread (EHS) and/or a cancer-related deterioration of general condition based on the Eastern Cooperative Oncology Group Performance Status (ECOG-PS > 0) . International guidelines all agree on starting systemic therapy for advanced HCC or intermediate stage (BCLC-B) not amenable or refractory to locoregional therapies . Since 2008, tyrosine-kinase inhibitors (TKIs) have played a central role in the pharmacologic scenario of advanced HCC. Sorafenib was the first approved drug as first-line therapy, and it represented the only therapeutic choice for these patients for about a decade . In the last five years, several new TKIs have been approved for the treatment of HCC patients: lenvatinib as an alternative first-line therapy , regorafenib as a second-line therapy after progression to sorafenib , and cabozantinib as both third-line therapy . The presence of EHS represents an indirect sign of tumor biological aggressiveness, and its negative prognostic impact on patients' survival has been widely demonstrated . The most common metastatic sites of HCC are lymph nodes, lungs, bone and adrenal glands . The prognostic role played by the different metastatic sites is less known, and their response rate to TKIs have not been yet defined in literature. The aim of the present study is to verify whether the different metastatic sites have clinical relevance in a large multicentric population of patients treated with sorafenib for metastatic HCC. 2. Materials and Methods 2.1. Design of the Study This study was performed using medical records from the ARPES database, a prospective multicenter registry of all consecutive HCC patients treated with sorafenib as first-line therapy. This registry was created in 2010, and it includes patients from five different Italian Centers (IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna; Cardarelli Hospital, Naples; Papa Giovanni XXIII Hospital, Bergamo; Azienda Ospedaliero-Universitaria Pisana, Pisa; Humanitas Clinical and Research Center, Milan, Italy). Data were entered every 3-6 months by co-investigators from each center and checked by the coordinating center for internal consistency. For this study, we considered patients with radiological detection of extrahepatic HCC localizations who started sorafenib from January 2012 to December 2020. The closing follow-up date was 31 October 2022 in order to allow an adequate follow-up period. 2.2. Baseline and Re-Evaluation Baseline characteristics including sex, age, laboratory findings (bilirubin, albumin, alpha-fetoprotein), liver disease characteristics (etiology, Child-Pugh score, intrahepatic tumor burden) and tumor features (MVI, EHS, ECOG-PS) were present for all patients. In all patients with EHS, the organ(s) affected by metastases was known and recorded. In all patients, a baseline contrast-enhanced CT scan of thorax and abdomen was performed within 30 days before start of sorafenib and then every 12 +- 2 week for tumor response assessment. Treatment response from target lesions was recorded according to Response Evaluation Criteria In Solid Tumours (RECIST) v1.1 . 2.3. Management of Sorafenib Sorafenib was started at the usual dosage of 400 mg bid. Dose modifications (reduction or temporary discontinuation) were performed in case of occurrence of intolerable adverse events. Sorafenib was permanently discontinued in case of (i) clinical and radiological progression of disease (for patients eligible for a second-line licensed drug or a clinical trial, radiological progression was considered sufficient for sorafenib interruption), (ii) unacceptable severe toxicity or intolerance and (iii) significant liver function deterioration. According to daily clinical practice and following a multidisciplinary team discussion, concomitant or sequential locoregional treatments could have been potentially performed for better tumor burden control; such patients were also included in the database considering the real-life observational nature of the registry. 2.4. Statistical Analysis Categorical variables were expressed as absolute and relative frequencies; continuous variables were expressed as mean and standard deviation. Comparisons between groups were performed using the chi-squared test for categorical variables and with Student's t test for continuous variables. Overall survival (OS) was measured from sorafenib starting date until date of patient death; last follow-up visit if no additional information could be retrieved or end of follow-up period. Radiological progression-free survival (rPFS) was measured from sorafenib starting date until date of radiological progression of disease, death or end of follow-up period. Survival curves were estimated using the Kaplan-Meier method. Stratification of predicting factors was analyzed with Log-rank test. In order to define the independent correlation between predictive variables and survival, we performed a time-dependent covariate survival approach, including the statistically significant (p < 0.05) variables from the univariate Cox analysis. Statistical analysis was performed using SPSS Statistic for MacOSX (version 24.0; IBM, Armonk, NY, USA). 3. Results 3.1. Study Population From the entire ARPES database of 712 patients, we considered for this study only 237 patients (33.2%) with radiological detection of EHS. Most patients were male (85.2%), cirrhotic (94.1%) and with viral etiologies (69.6%). Almost all patients (95.4%) presented preserved liver function defined as Child-Pugh A; remaining patients were all in Child-Pugh score B7 liver functional class. Baseline characteristics of study population compared with other patients in ARPES registry are summarized in Table 1. The most frequent sites of metastases were lymph nodes (48.1%), lungs (30.4%), bone (18.6%) and adrenal glands (11.0%); remaining metastatic sites presented a frequency < 5%. Multiple concomitant sites of metastases were recorded in 48 patients (20.2%) . Baseline characteristics of patients with lymph node, lung, bone and adrenal gland metastases compared with other patients of the study population are reported in Table 2. 3.2. Survival Analysis The univariate analysis of OS showed that compromised liver function (Child-Pugh B), high albumin-bilirubin grade (ALBI > 1), elevated serum alpha-fetoprotein values (AFP > 400 ng/mL), intrahepatic tumor burden > 50% (ITB > 50%), cancer-related deterioration of general conditions (ECOG-PS > 0), presence of microvascular invasion (MVI) and occurrence of dermatological adverse events during treatment (DAEs) were associated with patients' prognosis. A statistically significant independent correlation with survival was confirmed in the multivariate analysis for Child-Pugh B (HR 3.105, p = 0.002), AFP > 400 ng/mL (HR 1.396, p = 0.030), ITB > 50% (HR 1.543, p = 0.006), MVI (HR 1.770, p < 0.001) and DAEs (HR 0.755, p = 0.045). Regarding the sites of metastases, the presence of lymph node, lung and multiple site localizations of disease were associated with worse prognosis. A statistically independent correlation with survival was confirmed in the multivariate analysis for lymph node (HR 1.545; OS 7.1 vs. 10.2 mo; p = 0.007) and lung metastases (HR 2.110; OS 5.9 vs. 10.2 mo; p < 0.001) compared with patients with metastatic HCC without lymph node or lung localizations, respectively . After stratification of patients with lymph node and lung metastases, patients with the co-presence of these two metastatic sites had worse survival rates compared to those who presented only lymph node (HR 2.014; OS 5.0 vs. 7.4 mo; p = 0.006) or only lung metastases (HR 1.762; OS 5.0 vs. 6.5 mo; p = 0.040). 3.3. Subgroup Analysis in Patients with Single Site of Metastases In order to more accurately define the prognostic role of different site of metastases, we performed a subgroup survival analysis in patients with single metastatic site (n = 189). In this cohort of patients, Child-Pugh B (HR 5.661, p < 0.001), AFP > 400 ng/mL (1.464, p = 0.026), ITB > 50% (HR 1.614, p = 0.009) and presence of MVI (HR 1.770, p = 0.001) were significantly related to worse survivals. Regarding the sites of metastases, the presence of lymph nodes, lung and bone localizations of disease were associated with patient prognosis. In the multivariate analysis a statistically independent correlation with survival was confirmed only for lymph node (HR 1.645; OS 7.3 vs. 10.3 mo; p = 0.021) and lung metastases (HR 2.182; OS 6.5 vs. 10.2 mo; p = 0.002) compared with patients with metastatic HCC without lymph node or lung localizations, respectively . 3.4. Metastases Focused Combination Treatments In order to control extrahepatic tumor burden, locoregional combination treatments were performed in 28 patients. Among these, 3 patients had lymph node metastases (all received stereotaxic radiotherapy), 2 patients had pulmonary metastases (a patient received stereotaxic radiotherapy, the other received radiofrequency ablation) and 21 patients had bone metastases (all received radiotherapy with antalgic purpose). No surgical treatments (i.e., metastasectomy) have been performed in any patients of the study population. Due to the high number of treatments focused on bone metastases, we performed survival analysis in this cohort of patients. Radiation therapy was associated with a significant survival benefit in patients with bone metastases (HR 0.137; OS 19.4 vs. 6.5 mo; p < 0.001) . 3.5. Time to Progression According to Site of Metastases A re-evaluation of all CT images was also performed in order to assess the radiological progression-free survival (rPFS) of each site of metastases. A dimensional increase of at least 20% from baseline of a target metastatic lesion or the occurrence of a new lesion in a specific site of metastases was considered as progression of disease in that metastatic site. The rPFS of lymph node, lung, bone and adrenal gland metastases was 3.4 (95% CI 3.1-3.7; p = 0.930), 3.1 (95% CI 2.9-3.3; p = 0.107), 5.2 (95% CI 4.6-5.8; p = 0.126) and 4.5 (95% CI 3.5-5.4; p = 0.719) months, respectively. No statistically significant differences in rPFS were observed among different metastatic sites . The disease control rates (DCRs) of the four abovementioned sites of metastases were 39.5%, 30.5%, 75.0% and 61.5%, respectively. 4. Discussion Sorafenib represented the only available therapeutic option for patients with advanced HCC for several years. Since its approval, real-life studies have shown a progressive improvement in the survival of patients treated with sorafenib thanks to a better management of drug-related adverse events . In order to better understand the wide response variability among patients, several authors investigated predictors of survival. In the last few years, several studies showed how clinical , laboratory and pharmacologic features could influence the prognosis of patients with advanced HCC; for instance, the presence of EHS is a well-known predictor of negative prognosis. Regarding the actual impact of different sites of metastases on prognosis, evidence is scarce, and results are often contradictory. Two recently published works on this topic are the study of Zhan H et al., based on the American epidemiologic registry SEER (Surveillance, Epidemiology and End Results) that gives OS results , and the study of Huang SF et al., based on the national registry of Taiwan that gives PFS results . In the first study, lymph nodes were not considered as a metastatic site, and less than a half of patients were on systemic treatment; in the second study all patients with advanced HCC were analyzed, including those without EHS. In the study of Zhan H et al., the OS was negatively related to multiple metastatic sites, pulmonary, bone (only after propensity score matching) and lymph nodes metastases (considered as a potential influencing factor in survival analysis). In the study of Huang SF et al., the PFS was negatively related to lung and bone metastases and positively related to lymph node metastases (only in the cohort of patients with single metastatic site). In both studies, high rates of surgical and radiation treatments were reported, but the target metastatic site was not specified. In the current study we reported that the presence of lung or lymph node metastases are negative independent prognostic factors with a median OS of 5.9 and 7.1 months, respectively; the co-presence of these two metastatic sites reduced the median OS at 5.0 months. In the subgroup analysis of patients with a single metastatic site, a statistically significant correlation between lung and lymph node metastases and prognosis was confirmed. Lung and lymph node metastases did not reach statistical significance in rPFS analysis even though a negative trend is represented in survival curves. Concerning adrenal gland metastases, the fourth most common metastatic site, they did not reach statistical significance in any survival analysis, but the small sample size (26 cases) could be a determinant. Adrenal gland metastases have not been evaluated in any above-mentioned study. There are only case reports and case series on this topic in the literature, so our results on OS and rPFS (10.3 and 4.5 months, respectively) provide original, relevant information. Combination treatments, both surgical and radiation ones, are widely used to control the tumor burden and to improve patients' outcome . In our study population, palliative radiation therapy on bone metastases was the most common treatment performed, so it was possible to conduct subgroup analysis in this cohort of patients. Although there was no oncologic radical purpose, antalgic radiation therapy contributed to a significant improvement in survival (median OS 19.4 vs. 6.5 months). This result could explain the positive trend observed in bone metastases OS curves. Recently, it has been demonstrated how curative radiation therapy increases survival in patients with oligometastatic (up to 5 bone lesions) solid tumors and HCC . Nowadays, no conclusive results on the prognostic impact of palliative radiation therapy have been published . In the last few years, a rapid and progressive change in the management of advanced HCC patients has occurred, leading to improved prognosis. This was due to the approval of drugs for post-sorafenib treatment and the advent of immune checkpoint inhibitors (ICIs). Atezolizumab, a PD-L1 inhibitor, in association with bevacizumab, is the current front-line therapy for advanced HCC , and several clinical trial with ICIs, some of these in combination with TKIs, are now ongoing. With these preconditions, TKI monotherapy seems to be outdated, but it still assumes a central role in the therapeutic scenario for patients with advanced HCC and contraindications to ICIs or solid organ recipients ; furthermore, recent studies seem to highlight that the etiology of underling liver disease could influence the response to different first-line therapies . In the next few years, the ICIs actual efficacy on the different target lesions needs to be assessed due to the close relationship between these new drugs and tumor microenvironment. The final possible aim is to tailor individual therapeutic strategies for each patient with advanced HCC. Despite the large population of this study, the small sample size of less common sites of metastases did not allow us to perform a survival analysis in these subgroups of patients. In the current study, the enrollment of only metastatic patients in therapy with sorafenib and the low rate of concomitant treatments, with the exception of radiation therapy on bone metastases, significantly reduced possible confounders for survival analysis compared with previous studies. 5. Conclusions The presence of lymph node and lung metastases are independent negative prognostic factors in patients with metastatic HCC. Radiation therapy of bone metastases, even with a palliative antalgic purpose, seems to give a survival benefit, and it should be therefore considered for the management of these patients. Author Contributions Conceptualization, L.I. and I.G.; methodology, L.I., F.T. (Francesco Tovoli) and A.G.; formal analysis, L.I. and F.T. (Francesco Tovoli); data curation: L.I., M.T., B.S., R.T., G.M., F.T. (Franco Trevisani), R.S. and T.P.; writing--original draft preparation, L.I.; writing--review and editing, A.G., F.T. (Francesco Tovoli) and F.P. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Area Vasta Emilia Centro (protocol code 2014/Oss/147). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions. Conflicts of Interest F.T. (Francesco Tovoli) has served as a consultant for Bayer, Ipsen, and Eisai and an advisory board member for Laforce. F.T. (Franco Trevisani) is an advisor and a consultant for Bayer and an advisory board member for Sirtex, Alfasigma, and Bristol-Myers Squibb. F.P. has been lecturer or consultant for Bayer, Bracco, Eisai, Esaote, Exact Sciences, Ipsen, Samsung, AstraZeneca, MSD, Roche. All remaining authors have declared no conflict of interest. Figure 1 Study population and metastases localization distribution. * Multiple concomitant sites of metastases were recorded in 48 patients. Figure 2 Kaplan-Meier curves of overall survival in patients with lymph node, lung, bone and adrenal gland metastases. Figure 3 Kaplan-Meier curves of overall survival in patients with lymph node, lung, bone and adrenal gland metastases in the cohort of patients with single site of metastases. The last figure compares the survival curves of four overmentioned most frequent sites of metastases. Figure 4 Kaplan-Meier curves of overall survival in patients with bone metastases treated with combination radiation therapy. Figure 5 Kaplan-Meier curves of radiological progression-free survival for each site of metastases. The last figure compares the survival curves of lymph node, lung, bone and adrenal gland site of metastases. cancers-15-01523-t001_Table 1 Table 1 Baseline characteristics of patients with extrahepatic spread (EHS) compared with all remaining patients without extrahepatic spread (all w/o EHS). The latter is reported and also divided into two groups, which were themselves split in advanced HCC without metastases (BCLC-C w/o EHS) or intermediate HCC (BCLC-B). Variable EHS (n = 237) All w/o EHS (n = 475) p BCLC-C w/o EHS (n = 311) p BCLC-B (n = 164) p Male sex 202 (85.2%) 398 (83.8%) 0.637 264 (84.9%) 0.951 134 (85.2%) 0.355 Age 67.6 +- 11.5 67.8 +- 9.8 0.825 66.7 +- 10.4 0.374 69.7 +- 11.5 0.056 Viral etiology 165 (69.6%) 349 (73.5%) 0.281 231 (74.3%) 0.224 118 (69.6%) 0.630 Child-Pugh B 11 (4.6%) 47 (9.9%) 0.014 40 (12.9%) 0.001 7 (4.6%) 0.792 ALBI > 1 154 (65.0%) 381 (80.2%) <0.001 251 (80.7%) <0.001 130 (65.0%) 0.003 AFP > 400 ng/mL 76 (32.1%) 156 (32.8%) 0.841 116 (37.3%) 0.209 40 (32.1%) 0.115 ITB > 50% 69 (29.1%) 149 (31.4%) 0.545 106 (34.1%) 0.245 43 (29.1%) 0.628 ECOG-PS > 0 60 (25.3%) 126 (26.5%) 0.743 126 (26.5%) 0.743 N.A. - MVI 78 (32.9%) 232 (48.8%) <0.001 232 (48.8%) <0.001 N.A. - AFP: alfa-fetoprotein; ECOG-PS: Eastern Cooperative Oncology Group--Performance Status; ITB > 50%: intrahepatic tumor burden > 50%; MVI: macrovascular invasion. N.A. not applicable. cancers-15-01523-t002_Table 2 Table 2 Baseline characteristics of patients with lymph node, lung, bone and adrenal gland metastases compared with the rest of study population. Variable Yes (n = 114) Lymph Nodes No (n = 123) p Yes (n = 72) Lungs No (n = 165) p Male sex 93 (81.5%) 109 (88.6%) 0.108 61 (84.7%) 141 (85.4%) 0.845 Age 67.7 +- 12.5 67.6 +- 10.6 0.955 66.7 +- 9.8 68.0 +- 12.2 0.436 Viral etiology 81 (71.0%) 84 (68.2%) 0.673 46 (63.8%) 119 (72.1%) 0.062 Child-Pugh B 5 (4.3%) 6 (4.8%) 1.000 5 (6.9%) 6 (3.6%) 0.316 ALBI > 1 81 (71.0%) 73 (59.3%) 0.070 44 (61.1%) 110 (66.6%) 0.449 AFP > 400 ng/mL 36 (31.5%) 40 (32.5%) 0.890 24 (33.3%) 52 (31.5%) 0.880 ITB > 50% 33 (28.9%) 36 (29.2) 0.984 20 (27.7%) 49 (29.6%) 0.874 ECOG-PS > 0 23 (20.1%) 37 (30.0%) 0.100 20 (27.7%) 40 (24.2%) 0.627 MVI 44 (38.5%) 34 (27.6%) 0.090 25 (34.7%) 53 (32.1%) 0.764 Variable Yes (n = 44) Bone No (n = 193) p Yes (n = 26) Adrenal Glands No (n = 211) p Male sex 41 (93.1%) 161 (83.4%) 0.155 25 (96.1%) 177 (83.8%) 0.141 Age 68.4 +- 9.6 67.4 +- 11.9 0.618 67.3 +- 10.6 67.7 +- 11.7 0.867 Viral etiology 34 (77.2%) 131 (67.8%) 0.277 20 (76.9%) 145 (68.7%) 0.134 Child-Pugh B 3 (6.8%) 8 (4.1%) 0.433 1 (3.8%) 10 (4.7%) 1.000 ALBI > 1 26 (59.0%) 128 (66.3%) 0.293 15 (57.6%) 139 (65.8%) 0.375 AFP > 400 ng/mL 16 (36.3%) 60 (31.0%) 0.592 7 (26.9%) 69 (32.7%) 0.659 ITB > 50% 10 (22.7%) 59 (30.5) 0.341 6 (23.0%) 63 (29.8%) 0.813 ECOG-PS > 0 15 (34.0%) 45 (23.3%) 0.204 5 (19.2%) 55 (26.0%) 0.633 MVI 9 (20.4%) 69 (35.7%) 0.053 7 (26.9%) 71 (33.6%) 0.659 AFP: alfa-fetoprotein; ECOG-PS: Eastern Cooperative Oncology Group--Performance Status; ITB > 50%: intrahepatic tumor burden > 50%; MVI: macrovascular invasion. cancers-15-01523-t003_Table 3 Table 3 Univariate and multivariate Cox regression analysis of overall survival. Variable Univariate HR (95% CI) p Multivariate HR (95% CI) p Male sex 1.089 (0.758-1.564) 0.644 Viral etiology 0.918 (0.695-1.212) 0.546 Child-Pugh B 3.615 (1.952-6.696) <0.001 3.105 (1.538-6.268) 0.002 ALBI > 1 1.367 (1.038-1.801) 0.026 1.216 (0.904-1.637) 0.196 AFP > 400 ng/mL 1.478 (1.120-1.950) 0.006 1.396 (1.033-1.887) 0.030 ITB > 50% 1.550 (1.550-2.080) 0.003 1.543 (1.130-2.109) 0.006 ECOG-PS > 0 1.552 (1.152-2.092) 0.004 1.288 (0.926-1.791) 0.133 MVI 2.014 (1.522-2.080) <0.001 1.770 (1.301-2.409) <0.001 DAEs 0.759 (0.579-0.971) 0.029 0.755 (0.573-0.994) 0.045 Lymph nodes 1.487 (1.149-1.925) 0.003 1.545 (1.127-2.117) 0.007 Lungs 1.569 (1.186-2.075) 0.002 2.110 (1.484-2.999) <0.001 Bone 0.759 (0.546-1.055) 0.100 Adrenal glands 0.768 (0.506-1.164) 0.213 Multiple sites 1.505 (1.0.91-2.075) 0.013 1.041 (0.702-1.544) 0.842 AFP: alfa-fetoprotein; DAEs: dermatologic adverse events; ECOG-PS: Eastern Cooperative Oncology Group--Performance Status; ITB > 50%: intrahepatic tumor burden > 50%; MVI: macrovascular invasion. N.A. not applicable. cancers-15-01523-t004_Table 4 Table 4 Univariate and multivariate Cox regression analysis of overall survival in the cohort of patients with a single site of metastases. Variable Univariate HR (95% CI) p Multivariate HR (95% CI) p Male sex 1.079 (0.723-1.609) 0.710 Viral etiology 0.921 (0.672-1.262) 0.610 Child-Pugh B 5.356 (2.577-11.131) <0.001 6.326 (2.696-14.843) <0.001 ALBI > 1 1.423 (1.045-1.939) 0.025 1.291 (0.913-1.825) 0.148 AFP > 400 ng/mL 1.500 (1.098-2.048) 0.011 1.464 (1.046-2.049) 0.026 ITB > 50% 1.580 (1.140-2.191) 0.006 1.614 (1.130-2.307) 0.009 ECOG-PS > 0 1.587 (1.133-2.222) 0.007 1.311 (0.905-1.898) 0.152 MVI 1.963 (1.434-2.686) <0.001 1.770 (1.251-2.503) 0.001 DAEs 0.780 (0.584-1.042) 0.093 0.755 (0.573-0.994) 0.045 Lymph nodes 1.411 (1.054-1.890) 0.021 1.645 (1.078-2.509) 0.021 Lungs 1.431 (1.018-2.013) 0.039 2.182 (1.331-3.578) 0.002 Bone 0.663 (0.440-0.998) 0.049 1.018 (0.586-1.766) 0.950 Adrenal glands 0.727 (0.434-1.218) 0.226 AFP: alfa-fetoprotein; DAEs: dermatologic adverse events; ECOG-PS: Eastern Cooperative Oncology Group--Performance Status; ITB > 50%: intrahepatic tumor burden > 50%; MVI: macrovascular invasion. N.A. not applicable. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000515 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050732 healthcare-11-00732 Article Importance of Asprosin for Changes of M. Rectus Femoris Area during the Acute Phase of Medical Critical Illness: A Prospective Observational Study Sipahioglu Hilal Conceptualization Methodology Software Formal analysis Investigation Writing - original draft Visualization 1* Ilik Hatice Kubra Zenger Methodology Software 2 Ozer Nurhayat Tugra Methodology Formal analysis Data curation 3 Onuk Sevda Validation Formal analysis Data curation Supervision 1 Koyuncu Sumeyra Validation Data curation 4 Kuzuguden Sibel Data curation 5 Elay Gulseren Formal analysis Investigation 6 Roberts Shelley Academic Editor 1 Department of Intensive Care Unit, Kayseri City Training and Research Hospital, Kayseri 38080, Turkey 2 Department of Internal Medicine, Kayseri Training and Research Hospital, Kayseri 38080, Turkey 3 Department of Clinical Nutrition, Erciyes School of Medicine, Erciyes University, Kayseri 38080, Turkey 4 Department of Nephrology, Kayseri City Training and Research Hospital, Kayseri 38080, Turkey 5 Department of Biochemistry, Kayseri City Training and Research Hospital, Kayseri 38080, Turkey 6 Department of Intensive Care Unit, Gaziantep University, Gaziantep 27470, Turkey * Correspondence: [email protected]; Tel.: +90-035223-157700 (Ext. 11056) 02 3 2023 3 2023 11 5 73231 1 2023 27 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Asprosin, a new adipokine, is secreted by subcutaneous white adipose tissue and causes rapid glucose release. The skeletal muscle mass gradually diminishes with aging. The combination of decreased skeletal muscle mass and critical illness may cause poor clinical outcomes in critically ill older adults. To determine the relationship between the serum asprosin level, fat-free mass, and nutritional status of critically ill older adult patients, critically ill patients over the age of 65 receiving enteral nutrition via feeding tube were included in the study. The patients' cross-sectional area of the rectus femoris (RF) of the lower extremity quadriceps muscle was evaluated by serial measurements. The mean age of the patients was 72 +- 6 years. The median (IQR) serum asprosin level was 31.8 (27.4-38.1) ng/mL on the first study day and 26.1 (23.4-32.3) ng/mL on the fourth study day. Serum asprosin level was high in 96% of the patients on the first day, and it was high in 74% on the fourth day after initiation of enteral feeding. The patients achieved 65.9 +- 34.1% of the daily energy requirement for four study days. A significant moderate correlation between delta serum asprosin level and delta RF was found (Rho = -0.369, p = 0.013). In critically ill older adult patients, a significant negative correlation was determined between serum asprosin level with energy adequacy and lean muscle mass. asprosin adipokine older adult patients muscle mass ICU This research received no external funding. pmc1. Introduction Per the results of the world population estimates revised in 2017, Europe faces exceptional demographic changes. Accordingly, individuals aged 60 and above already constitute 25% of the population, and by 2050, this ratio is expected to reach 35%. The number of those with an age of 80 and above will be tripled by 2050 . In developed countries, the increased average life expectancy has also resulted in increased demand for hospitalization of the elderly population in hospitals and intensive care units (ICU). It has been determined that approximately more than 50% of the patients hospitalized in the intensive care unit are above 65 years old . A systematic review demonstrated a significantly high malnutrition prevalence (38-78%) in ICU patients. This situation is correlated to an increase in morbidity, mortality, and hospital-related costs for patients . The dependency on mechanical ventilation is correlated with malnutrition, length of hospital stay, ICU readmission, infection rates, and risk of hospital death, making this a critical dilemma in ICU patients' care. There are significant challenges in accurately estimating energy requirements and hence the optimal dosing of nutrition. Critical illness results in hypermetabolism and hypercatabolism, putting patients in the ICU at high risk of malnutrition. The metabolic and hormonal changes in critical illness result in muscle wasting and associated ICU-acquired weakness, which can persist for years . Muscle atrophy can occur relatively early in critically ill patients in intensive care units. Muscle atrophy occurs with increased destruction and decreased muscle protein synthesis . Inflammation, immobilization, endocrine stress responses, rapidly developing nutritional deficit, impaired microcirculation, and denervation are conditions that accelerate muscle atrophy . Additionally, muscle loss is common in humans due to aging. Accordingly, muscle loss caused by aging may deepen in the presence of critical illness. Reversing skeletal muscle catabolism can prevent muscle atrophy during critical illness and improve functional outcomes . Proinflammatory mediators are used as an indicator of muscle atrophy during critical illness . Ultrasound is widely used in clinical practice, greatly contributing to diagnosis and management of many conditions. While systematic ultrasound examinations have been conducted mainly by sonographers in an examination room, there is now considerable interest in having physicians perform ultrasounds at the bedside, as part of regular medical examinations. Studies using portable ultrasounds have been spreading not only in the emergency room and intensive care unit (ICU) settings, but also in out-of-hospital situations in, for example, primary care and long-term care facilities (e.g., nursing homes). Additionally, muscle ultrasound is a suitable method for evaluating patients with muscle atrophy. The ultrasonographic evaluation of quadriceps' muscle thickness effectively determines the effect of nutritional interventions on muscle loss in critically ill patients . Adipose tissue functions as an endocrine organ with central energy storage that creates a diversity of bioactive mediators and adipokines (adipose-derived secreted factors), possessing proinflammatory or anti-inflammatory impacts. Adipokines may easily move into the systemic circulation and perform their effects through an inter-cell communication network (autocrine, paracrine, endocrine). Furthermore, they preserve regulating several aspects of the normal metabolic processes in the human body, such as glucose and lipid homeostasis, insulin sensitivity, and inflammatory response . Asprosin is a novel glucogenic adipokine discovered in 2016, mainly secreted from white adipose tissue, and has a critical role in the regulation of hepatic glucose release, insulin secretion, appetite, and inflammatory response . Moreover, it activates the PKCd/SERCA2-mediated endoplasmic reticulum stress/inflammation pathways in skeletal muscle and promotes insulin resistance . Insulin resistance has been revealed to be relatively higher in critically ill patients compared to healthy patients . Evidence suggests an association between asprosin secreted levels and weight loss extent as a result of bariatric surgery, including sleeve gastrectomy or cholecystectomy. Two studies indicated a significant decrease in serum asprosin levels after six months of weight loss surgical intervention . During fasting, the circulating serum asprosin level rises according to the glucose requirement and decreases with the start of feeding. Providing adequate nutritional support to critically ill patients has a critical role in the clinical prognosis of the patient . Considering the above-mentioned information, the relationship between asprosin, muscle mass, and nutritional support in critically ill elderly patients is unclear. This study aimed to reveal the relationship between the serum level of asprosin, a new adipokine, the change in lean muscle mass in critically ill elderly patients, and the nutritional support given to the patients. 2. Material and Methods 2.1. Study Design and Participants This study presents a prospective observational design developed in a tertiary care hospital's clinical-internal intensive care unit from March to September 2022. All patients over the age of 65 who were expected to stay in the intensive care unit for at least 4 days and were administered enteral nutrition support within the first 48 h after their admission to the ICU were included. Patients who could be fed orally, who had previously been treated with parenteral therapy, and who had contraindications for enteral nutrition were excluded from the study. The study was approved by the local ethics committee (No: 586, date: 24 February 2022) and was conducted according to the Helsinki Declaration guidelines. Free and informed consent was obtained from the legal guardians of the study participants. 2.2. Data Collection Demographic data, ICU admission diagnostics, comorbidities, APACHE II (Acute Physiology and Chronic Health Evaluation) scores, SOFA (Sequential Organ Failure Assessment) scores, and the Charlson comorbidity index were recorded at admission. During the follow-up, the need for a mechanical ventilator, renal replacement requirement, and the number of days spent in the intensive care unit and hospital were recorded. The energy target of the patients was calculated as 25-30 kcal/kg/day according to ESPEN Recommendations . The daily energy intake of the patients by tube who actually received enteral nutrition for four days from the start of enteral nutritional support was recorded. The percentage of patients reaching the target energy was calculated. No adjustments were made for age or BMI when calculating energy targets. The risk of malnutrition in patients was determined by the NRS-2002 score. The NRS-2002 form was filled in by the nurses on the day that the patients were admitted to the intensive care unit, taking information from the patients and their relatives, and recorded in the patient file. The nutritional risk of the patients was determined, and a nutrition plan was made. Patients with NRS-2002 >= 3 were considered to be at risk for malnutrition. 2.3. Serum Asprosin Measurement Here, 3 mL blood samples were collected in tubes, and the samples were centrifuged at 3000x g for 10 min at the 24th hour (first day) and fourth day after the start of enteral nutrition support. In our intensive care unit, feeding is interrupted at 11 am for all patients receiving enteral nutrition. Blood samples were drawn in the morning fasting before feeding was re-initiated. Then, 1 mL of serum supernatant was removed and collected in an Eppendorf tube. Serum samples were kept frozen at -80 degC. Serum asprosin protein concentrations were analyzed using the ELISA method (Cat. No. E4095HU). Delta (D) asprosin was calculated as the difference between the first and fourth day asprosin levels of the patients. The normal asprosin level was considered as <23.6 ng/mL (according to the reference range (kit used) determined by the Bioassay Technology Laboratory). 2.4. Ultrasonographic Assessment Ultrasound measurements were performed at 24 h (day 1) and on day 4 after the start of enteral nutritional support. Philips ClearVue 550 system with a linear ultrasound probe (4-12 Mhz) was used for calculation while these measurements were in the supine position on the surface in B mode. The area of the rectus femoris (RF) muscle of the lower extremity quadriceps muscle was measured. The sensor was perpendicular to the thigh axis, and the point is located at 2/3 of the distance from the anterior superior iliac spine to the upper border of the patella. All ultrasonography (USG) measurements were performed by an intensive care specialist with five years of USG experience. Delta (D) RF was calculated as the difference between the RF area of the patients on the first and fourth days. 2.5. Statistics Statistical analysis was performed using the IBM SPSS statistics program version 22 (IBM, New York, NY, USA). The normality distributions of continuous variables were examined using the Shapiro-Wilk test. According to the normal distribution, continuous variables were presented as mean +- SD or median (interquartile range). Categorical variables were shown as numbers (%, percentage). The correlation between the data was investigated using Spearman's correlation test. The correlation coefficient was accepted as 0-0.29 (weak), 0.30-0.69 (moderate), and 0.70-1.0 (strong). A value of p < 0.05 was considered statistically significant for all analyses. The study sample size was calculated as 42 patients, with a medium effect size according to the baseline asprosin level (d = 0.5), 80% strength, and 5% error probability using G-Power 3.1 software. 3. Results Two hundred and fifty-one patients hospitalized in the intensive care unit were evaluated. Of these patients hospitalized in the intensive care unit, 94 were under the age of 65, and 94 did not receive enteral nutrition (26 who received oral nutrition, 68 who received parenteral nutrition) were excluded. First, 67 patients were included in the study. However, 12 patients died during the study period, and 7 patients were excluded since their serum blood was hemolyzed. Two patients were excluded from the study because they switched from enteral to oral feeding. As a result, a total of 46 patients were included in the study . The mean age of the patients was 72 +- 6 years, and the median value of males (IQR) was 25 (54.3). The median (IQR) BMI of the patients was 22.0 (20.9-29.0), the mean APACHE II was 19.8 +- 6.98, and the median (IQR) Charlson comorbidity index was 6 (4-8). Metabolic disorders (n: 17, 37.0%) and sepsis/septic shock (26.1%) were the most common reasons for hospitalization in the intensive care unit. Diabetes mellitus was present in 16 (34.8%) of our patients, and at the same time, all the patients had received insulin therapy. The most common comorbidity in our patients was hypertension, in 29 patients (63.0%). The malnutrition risk was found in 32 patients (70.0%). The median percentage of reaching the daily energy requirement was 65.9 +- 34.1 during the 4-day follow-up. The daily energy requirements and the amount they can actually take are presented in Table 1. The mean daily protein intake was 0.4 +- 0.27 g/kg/day on the first day and 0.8 +- 0.47 g/kg/day on the fourth day. Mechanical ventilation (21 (45.7%)) and renal replacement requirement (21 (45.7%)) of the patients were quite high. Demographic data and clinical characteristics of the patients are presented in Table 1. Median (IQR) asprosin levels were 31.8 (27.4-38.1) ng/mL on the first day and 26.1 (23.4-32.3) ng/mL on the fourth day. The serum asprosin concentration of study participants significantly decreased (p < 0.001), and the delta asprosin value was -5.77 (-9.22 to 0.28) (Table 2). The asprosin level was high in 95.7% of the patients on the first day. This rate decreased on the fourth day of the study, and 73.9% of patients had high asprosin levels . Median RF was 1.68 (1.35-2.07) cm2 on the first day and 1.82 (1.38-2.01) cm2 on the fourth day (p = 0.196). The median delta RF was 0.15 (-0.43 to 0.46). The laboratory values of the patients on the first and fourth days are presented in detail in Table 3. The glucose level of the patients was 143 (110-194) mg/dL on the first day, 125 (103-170) mg/dL higher than on the fourth day (p < 0.001). The albumin value was statistically significantly lower on the fourth day than on the first day of the study (2.7 (2.4-3.1) g/L vs. 2.5 (2.2-2.9) g/L, p = 0.001). A significant negative correlation was observed between the delta asprosin level and the delta RF value of the patients (Rho = -0.369, p= 0.013) . There was a moderate correlation between the serum asprosin level of the patients and the received % of the daily energy target (Rho = 0.345, p = 0.027) . The correlations between the serum asprosin value and the severity of illness and biochemical parameters of patients on both study time points are summarized in Table 4. A negative correlation was determined between albumin and prealbumin levels and the first day and delta asprosin levels (p < 0.05). 4. Discussion To the best of our knowledge, this prospective study is the first to investigate the serum asprosin value and its relationship between muscle mass and nutritional adequacy in critically ill older adult patients. Most of the participants had increased serum asprosin levels upon study admission. On the fourth day after enteral nutrition support initiation, the serum asprosin concentration of the study sample significantly decreased compared to the first day of the study. There was a significantly negative correlation between the delta asprosin value and the delta RF of patients. Besides, the delta asprosin value was significantly correlated with the received percentage of energy intake from daily energy requirements. Almost all patients had elevated asprosin levels on the first day of the study. A significant decrease in asprosin levels was observed in our patients after four days of enteral nutrition. We think that the reason for the high first-day asprosin level in patients is malnutrition in adult patients and/or high insulin resistance developing in critical illness. The mean age of our patients was high, and 70.0% were at risk of malnutrition in our study. The main concern in the elderly, especially the very elderly and those with multiple comorbidities, is reduced food intake and weight loss. Malnutrition in elderly patients delays recovery in both acute and chronic diseases and increases morbidity and mortality . In response to starvation with a low-intake diet, asprosin is released from white adipose tissue and transported to the liver to mediate glucose release into the bloodstream. Additionally, asprosin is abundantly expressed in human skeletal muscle-derived mesoangioblasts, suggesting that the musculoskeletal system may play a role in regulating asprosin expression . In a cross-sectional study by Hu et al., 46 patients with anorexia nervosa were included. It was found that these patients had a statistically significant increased plasma asprosin level compared to healthy controls . Providing adequate nutritional support in critically elderly patients may be a key method in optimizing increased asprosin levels. It was shown that insulin resistance in intensive care patients is considerably higher than in healthy patients . In a cross-sectional study conducted by Goodarzi et al., it was reported that the serum asprosin level was statistically significantly positively correlated with Hba1c, HOMA-IR, and insulin levels in patients with a type 2 diabetes mellitus diagnosis and nephropathy . Similarly, the first-day glucose values of our patients were higher than the glucose values after four days of feeding. Factors including systemic inflammation, decreased peripheral blood flow, inactivity, insulin resistance, and decreased food intake might cause significant reductions in muscle mass in severely ill patients hospitalized in intensive care units. Malnutrition, depending on the negative nutritional balance between what is necessary for the patients and what they receive, is reliant on decreased muscle mass and functionality, which is considered common among ICU patients. Thus, the correct nutritional diagnosis of these patients is critical to support adequate dietary maintenance. Nevertheless, nutritional evaluation is challenging in intensive care units, particularly when monitoring nutritional status. Ultrasonography is a portable, non-invasive bedside method that may specify and measure skeletal muscle and has been used as a supportive examination tool to provide nutritional diagnostics. The ability to detect short-term changes by allowing serial measurements is one of the most advantageous aspects of ultrasonography compared to other anthropometric measurement instruments. The ultrasound examination of rectus femoris muscle thickness has been reported to be used in the monitoring of nutrition . In the study of Duerrschmid et al., which experimented with mice, wild-type mice and mice with truncated mutations in the FBN1 gene were provided a high-calorie, high-fat diet. Mice with truncated mutations in the FBN1 gene had less fat and muscle content than wild-type mice. This study demonstrates that asprosin, encoded by FBN1, has an impact on nutrition and muscle mass . One of our hypotheses in our study was that insulin resistance, being very common in intensive care units, can be improved as adequate nutrition is provided, and the increase in the asprosin level may be effective in this condition. Since we did not measure insulin resistance, we cannot clarify this. This muscle wasting also adversely affects the clinical outcomes of the patients. Quadriceps' muscle thickness is used to evaluate nutritional interventions in critically ill patients in the intensive care unit . The present study demonstrated a negative correlation between the change in quadriceps' muscle thickness and asprosin after four days of nutrition. In the current literature, it has been reported that the musculoskeletal system effectively regulates the level of asprosin . Du et al. conducted a cross-sectional study of 120 cancer patients. A statistically significant positive correlation was found between the serum asprosin level and body fat mass in these patients . Moreover, increased levels of asprosin may accelerate the reduction in muscle mass in critically ill elderly patients. In intensive care units, giving sufficient nutritional substances and using them in the anabolic process positively contributes to the course of the disease. We determined a negative correlation between the serum asprosin level of our patients and the percentage of patients reaching the target energy. The present study concluded a negative correlation between prealbumin and albumin with the asprosin value on the first day. Prealbumin and albumin values are frequently used as biomarkers of adequate nutrition. However, serum albumin and prealbumin levels are affected by many factors . Biochemical measures are beneficial to obtain in the ICU setting. Nonetheless, improvements in such parameters are not consistently related to improvements in outcomes when controlled for illness severity. There may be several reasons for these limitations . The significant fluid shifts in critical illness can impact the serum concentrations of the most commonly used biochemical indicators. Visceral or "hepatic" proteins, including albumin and prealbumin, are affected by the acute phase response, independent of nutrition status or nutrition input . For example, the prealbumin level usually falls at the beginning of the ICU admission even when nutrition support has been entirely implemented, and the level may improve as the acute phase response decreases, even if the patient has not received adequate nutrition or has continued to lose weight. However, several studies have suggested that if the acute phase response is reasonably stable, the prealbumin levels then correlate with nutrition intake, but perhaps not the outcome. Prealbumin levels cannot be measured at all hospital laboratories . Nonetheless, the serum albumin level is routinely measured in most hospitals and is a robust prognostic indicator even in critical illness, but it has a long half-life and does not correlate to significant alterations in nutrition input, making it less useful as a parameter for sequential monitoring of nutrition progress . Malnutrition is a very common and vital issue in intensive care. There are no good markers to assess rapidly developing muscle wasting in patients with fractures. The prealbumin and albumin we used in our routine are affected by many parameters. Our study suggests that asprosin, a new adipokine, can be used to monitor adequate nutrition and muscle loss. However, a larger number of patients and further studies are needed. 5. Limitations The limitations of our study are that it is single-centered, and the number of patients is small. Our study findings included only elderly critically ill patients. This limits generalizability in critically ill patients. If we had also evaluated insulin resistance in our patients, we could better explain the pathophysiology. Another limitation of our study was the inability to measure inflammatory and anti-inflammatory cytokines in patients due to cost. If we could measure the cytokine values, we could see the effect of inflammation on nutrition and asprosin more clearly. Evaluation with ultrasonography for a longer time would have yielded more precise results to better evaluate the response of muscle mass in response to feeding in patients. The mitochondrial evaluation was not performed for the asprosin level in our study. More reliable results could have been obtained with this evaluation. 6. Conclusions Nearly all the critically ill elderly patients had elevated serum asprosin levels. Serum asprosin levels decreased in those patients who received enteral nutritional support and ICU treatment. In this study, there was a negative correlation between the serum asprosin level and delta lean muscle mass. Additionally, the serum asprosin level correlated with nutritional adequacy. For future investigations, whether the serum asprosin level can be used as a biomarker in evaluating the adequacy of nutritional interventions in critically ill patients should be evaluated with larger sample sizes. The relationship between the asprosin level and ICU-acquired weakness should be clarified. Author Contributions Conceptualization, H.S.; methodology, H.S., H.K.Z.I. and N.T.O.; software, H.S. and H.K.Z.I.; validation, S.K. (Sumeyra Koyuncu) and S.O.; formal analysis, H.S., N.T.O. and G.E.; investigation, H.S. and G.E.; resources, H.S.; data curation, S.O., N.T.O. and S.K. (Sibel Kuzuguden); writing--original draft preparation, H.S.; writing--review and editing, H.S.; visualization, S.O. and H.S. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study received ethical approval from Kayseri City Education and Research Hospital Local Ethical Board. The study was conducted in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Written informed consent was obtained from all participants (Ethics Committee Decision No. 586, date: 24 February 2022). Informed Consent Statement Written informed consent was obtained from the patients before the study. Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart of the study. Figure 2 The distribution of patients with high/low-normal asprosin levels on the first and fourth days after EN initiation. Figure 3 The Spearman correlation between the delta RF and the delta asprosin value. Figure 4 The Spearman correlation between the serum asprosin level and the received % of the daily energy target. healthcare-11-00732-t001_Table 1 Table 1 Demographic and clinical characteristics of the study participants. Variables Total (n = 46) Age (years) +- SD 72 +- 6 Gender, n (%) Male 25 (54.3) Female 21 (41.7) BMI, median (IQR) 22.0 (20.9-29.0) Reason for ICU admission, n (%) Respiratory failure 8 (17.4) Sepsis/septic shock 12 (26.1) Cerebrovascular disease 8 (17.4) Metabolic reasons 17 (37.0) Post-op 1 (2.2) Comorbidity disease, n (%) Diabetes mellitus 16 (34.8) Hypertension 29 (63.0) Chronic obstructive pulmonary disease 12 (26.1) Cardiac failure 10 (21.7) Chronic renal failure 8 (17.4) Dementia 10 (21.7) Other (...) 17 (37.0) APACHE II score, +- SD 19.8 +- 6.98 SOFA score, +- SD Day 1 6.8 +- 3.43 Day 4 7.3 +- 4.17 Charlson comorbidity index, median (IQR) 6.0 (4.0-8.0) Baseline Glasgow score, median (IQR) 10.0 (3.0-13.0) Malnutrition at risk, n (%) 32 (70.0) Daily energy requirement (kcal/day), +-SD 1540 +- 193.0 Daily energy intake (kcal), +-SD Day 1 530 +- 371.3 Day 2 931 +- 574.5 Day 3 1023 +- 560.4 Day 4 1062 +- 622.9 The received % of daily energy target, +-SD Day 1 34.9 +- 24.8 Day 2 61.4 +- 38.7 Day 3 67.7 +- 37.4 Day 4 74.0 +- 42.0 Daily protein intake (g/kg/day), +-SD Day 1 0.4 +- 0.27 Day 2 0.7 +- 0.44 Day 3 0.8 +- 0.42 Day 4 0.8 +- 0.47 The received % of daily protein target, +-SD Day 1 35.8 +- 23.54 Day 2 65.3 +- 40.84 Day 3 73.1 +- 41.22 Day 4 79.3 +- 46.67 Need for MV support, n (%) 21 (45.7) Need for RRT, n (%) 21 (45.7) Length of ICU stay (day), median (IQR) 11.5 (9.8-18.5) Length of hospital stay (day), median (IQR) 19.0 (13.0-31.8) Mortality, n (%) 29 (63.0) APACHE II: Acute Physiology and Chronic Health Evaluation, BMI: body mass index, SOFA: Sequential Organ Failure Assessment, IQR: interquartile range, MV: mechanical ventilation, RRT: renal replacement therapy. healthcare-11-00732-t002_Table 2 Table 2 Serum asprosin concentrations and RF values of participants on the first and fourth study days. Day 1 Day 4 Delta (D) p Asprosin value, ng/mL 31.8 (27.4 to 38.1) 26.1 (23.4 to 32.3) -5.77 (-9.21 to 0.28) <0.001 RF, cm2 1.68 (1.35 to 2.07) 1.82 (1.38 to 2.13) 0.15 (-0.43 to 0.46) 0.196 healthcare-11-00732-t003_Table 3 Table 3 The laboratory values of the patients on the first and fourth study days. Day 1 Day 4 p Glucose (mg/dL) 143 (110-194) 125 (103-170) <0.001 AST (IU/L) 24 (15-35) 22 (13-38) 0.651 ALT (IU/L) 15 (8-24) 16 (9-25) 0.433 LDH (U/L) 294 (237-395) 267 (200-389) 0.040 Albumin (g/dL) 2.7 (2.4-3.1) 2.5 (2.2-2.9) 0.001 Prealbumin (g/L) 0.1 +- 0.04 0.1 +- 0.05 0.051 CRP (mg/L) 72.3 (36.7-152.5) 77.6 (30.9-139.5) 0.666 Procalcitonin (mg/L) 0.49 (0.21-1.96) 0.60 (0.14-3.30) 0.984 AST: aspartate aminotransferase, ALT: alanine aminotransferase, LDH: lactate dehydrogenase, CRP: C-reactive protein. healthcare-11-00732-t004_Table 4 Table 4 The Spearman correlation analysis between serum asprosin levels and severity of illness scores and some biochemical parameters. Asprosin Value, ng/mL Day 1 Day 4 Delta APACHE II -0.160 - -0.050 mNUTRIC score -0.063 - 0.102 Charlson comorbidity index 0.151 - 0.012 SOFA Day 1 0.067 - 0.089 Day 4 - 0.142 0.133 Glucose Day 1 -0.052 -0.060 Day 4 - -0.067 AST Day 1 -0.088 -0.078 Day 4 -0.075 ALT Day 1 -0.082 -0.056 Day 4 -0.111 LDH Day 1 -0.007 -0.096 Day 4 -0.026 Albumin Day 1 -0.315 * -0.525 * Day 4 -0.002 Prealbumin Day 1 -0.334 * -0.322 * Day 4 -0.267 CRP Day 1 -0.106 0.077 Day 4 0.154 PCT Day 1 -0.001 0.204 Day 4 -0.120 *: p < 0.05. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. 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PMC10000516 | CDKN2A is a tumor suppressor gene encoding the p16 protein, a key regulator of the cell cycle. CDKN2A homozygous deletion is a central prognostic factor for numerous tumors and can be detected by several techniques. This study aims to evaluate the extent to which immunohistochemical levels of p16 expression may provide information about CDKN2A deletion. A retrospective study was conducted in 173 gliomas of all types, using p16 IHC and CDKN2A fluorescent in situ hybridization. Survival analyses were performed to assess the prognostic impact of p16 expression and CDKN2A deletion on patient outcomes. Three patterns of p16 expression were observed: absence of expression, focal expression, and overexpression. Absence of p16 expression was correlated with worse outcomes. p16 overexpression was associated with better prognoses in MAPK-induced tumors, but with worse survival in IDH-wt glioblastomas. CDKN2A homozygous deletion predicted worse outcomes in the overall patient population, particularly in IDH-mutant 1p/19q oligodendrogliomas (grade 3). Finally, we observed a significant correlation between p16 immunohistochemical loss of expression and CDKN2A homozygosity. IHC has strong sensitivity and high negative predictive value, suggesting that p16 IHC might be a pertinent test to detect cases most likely harboring CDKN2A homozygous deletion. p16 immunohistochemistry CDKN2A deletion FISH gliomas prognosis ARAME association, Societe Francaise des Cancers de l'Enfant and Enfants, Cancers et Sante associationThis research was funded by ARAME association, Societe Francaise des Cancers de l'Enfant and Enfants, Cancers et Sante association. We are very thankful for this financial support and their help with this study. pmc1. Introduction The Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) gene is a tumor suppressor gene located at chromosome 9, locus p21.3 that encodes the p14ARF and p16INK4a proteins . Both proteins are generated by alternative mRNA splicing of the CDKN2A gene. The p16 protein is a key regulator of the cell cycle in the p16INK4a/cyclin D1/CDK4/Rb/E2F1 pathway and interacts closely with p53/p21/Rb signaling . Both pathways are involved in various steps of the G1-S phase transition . p16INK4a acts by binding the Cyclin-Dependent Kinase 4/6, which inhibits its kinase activity and therefore prevents Rb phosphorylation. Rb stays bound to the transcription factor E2F1, keeping this complex within the cytoplasm and preventing E2F1 transcription of target genes involved in the G1-S phase transition . CDKN2A is the second most impaired tumor suppressor gene in cancers, including gliomas , and its inactivation promotes the G1-S phase transition. The most frequently encountered molecular inactivation mechanism is CDKN2A homozygous deletion, but molecular inactivation can also be achieved by promoter hypermethylation, missense mutations, or post-transcriptional regulation mechanisms . The prognostic impact of CDKN2A homozygous deletion is crucial, especially in IDH-mutant astrocytomas . Thus, the last WHO classification of central nervous system tumors integrated this deletion into the grading of this type of glioma. Indeed, the presence of a CDKN2A homozygous deletion would now classify an IDH-mutant astrocytoma as WHO grade 4, even in the absence of microvascular proliferation or necrosis . CDKN2A homozygous deletion can be detected by various techniques, such as Fluorescence In Situ Hybridization (FISH), Comparative Genomic Hybridization array (CGH-array), or potentially Next Generation Sequencing (NGS). All these methods are complex, time-consuming, and may result in delayed diagnosis and subsequent treatment. IHC is currently not recommended as a reliable surrogate test. However, there is a p16-protein-targeting antibody, which is used in daily practice for the diagnosis of HPV-induced neoplasia. Therefore, it might be of interest to evaluate IHC levels of p16 expression to provide information about CDKN2A alterations in other cancers. Few studies focus on the association between p16 IHC and CDKN2A deletion in glioma samples , but, with respect to IDH-mutant astrocytomas, some have reported a significant association between p16-negative IHC and a high negative predictive value. Such results promote this technique as a pertinent test to evaluate p16 expression and glioma prognosis . Nevertheless, other publications conclude a poor correlation between CDKN2A results generated by FISH and IHC . These conflicting results may be related in part to small sample size or to cohorts comprising heterogenous groups of gliomas that did not reflect the current histomolecular classification diversity . Here, we describe the correlation between p16 IHC expression and CDKN2A heterozygous and homozygous deletion assessed by FISH in a cohort of high-grade diffuse adult-type gliomas, as well as in circumscribed gliomas. Survival analyses were performed to evaluate and compare the prognostic impacts of p16 IHC expression and the paired CDKN2A homozygous deletion. 2. Material and Methods 2.1. Patient Cohort A retrospective study was conducted including one hundred and seventy-three gliomas of all grades diagnosed over a period of 13 years (1999-2012), resected in the neurosurgical department of Strasbourg University Hospital. Most of the cases were from 2005 to 2012, especially adult-type diffuse gliomas. The period of inclusion was only extended for rarer tumors, especially BRAF-altered tumors. Most cases from biopsies with limited FFPE residual samples were excluded due to the impossibility of performing tissue microarray (TMA) and additional molecular tests. Cases without informed consent and clinical follow-up were also excluded. Therefore, our cohort represents about 35% of all the patients operated on in the neurosurgical department of Strasbourg University Hospital. TMAs comprising 3 representative 1 mm diameter tumoral cores of all patients' specimens were constructed. All specimens were obtained after informed consent from parents and patients and were anonymized for their analyses. This study was conducted in accordance with the ethical committee approval (declaration number: DC-2017-3090). All hematoxylin and eosin (HE)-stained slides of the entire glioma population were reviewed to reclassify all gliomas according to the 2021 WHO classification of central nervous system tumors--which also recommends IHC, FISH and/or NGS assays for an accurate histomolecular diagnosis. Supplementary IHC for the whole cohort included a search for ATRX loss of expression (ATRX antibody, clone BSB-108), p53 expression (p53 antibody, clone D07), and IDH1 R132H expression (IDH1 R132H antibody, clone IHC 132). In 50 cases for which morphological and immunohistochemical profiles were suggestive of oligodendroglioma diagnosis, the 1p/19q codeletion was detected with a FISH technique (ZytoLight SPEC 1p36/1q25 Dual Color Probe et ZytoLight SPEC 19q13/19p13 Dual Color Probe). NGS was performed on diffuse high-grade pediatric gliomas and on circumscribed gliomas (68 cases), using Illumina MiSeq sequencing technology. Illumina NGS workflows include 4 basic steps: library preparation using the Multiplicom Tumor Hotspot MASTR Plus kit (MR-0200.024), cluster generation, sequencing, and data analysis. The bioinformatics was performed using the STARK analysis environment (version 0.9b). Each technique in each case was interpreted based on the percentage of tumor cells. 2.2. Clinical Characteristics Clinical data focused on patient gender, age at diagnosis, type of specimen (biopsy or surgical resection), presence of tumor recurrence, date of progression, and/or date of death. The overall survival (OS) time was calculated from the date of the initial surgery to the date of death. 2.3. Evaluation of p16 and Rb1 Immunohistochemistry IHC was performed to evaluate p16 expression using an antibody against the p16 protein (clone E6H4). The average percentage of tumor cells exhibiting both nuclear and cytoplasmic expression was evaluated on the 3 TMA cores. Loss of Rb1 expression was assessed using an Rb1 antibody (G3-245 clone). Loss of Rb1 expression was only considered when positive control was present on the core, consisting of a positive staining of endothelial cells and micro-environmental lymphocytes. 2.4. FISH Analysis CDKN2A deletion status was assessed by FISH, using a dual-color FISH assay on paraffin-embedded sections with the ZytoLight SPEC CDKN2A/CEN 9 Dual Color Probe FISH probes. One hundred nuclei were evaluated to assess normal signals and the number of heterozygous or homozygous deleted tumor cells. The percentage of heterozygous or homozygous cells was related to the percentage of tumor cells evaluated on HE slides. As recommended in previous studies, a 15% cutoff of nuclei with homozygous or heterozygous deletion was set up . 2.5. Statistical Analyses The analyses were performed using statistical websites: and www.pvalue.io (accessed on 7 June 2022). Qualitative variables were described as percentages and quantitative variables were described as their medians and ranges. Correlations between two groups were analyzed using Fisher's exact test. Quantitative data were compared using Student's t-test. All survival correlations were estimated by the Kaplan-Meier method. The log-rank test was used for univariate analyses and the Cox regression model for multivariate analyses. Variables showing prognostic significance with a p-value under 0.05 in univariate analysis (tumor recurrence and age over 36.5 years) were included in the multivariate analysis model. p-values under 0.05 were considered statistically significant. The ROC analysis curve was determined after calculating the True Positive Rate (TPR) and the False Positive Rate (FPR) values for several percentage thresholds of p16-positive tumor cells in the IHC assay (0%, 1%, 2%, 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%). The TPR and FPR values were then reported on a curve using Microsoft Excel software. 3. Results 3.1. Characteristics of the Study Population The median age of the study population was 36.5 years (range: 1 to 79 years), and 95 patients (55%) were men. One hundred and sixty-three patients (94%) had a surgical resection of the tumor, and 10 patients (6%) had a simple biopsy. Thirty-three patients (19%) were reoperated on for tumor recurrence. Table 1 summarizes the clinical information. For survival data, the median follow-up time was 62 months (range 0 to 273 months). During this follow-up period, 114 patients (66%) died. The diagnoses according to the last 2021 WHO classification of central nervous system tumors were as follows:- adult-type diffuse gliomas, including 63 IDH-wt glioblastomas (GBM) (considered WHO grade 4 tumors), 15 IDH-mutant astrocytomas (four grade 2, five grade 3, and six grade 4 cases), and 27 IDH-mutant 1p/19q codeleted oligodendrogliomas (OG) (10 grade 2 and 17 grade 3 cases) - 18 high-grade pediatric-type diffuse gliomas, including nine H3K27-altered gliomas, one hemispheric H3.3 G34-mutant glioma, and eight wt hemispheric gliomas - 47 circumscribed gliomas, including 36 pilocytic astrocytomas (PA) (considered WHO grade 1 tumors), 10 gangliogliomas (GGLs) (grade 1), and one pleomorphic xanthoastrocytoma (PXA) (with anaplastic features of WHO grade 3) - three low-grade pediatric gliomas including two subependymal giant-cell astrocytomas (WHO grade 1) and one angiocentric glioma (also grade 1) 3.2. Patterns of Immunohistochemical p16 Expression and Prognostic Implications Three patterns of p16 expression were identified: (1) a total loss of expression , (2) a focal positive expression in a variable amount of tumor cells , and (3) an intense and diffuse positivity throughout samples . These patterns were preferentially observed in different glioma types. Indeed, an absence of p16 expression was encountered in 32% of the whole cohort (56/173) and was almost restricted to high-grade glioma subtypes. Loss of p16 expression was observed in 57% (36/63) of IDH-wt GBM, 33% (2/6) of IDH-mutant astrocytomas (grade 4), 40% (2/5) of IDH-mutant astrocytomas (grade 3), 29% (5/17) of IDH-mutant 1p/19q codeleted OG (grade 3), 67% (6/9) of H3K27-altered diffuse gliomas, 38% (3/8) of wt pediatric diffuse gliomas, and in the only case of PXA with anaplasia. Among the low-grade gliomas, only one PA showed an absence of p16 expression. A focal expression of p16 was encountered in 51% of the whole cohort (89/173). This pattern was mostly observed in low-grade MAPK-altered gliomas, especially in 83% (30/36) of PAs and 50% (5/10) of GGLs. This was also the most represented pattern of expression in low-grade adult-type gliomas, seen in 100% (4/4) of IDH-mutant astrocytomas (grade 2) and 100% (10/10) of IDH-mutant 1p/19q codeleted OG (grade 2). A subset of high-grade gliomas also exhibited this pattern: 27% (17/63) of IDH-wt GBM, 50% (3/6) of IDH-mutant astrocytomas (grade 4), 40% (2/5) of IDH-mutant astrocytomas (grade 3), 59% (10/17) of IDH-mutant 1p/19q codeleted OG (grade 3), 11% (1/9) of H3K27-altered midline gliomas, 38% (3/8) of wt high-grade pediatric gliomas, and in the only case of hemispheric G34-mutant high-grade pediatric glioma. An intense and diffuse expression of p16 was observed in two distinct groups of gliomas: MAPK-induced low-grade gliomas and diffuse high-grade gliomas. Indeed, this pattern was observed in 14% (5/36) of PAs and 50% (5/10) of GGLs. Among the high-grade gliomas, it was noticed in 16% (10/63) of IDH-wt GBM, 17% (1/6) of IDH-mutant astrocytomas (grade 4), 20% (1/5) of IDH-mutant astrocytomas (grade 3), 12% (2/17) of IDH-mutant 1p/19q OG (grade 3), 22% (2/9) of midline H3K27-altered gliomas, and 25% (2/8) of wt diffuse pediatric gliomas. Among high-grade gliomas with intense and diffuse p16 expression, all except one showed a loss of Rb1 expression. Contrarily, no case harbored a loss of Rb1 in low-grade MAPK-induced gliomas. This pattern was not encountered in other glioma subtypes. Results are summarized in Table 2. In the whole cohort, absence of p16 expression was significantly associated with a shorter OS in univariate analysis (Kaplan-Meier and log-rang test, p < 0.001). Worse outcomes were especially noticed in IDH-wt GBM (p < 0.001) and IDH-mutant 1p/19q oligodendrogliomas (grade 3) (p = 0.002) . In IDH-wt GBM, intense and diffuse p16 expression was associated with worse outcomes when compared to focal p16 expression . Nevertheless, intense and diffuse expression of p16 was associated with different prognostic impacts depending on the molecular alteration driving the tumors. In high-grade gliomas, especially in IDH-wt GBM, this overexpression was associated with dismal prognoses (p < 0.001) . However, in MAPK-induced gliomas, p16 overexpression was associated with better prognoses (p = 0.04), . 3.3. CDKN2A Status and Prognostic Implications Thirty-eight CDKN2A homozygous deletions and 15 CDKN2A heterozygous deletions were identified. Homozygous deletions were essentially restricted to high-grade gliomas including 29% (5/17) of IDH-mutant 1p/19q codeleted OG (grade 3), 46% (29/63) of IDH-wt GBM, and 33% (3/9) of midline H3K27-altered gliomas. The latter was the only diffuse high-grade pediatric-type glioma to harbor homozygous deletion. No CDKN2A homozygous deletion was identified in grade 2 gliomas. Surprisingly, one PA presented a homozygous deletion. Heterozygous deletions were observed in high-grade gliomas including 35% (6/17) of IDH-mutant 1p/19q oligodendrogliomas (grade 3), 20% (1/5) of IDH-mutant astrocytomas (grade 3), 5% (3/63) of IDH-wt GBM, and 55% (5/9) of high-grade diffuse pediatric gliomas, especially H3 and IDH-wt. Statistically, CDKN2A homozygous deletion was associated with adverse prognoses in the whole population in univariate analysis (Kaplan-Meier and log-rang test, p < 0.001). In IDH-wt GBM , as well as in IDH-mutant 1p/19q OG (grade 3) , the poor prognostic outcome was also significant (p < 0.001). In multivariate analyses, the correlation between CDKN2A homozygous deletion and worse outcomes was significant and persisted even after adjusting the population for tumor recurrence and age over 36.5 years, which are recognized as poor prognostic factors (p < 0.001, hazards ratio [HR]: 2.536, 95% confidence interval [CI]: 1.195-5.271 for grade 3 OG and p = 0.02, HR: 1.723, 95% CI: 1.012-2.936 for IDH-wt GBM). The prognostic impact in pediatric-type high-grade gliomas was not statistically significant. The only pilocytic astrocytoma with CDKN2A homozygous deletion showed a pejorative evolution with an OS of 60 months. No prognostic impact of heterozygous deletion was observed, either in the whole cohort or in precise subtypes. 3.4. Comparison between p16 Immunohistochemistry and CDKN2A FISH Results The association between CDKN2A homozygous deletion and the absence of p16 expression was clearly significant (p < 0.001). Sixty-eight percent (38/56) of gliomas with an absence of p16 expression demonstrated a CDKN2A homozygous deletion on FISH assays. On the other hand, none of the gliomas with intense and diffuse p16 expression (0/28) demonstrated a CDKN2A homozygous deletion. In the pattern defined as focal expression, there was no CDKN2A homozygous deletion (0/89) if more than 5% of tumor cells were expressing p16. On the ROC analysis plot, a threshold of 5% of p16-positive cells on the IHC assay showed the best performance values. Indeed, observation of less than 5% p16-positive tumor cells predicted a homozygous deletion of CDKN2A with a sensibility of 100%, a specificity of 71%, a positive predictive value of 50%, and a negative predictive value of 100% . Survival curves of p16 pattern expression and CDKN2A FISH showed similar prognostic statistics . Furthermore, survival curves of cases with absence of p16 expression with or without CDKN2A deletion were similar (F). 4. Discussion This study demonstrates similar prognostic values for p16 IHC absence of expression and CDKN2A homozygous deletion in a molecularly defined cohort comprising almost all glioma types. To obtain a significant and statistically valuable comparison, we first studied the patterns of p16 expression in the entire cohort. Three types of patterns were identified: (1) absence of expression, (2) focal expression in a variable amount of tumor cells, and (3) intense and diffuse expression across all tumor cells, which might also be considered overexpression. Interestingly, these patterns were already described in the study by Park et al. in adult-type diffuse gliomas , highlighting the reproducibility of these patterns and their potential extension to all glioma subtypes. As for our study, each pattern was preferentially observed in specific glioma subtypes and we were able to confirm that the absence of p16 expression was significantly correlated with worse outcomes in all glioma samples, including IDH-mutant gliomas. We observed that the absence of p16 expression was significantly associated with worse outcomes in IDH-mutant 1p/19q OG (grade 3) and in IDH-wt GBM. As our cohort comprised circumscribed and pediatric-type gliomas, we were able to demonstrate that p16 was focally expressed in pediatric-type, low-grade gliomas, and that overexpression of p16 was present in both IDH-wt glioblastomas and MAPK-induced, low-grade gliomas. We were able to demonstrate that the prognostic significance of p16 overexpression depended on the glioma type and, more exactly, on the molecular alteration responsible for this overexpression. In low-grade gliomas, p16 overexpression is probably related to an oncogene-induced senescence (OIS) phenomenon, which is an antiproliferative response resulting from the activation of the MAPK pathway in the presence of a functional p16 protein. These proteic features partly explain the relatively indolent course of MAPK-induced tumors, especially in low-grade and pediatric settings. In fact, the massive activation of the MAPK pathway leads to an initial hyperproliferative phase usually associated with altered DNA replication, which is followed by a DNA damage response via the p53 tumor suppressor signaling pathway. Finally, this molecular cascade triggers cellular senescence, the maintenance of which depends on the p16 pathway . In contrast, in adult high-grade gliomas, especially in IDH-wt glioblastomas, p16 overexpression was associated with worse prognoses. In this high-grade setting, p16 overexpression results from positive feedback triggered by a loss of Rb1 expression that typically limits the G1-S transition. The loss of Rb1 expression, present in all our cases except one, is probably linked to Rb1 deletion, which has already been described in this high-grade subtype and is related to poor prognosis in some glioma subtypes . p16 overexpression is, then, the witness of this molecular Rb1 alteration . Regarding the CDKN2A FISH results, homozygous deletions were mostly found in IDH-wt GBM, IDH-mutant 1p/19q OG (grade 3), and H3K27-altered gliomas. No homozygous deletions were identified in IDH-mutant high-grade astrocytomas. The prognostic impact of CDKN2A homozygous deletion in diffuse IDH-mutant astrocytomas is still under debate in the literature for grade 4 subsets, but not for grades 2 and 3 . Due to an insufficient number of IDH-mutant astrocytomas in our cohort, we could not reliably assess the prognostic impact of CDKN2A homozygous deletion in this grade 4 histomolecular entity. For another subtype, the IDH-mutant 1p/19q codeleted OG (grade 3), the presence of CDKN2A homozygous deletion led to very poor prognoses, close to those described in IDH-wt GBM. Up to now, this correlation was only underlined in the study by Appay et al. . This result must be confirmed in greater cohorts; if confirmed, it would be possible to refine the WHO grading of those oligodendrogliomas harboring a CDKN2A homozygous deletion and/or a p16 loss of protein expression. Future investigations should focus on an unexpected grade 4 subset of oligodendrogliomas, and a CDKN2A-deletion or p16-protein-loss assessment must be proposed and used routinely to define those specific aggressive cases. Regarding the H3K27-altered gliomas, no significant prognostic impact was observed, probably due to the small size of our population. Nevertheless, CDKN2A deletion and p16 expression have been recorded, if rarely, in this pediatric population of midline diffuse gliomas, as well as in sus-tentorial high-grade tumors . Our results showing frequent loss of p16 expression in the entire tumor or focally (7/9 H3 K27M and 6/8 wt cases) have implications that should be considered more largely, as they may open the path for therapies targeting the p16 pathway (e.g., CDK4 or cyclin D1) in this population. In low-grade gliomas, CDKN2A homozygous deletion seems to be an extremely rare event. No low-grade adult-type diffuse gliomas presented such deletion in our cohort. Our results therefore suggest that evaluating CDKN2A status in adult low-grade diffuse gliomas is not mandatory. Nevertheless, although CDKN2A homozygous deletion was rare in our cohort, with only one case of PA, its presence in cases of low-grade MAPK-induced gliomas showed a dramatic clinical evolution, pointing out the possibly strong prognostic impact of CDKN2A homozygous deletion in those populations . CDKN2A heterozygous deletion was observed in many tumor types without any prognostic impact. Nevertheless, additional work in other molecularly defined cohorts with larger numbers may be needed to confirm our results. 5. Conclusions Finally, beyond the prognostic impact, we were able to closely correlate p16 immunohistochemical expression and CDKN2A homozygous deletion. As expected, p16 overexpression was never associated with CDKN2A homozygous deletion. An absence of p16 expression was only related to CDKN2A homozygous deletion in two-thirds of cases, suggesting the influence of another silencing phenomenon in the remaining cases, perhaps relating to transcriptional or post-transcriptional rearrangements. Regarding the pattern of focal expression, a 5% cutoff of p16-positivity detected all CDKN2A homozygous deletions in our cohort and was associated with a very high sensitivity and negative predictive value for detecting a CDKN2A homozygous deletion with this IHC method. Furthermore, the similarities between the survival curves using both techniques suggest that p16 immunohistochemical expression and CDKN2A deletion evaluated by FISH assay give similar information regarding prognostic implications. So, IHC might be proposed as a pertinent surrogate test to evaluate CDKN2A status when using our cutoff, and it will provide adequate prognostic data in each glioma subset. Acknowledgments We are thankful to the associations which provided funding to initiate and finalize this monocentric study. We are also thankful to the pathology department technicians for their technical expertise in immunohistochemical assessment and to the Centre de Ressources Biologiques for the management of FFPE samples. We also thank Aurelia Nguyen and Noelle Weingertner for initiating the TMA program for gliomas. We thank all patients for allowing us to go further in this study. Author Contributions B.L., L.G., T.W., M.-P.C., H.C., R.S., G.N., E.G., D.R., E.P. and N.E.-W.: conceptualization, project administration, data curation, resources, formal analysis, visualization, manuscript editing; B.L., L.G., T.W., M.-P.C., H.C., R.S., G.N., E.G., D.R., E.P. and N.E.-W.: investigation, manuscript review and editing; B.L., L.G., E.G., D.R. and E.P.: investigation--sequencing; B.L., L.G., T.W., M.-P.C., H.C., R.S., G.N., E.G., D.R., E.P. and N.E.-W.: supervision, resources, manuscript review and editing; B.L., L.G., T.W., M.-P.C., H.C., R.S., G.N., E.G., D.R., E.P. and N.E.-W.: investigation, resources, manuscript review; N.E.-W., M.-P.C. and B.L.: resources, manuscript review; B.L., L.G., T.W., M.-P.C., H.C., R.S., G.N., E.G., D.R., E.P. and N.E.-W.: conceptualization, project administration, formal analysis, manuscript editing. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of University Hospital of Strasbourg. The declaration number DC-2017-3090 was obtained for the use of FFPE. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The entire and detailed immunohistochemistry data and FISH data are available upon request to the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Representative images of patterns of p16 immunohistochemical staining: absence of expression (A), focal expression in a variable amount of tumor cells (B), and intense and diffuse expression in a large majority of tumor cells (C). Scale bar is 50 mm for Figure 1A-C. Figure 2 Kaplan-Meier survival curves according to the pattern of p16 expression in IDH-wt glioblastomas (A) and IDH mutant 1p/19q codeleted oligodendrogliomas (grade 3) (B). Comparison of Kaplan-Meier survival curves according to the pattern of p16 expression in IDH-wt glioblastomas and MAPK-induced gliomas (C,D). p-value under 0.05 was considered statistically significant. Figure 3 Kaplan-Meier survival curves according to CDKN2A homozygous deletion in IDH-wt glioblastomas (A). Kaplan-Meier survival curves according to the pattern of p16 expression in IDH-wt glioblastomas (B). Kaplan-Meier survival curves according to CDKN2A homozygous deletion in oligodendrogliomas (grade 3) (C). Kaplan-Meier survival curves according to the pattern of p16 expression in oligodendrogliomas (grade 3) (D). ROC analysis plot of the performance of p16 IHC in detecting CDKN2A homozygous deletion (E). Kaplan-Meier survival curves according to CDKN2A deletion in the p16 negative groups (F). p-value under 0.05 was considered statistically significant. Figure 4 Schematic representation of the Oncogene-induced Senescence (linked to the activation of the MAPK pathway) leading to low-grade tumors (A). Schematic representation of p16 overexpression in high-grade gliomas linked to the positive feedback related to RB1 deletion (B). cancers-15-01512-t002_Table 1 Table 1 Clinical characteristics of the cohort. Characteristics Number (%) (n = 173) Number of Deceased Patients (%) Median age (years) 36.5 (1-79) Sex Male 95 (55) Female 78 (45) Adult-type diffuse gliomas IDH-mutant astrocytoma, grade 2 4 (2) 1 (25) IDH-mutant astrocytoma, grade 3 5 (3) 4 (80) IDH-mutant astrocytoma, grade 4 6 (3) 6 (100) IDH mutant and 1p/19q codeleted oligodendroglioma, grade 2 10 (6) 3 (30) IDH mutant and 1p/19q codeleted oligodendroglioma, grade 3 17 (10) 16 (94) IDH-wt glioblastoma, grade 4 63 (36) 63 (100) Circumscribed gliomas Pilocytic astrocytoma 36 (21) 3 (8) Fusion KIAA1549 :: BRAF 27 BRAF V600E mutation 1 NF1 mutation 1 FGFR1 duplication 1 NOS 6 Pleomorphic xanthoastrocytoma with anaplasia 1 (1) 0 (0) Glioneuronal tumors Ganglioglioma 10 (6) 0 (0) Fusion KIAA1549 :: BRAF 2 BRAF V600E mutation 8 Other low-grade pediatric gliomas Subependymal giant-cell astrocytoma 2 (1) 0 (0) Angiocentric glioma with MYBL1 alteration 1 (1) 0 (0) High-grade pediatric-type diffuse gliomas Diffuse midline glioma H3K27-altered 9 (5) 9 (100) High-grade diffuse pediatric glioma, H3 and IDH-wt 8 (4) 8 (100) Diffuse hemispheric glioma H3 G34-mutant 1 (1) 1 (100) Deceased patients 114 (66) Operated tumor recurrence 33 (19) Surgical specimens Biopsy 10 (6) Resection 163 (94) cancers-15-01512-t002_Table 2 Table 2 Patterns of p16 expression in the whole cohort. Diagnostic Number of Cases Absence of p16 Expression (Nb) Focal p16 Expression (Nb) P16 Overexpression (Nb) IDH-mutant astrocytoma, grade 2 4 0 4 0 IDH-mutant astrocytoma, grade 3 5 2 2 1 IDH-mutant astrocytoma, grade 4 6 2 3 1 IDH-mutant, 1p/19q codeleted oligodendroglioma, grade 2 10 0 10 0 IDH-mutant, 1p/19q codeleted oligodendroglioma, grade 3 17 5 10 2 IDH-wt glioblastoma, grade 4 63 36 17 10 Pilocytic Astrocytoma, grade 1 36 1 30 5 Anaplastic PXA, grade 3 1 1 0 0 Ganglioglioma, grade 1 10 0 5 5 Other low grade gliomas, grade 1 3 0 3 0 Diffuse midline glioma, H3K27-altered, grade 4 9 6 1 2 Diffuse pediatric-type glioma, H3 and IDH wt, grade 4 8 3 3 2 Diffuse hemispheric glioma, H3-G34-mutant, grade 4 1 0 1 0 Total 173 56 89 28 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000517 | We previously reported a splicing defect (CD22DE12) associated with the deletion of exon 12 of the inhibitory co-receptor CD22 (Siglec-2) in leukemia cells from patients with CD19+ B-precursor acute lymphoblastic leukemia (B-ALL). CD22DE12 causes a truncating frameshift mutation and yields a dysfunctional CD22 protein that lacks most of the cytoplasmic domain required for its inhibitory function, and it is associated with aggressive in vivo growth of human B-ALL cells in mouse xenograft models. Although CD22DE12 with selective reduction of CD22 exon 12 (CD22E12) levels was detected in a high percentage of newly diagnosed as well as relapsed B-ALL patients, its clinical significance remains unknown. We hypothesized that B-ALL patients with very low levels of wildtype CD22 would exhibit a more aggressive disease with a worse prognosis because the missing inhibitory function of the truncated CD22 molecules could not be adequately compensated by competing wildtype CD22. Here, we demonstrate that newly diagnosed B-ALL patients with very low levels of residual wildtype CD22 ("CD22E12low"), as measured by RNAseq-based CD22E12 mRNA levels, have significantly worse leukemia-free survival (LFS) as well as overall survival (OS) than other B-ALL patients. CD22E12low status was identified as a poor prognostic indicator in both univariate and multivariate Cox proportional hazards models. CD22E12low status at presentation shows clinical potential as a poor prognostic biomarker that may guide the early allocation of risk-adjusted, patient-tailored treatment regimens and refine risk classification in high-risk B-ALL. B-ALL CD22 mRNA relapse aberrant splicing SIGLEC-2 National Cancer InstituteU01-CA-151837 R01CA-154471 R21-CA-164098 V-Foundation, Nautica TriathlonRonald McDonald House Charities of Southern CaliforniaWilliam Lawrence, Blanche Hughes Foundation grantAres PharmaceuticalsThe project described was supported in part by DHHS grants U01-CA-151837, R01CA-154471, and R21-CA-164098 (F.M.U.) from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. This work was also supported in part by the V-Foundation, Nautica Triathlon as well as the Ronald McDonald House Charities of Southern California and a William Lawrence, Blanche Hughes Foundation grant (F.M.U.). This study also received funding from Ares Pharmaceuticals (S.Q.). Authors F.M.U. and S.Q., who participated in the analysis and decision to submit the manuscript for publication, are affiliated with the funder Ares Pharmaceuticals. pmc1. Introduction The inhibitory B-cell co-receptor CD22 (Siglec-2) regulates several signaling pathways related to the proliferation and survival of B-lineage lymphoid cells . The inhibitory function of CD22 is mediated by the interactions of its cytoplasmic domain with the protein tyrosine phosphatase SHP-1 . Any CD22 mutation impairing or preventing this protein-protein interaction would hamper the inhibitory function of CD22 and thereby result in abnormally augmented proliferation as well as prolonged survival of B-lineage lymphoid cells. We previously reported a splicing defect associated with the deletion of CD22 Exon 12 (CD22E12) in leukemia cells from patients with CD19+ B-precursor acute lymphoblastic leukemia (B-ALL) . We demonstrated that this CD22E12 deletion ("CD22DE12") causes a truncating frameshift mutation and yields a C-terminal truncated dysfunctional CD22 protein that lacks most of its cytoplasmic domain, including the signal transduction elements that are required for the interaction of CD22 with SHP-1 . CD22DE12 is associated with aggressive in vivo growth of human B-ALL cells in mouse xenograft models . Furthermore, forced overexpression of the mutant human CD22DE12 in transgenic mice caused fatal B-ALL, demonstrating that CD22DE12 alone may be sufficient as a driver lesion for the leukemic transformation and aggressive in vivo growth of BCPs . We previously reported that CD22E12 mRNA expression levels, as measured via multiprobe transcriptome profiling using the microarray platform, are selectively and significantly reduced in B-ALL cells with the CD22DE12 splicing defect . Using Western blot analysis and RT-PCR, we demonstrated that CD22 exon 12 deletion is not observed in normal human pro-B and pre-pre-B cells . Further, our comparison of matched-pair diagnostic vs. post-induction remission bone marrow specimens from B-ALL patients showed a marked reduction of CD22DE12 mRNA levels after chemotherapy. These findings demonstrate that normal hematopoietic cells in the remission bone marrow of CD22DE12+ B-ALL patients do not express the aberrant CD22DE12 mRNA associated with the CD22DE12 genetic defect . Although CD22DE12 was detected in a high percentage of newly diagnosed and relapsed B-ALL patients , its clinical significance has yet to be deciphered. The purpose of the present study was to evaluate the clinical prognostic significance of CD22DE12 in B-ALL. We postulated that residual wildtype CD22 with undeleted exon 12 could compensate for the missing inhibitory function of the truncated CD22 molecules and thereby mitigate the net effect of the CD22DE12 splicing defect on B-ALL cells . Indeed, we previously demonstrated that lentiviral-based overexpression of full-length wildtype CD22 in CD22DE12-positive B-ALL cells virtually abrogates their clonogenic growth in vitro . We hypothesized that the missing inhibitory function of the truncated CD22 molecules could not be adequately compensated by very low levels of wildtype exon 12-containing CD22. Therefore, we set out to test the hypothesis that B-ALL patients with very low levels of CD22E12 ("CD22E12low"), as measured by RNAseq-based CD22E12 mRNA levels, would have a worse prognosis than other B-ALL patients. Our findings provide unprecedented evidence that CD22E12low B-ALL patients have worse leukemia-free survival (LFS) and overall survival (OS) outcomes than other B-ALL patients. CD22E12low status was identified as a poor prognostic indicator in univariate and multivariate Cox proportional hazards models. 2. Materials and Methods 2.1. Comparative Analysis of the Expression Levels of CD22 Exons 11-14 in Primary Leukemia Cells from Newly Diagnosed Pediatric Patients with B-All and Normal Hematopoietic Cells from Non-Leukemic Controls Using a Human Genome Expression Microarray Platform for Transcriptome Profiling We used the publicly available archived gene expression profiling datasets GSE13159, GSE11877, and GSE13351, which were generated in the GeneChip Human Genome U133 Plus 2.0 Array platform (Thermo Fischer Scientific, Waltham, MA, USA), to examine the relative expression levels of CD22 exons 11-14 in primary leukemia cells from 421 newly diagnosed pediatric B-ALL patients. The B-ALL patient population included Ph-like B-ALL patients (n = 154; GSE11877 and GSE13351); TCF3-PBX1+/E2A-PBX1 B-ALL patients (n = 25; GSE11877 and GSE13351); KMT2A/MLL-R+ B-ALL patients (n = 25; GSE11877 and GSE13351); BCR-ABL/Ph+ ALL patients (n = 123; GSE13159 and GSE13351); other B-ALL patients (n = 94; GSE11877 and GSE13351). BLAT analysis of CD22 probe sequences for the Affymetrix probe set 217422_s_at (9 probes covering exons 11-14; Human Genome U133 Plus 2.0 Array platform) that were mapped onto specific CD22 exons was visualized using the UCSC genome browser. Expression of each probe was log2-transformed and median-centered across all probes in each sample. Similarly, the expression levels of CD22E11, CD22E13, and CD22E14 were estimated by determining the mean expression values for 6 probes mapped to these CD22 exons in B-ALL samples mean-centered to the corresponding expression values in non-leukemic CON samples. The perfect match (PM) signal value for each probe was background-corrected, robust multiarray analysis (RMA)-normalized, log2-transformed, and median-centered across all probes in each sample. The expression level of CD22E12 in the B-ALL samples (n = 421) was estimated from the mean signal value for the 3 CD22E12 probes, namely HG-U133_PLUS_2:217422_S_AT_7 aligned to chr19:35836590-35836614, HG-U133_PLUS_2:217422_S_AT_6 aligned to chr19:35836566-35836590, HG-U133_PLUS_2:217422_S_AT_5 aligned to chr19:35836535-35836559, and mean-centered to the mean signal value for the same probes in non-leukemic control (CON) samples (n = 74, GSE13159). A CD22E12 index was calculated by subtracting the mean expression values for the 6 probes for CD22E11, CD22E13, CD22E14 in the 217422_s_at probe set, namely, HG-U133_PLUS_2:217422_S_AT_11 aligned to chr19: 35837525-35837549/CD22E14), HG-U133_PLUS_2:217422_S_AT_10 aligned to chr19: 35837478-35837502/CD22E14, HG-U133_PLUS_2:217422_S_AT_8 aligned to chr19: 35837100-35837124/CD22E13), HG U133_PLUS_2:217422_S_AT_9 aligned to chr19: 35837117-35837139/CD22E13), HG-U133_PLUS_2:217422_S_AT_4 aligned to chr19:35835979-35836003/CD22E11, and HG-U133_PLUS_2:217422_S_AT_3 aligned to chr19:35835811-35835960/CD22E11, from the expression values for the 3 CD22E12 probes, as previously reported . Expression levels for CD22E12 versus the mean of CD22E11, CD22E13, and CD22E14 were visualized using density graphs (fitted using a Gaussian smoothing kernel density estimation) superimposed on histograms of the CD22E12 index values and were plotted for CON and B-ALL samples (ggplot2_3.3.5 R package). 2.2. Detection of CD22DE12 mRNA in B-ALL Leukemia Samples via Real-Time Quantitative RT-PCR Cellular RNA was extracted from Ficoll-Hypaque-separated leukemia cells of 12 de-identified pediatric patients with newly diagnosed high-risk B-ALL and 12 de-identified pediatric patients with newly diagnosed standard-risk ALL using the Qiagen RNeasy Mini Kit (Cat# 74104, Qiagen, Valencia, CA). The secondary use of de-identified leukemia cells for subsequent laboratory studies did not meet the definition of human subject research per 45 CFR 46.102 (d and f) because it did not include identifiable private information, and it was approved by the IRB (CCI) at the Children's Hospital Los Angeles (CHLA) (Protocol #' CCI-09-00304 and CCI-10-00141; Human Subject Assurance Number: FWA0001914). One-step real-time quantitative (q) RT-PCR was performed using the One-Step PrimeScript RT-PCR kit (Cat. # RR064B, Takara/Clontech, Mountain View, CA) and the Applied Biosystems 7900HT Fast Real-Time PCR System housed in the CHLA/USC Stem Cell Core Facility to compare the expression levels of the CD22DE12 mRNA in pediatric B-ALL samples, as previously described in detail . The PCR primer pair (viz.: forward primer E11-F2: 5'-CAGCGGCCAGAGCTTCTT-3' and reverse primer E13-R2: 5'-GCGCTTGTGCAATGCTGAA-3') was selected to amplify a 113-bp fragment spanning from Exon 11 to Exon 13 of the human CD22DE12 cDNA. The amplified fragment was then specifically annealed to a pre-mixed oligo DNA probe (5'-TGTGAGGAATAAAAAGAGATGCAGAGTCC-3') conjugated with 5' FAM reporter and 3'BHQ quencher on the CD22DE12-specific unique junction region between exon 11 and exon 13. The FAM reporter fluorescence intensity was recorded by applying the sequence detection system of the real-time qPCR system, expressed as threshold cycle threshold (Ct) value for quantification, as reported . Each sample was also subjected to a qRT-PCR reaction for the housekeeping gene beta (b)-actin with a primer set amplifying a 234-bp region at the junction between exon 4 and exon 5 of the human b-actin gene for normalization of the Ct values, as previously reported . The results were visualized in box plots superimposed with a kernel density plot showing the peaks, median, and inter-quartile range in the numerical distribution of the data (ggplot2_3.3.5 R package). 2.3. Data Normalization for Exon-Level CD22 Gene Expression Data Derived from Primary B-ALL Cells We downloaded the RNAseq data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program accessed on 28 January 2022). Summary files were named using a coding system specific to Office of Cancer Genomics (OCG) characterization programs accessed on 28 January 2022), allowing for the identification of data files that contained exon-level mRNA expression levels for each sample. These data files reported the exon locations for the CD22 gene (Human (GRCh37/hg19) build), raw read counts, length of exons, and reads per kilobase million (RPKM) values. Read count, alignment, and within-sample-level normalization of mRNA expression levels were detailed in previous study reports that contributed to the data deposited in the TARGET repository (4; summarized in (accessed on 28 September 2022)). Briefly, exon-level quantification was performed by aligning Illumina paired-end RNA sequencing reads (fasta files) to GRCh37-lite genome-plus-junctions and exon-exon junction sequences, whereby the corresponding coordinates were based on annotations of transcripts in the Ensembl (v59) reference using BWA version 0.5.7. Mapped reads between these junction regions were positioned according to the reference genome (GRCh37/hg19) build). The raw count reports the number of reads that overlapped each of the CD22 exon junctions in each sample. The corresponding data files with exon-level quantification for the CD22 exons 11, 12, 13, and 14 were manually downloaded from the TARGET repository. The exon locations, which were all on the positive strand, were as follows: CD22E11:35835954-35836029; CD22E12:35836505-35836623; CD22E13:35837054-35837138; CD22E14:35837469-35838258. We utilized the normalized RPKM metric for the exon-level quantification of CD22 mRNA. In this summarization, the total read count in a sample was divided by 106 to obtain the scaling factor. The read counts were divided by the scaling factor to normalize the read counts for sequencing depth (reads per million (RPM)). The RPM value was then divided by the length of the exon in kilobases to calculate RPKM. We calculated the CD22E12 expression to measure the relative level of CD22E12 expression compared to the mean level of expression of 3 surrounding exons with similar RPKM values, namely, CD22E11, CD22E13, and CD22E14. Mean RPKM values were used for cases with duplicate samples. The sample information was obtained from annotation files deposited on the TARGET website: TARGET_ALL_SampleMatrix_Phase2_Validation_20190606.xlsx and TARGET_ALL_SampleMatrix_Phase2_Discovery_20190606.xlsx. The archived database contained the data from the B-ALL patients (n = 141) that were used in our analyses, including 90 pediatric or young adult patients with NCI high-risk ALL treated in the Children's Oncology Group (COG) studies P9906 or AALL0232 and 51 pediatric patients with standard risk ALL treated in COG study AALL0331 . Within the 141-patient RNA-seq subset, 89 high-risk patients were treated in the COG study AALL0232 , and 51 standard-risk patients were treated in the COG study AALL0331 . CD22-targeting therapies were not part of these protocols. No patient received inotuzumab-ozogamicin. Treatment details for the AALL0232 and AALL0331 protocols are described in detail and can be accessed via and respectively. In brief, AALL0232 was a randomized, multicenter study (see for treatment details, accessed on 1 January 2023). Patients were stratified according to early response (slow early response (SER) vs. rapid early response (RER)). For Induction therapy, patients were randomized to 1 of 4 treatment arms: (i) ARM I: patients received cytarabine intrathecally (IT) on day 1, vincristine intravenously (IV) and daunorubicin IV on days 1, 8, 15, and 22, dexamethasone orally (PO) or IV twice daily (BID) on days 1-14, methotrexate (MTX) IT on days 8 and 29*, and pegaspargase intramuscularly (IM) once on day 4, 5, or 6. Patients with CNS3 disease (WBC > 5/mL in cerebrospinal fluid and positive for blasts on cytospin) also received MTX IT on days 15 and 22. (ii) ARM II: patients received induction therapy as in ARM I. (iii) ARM III: patients received cytarabine, vincristine, daunorubicin, and pegaspargase as in ARM I. Patients also received prednisone PO or IV BID on days 1-28 and MTX IT on days 8 and 29. (iv) ARM IV: patients received induction therapy as in ARM III. Patients in all arms were evaluated at day 29 of induction therapy. Patients with M3 disease were removed from the study. Patients with M1 disease and less than 1% minimal residual disease (MRD) proceeded to consolidation therapy beginning on day 36. Patients with M2 disease or with MI disease and at least 1% MRD received extended induction therapy for 2 additional weeks. Patients with SER disease and MLL rearrangements were removed from the study. For extended induction therapy, patients continued to receive therapy according to the arm to which they were originally randomized: ARMS I and II: patients received dexamethasone PO or IV BID on days 1-14, vincristine IV on days 1 and 8, daunorubicin IV on day 1, and pegaspargase IM on day 4, 5, or 6 and were then reevaluated; ARMS III and IV: patients received prednisone PO or IV BID on days 1-14 and vincristine, daunorubicin, and pegaspargase as in Arms I and II, and they were then reevaluated. Patients in all arms who had M1 disease and less than 1% MRD after extended induction proceeded to consolidation therapy and continued as SER patients. All other patients were removed from the study. For consolidation therapy, all patients received cyclophosphamide IV over 30 min on days 1 and 29, cytarabine IV or subcutaneously (SC) on days 1-4, 8-11, 29-32, and 36-39, mercaptopurine (MP) PO on days 1-14 and 29-42, vincristine IV on days 15, 22, 43, and 50, pegaspargase IM on days 15 and 43, and MTX IT on days 1, 8, 15, and 22. Patients with testicular disease also received radiotherapy to the testes. Patients with CNS3 disease received MTX on days 1 and 8 only. For interim maintenance therapy 1, patients continued to receive treatment according to the arm to which they were originally randomized: (i) ARM I: (escalating-dose MTX) patients received vincristine IV and escalating-dose MTX IV on days 1, 11, 21, 31, and 41, pegaspargase IM on days 2 and 22, and MTX IT on days 1 and 21. (ii) ARM II: (high-dose MTX) patients received vincristine IV and high-dose methotrexate IV over 24 h on days 1, 15, 29, and 43, MP PO on days 1-56, and IT MTX on days 1 and 29. Patients also received leucovorin calcium IV every 6 h for at least 3 doses, beginning 42 h after start of each MTX infusion. (iii) ARM III: (escalating-dose MTX) patients received interim maintenance 1 therapy as in ARM I. (iv) ARM IV: (high-dose MTX) patients received interim maintenance therapy as in ARM II. For delayed intensification therapy 1, all patients received vincristine IV on days 1, 8, 15, 43, and 50, dexamethasone PO or IV BID on days 1 to 21 for patients ages 1 to 12 OR on days 1-7 and 15-21 for patients ages 13 and over, doxorubicin IV on days 1, 8, and 15, pegaspargase IM on day 4, 5, or 6 as well as day 43, cyclophosphamide IV over 30 min on day 29, cytarabine IV or SC on days 30-33 and 37-40, thioguanine PO on days 29-42, and MTX IT on days 1, 29, and 36. After delayed intensification I, SER patients proceeded to interim maintenance 2 and delayed intensification 2. RER patients proceeded directly to maintenance. For interim maintenance therapy 2, all patients received vincristine IV and MTX IV on days 1, 11, 21, 31, and 41, pegaspargase IM on days 2 and 22, and MTX IT on days 1 and 21. Patients then proceeded to delayed intensification 2. For delayed intensification therapy 2, all patients received therapy as in delayed intensification 2, ARM I. CNS3 patients also received radiotherapy for 3-10 days, beginning on day 29. All other SER patients, patients with MLL rearrangements, and some patients pretreated with steroids (>48 h within the week prior to diagnosis) received prophylactic cranial radiotherapy (CRT) for 8 days, beginning on day 29. Patients then proceeded to maintenance therapy. For maintenance therapy, all patients received vincristine IV on days 1, 29, and 57, dexamethasone PO BID on days 1-5, 29-33, and 57-61, MP PO on days 1-84, MTX IT on day 1*, and MTX PO on days 1, 8, 15, 22, 29, 36, 43, 50, 57, 64, 71, and 78. RER patients (who did not undergo CRT) also received MTX IT on day 29 for maintenance courses 1-4. In all arms, maintenance therapy was repeated every 12 weeks until the total duration of therapy was 2 years from the start of interim maintenance 1 for female patients and 3 years from the start of interim maintenance 1 for male patients. Patients with testicular disease could receive testicular radiotherapy for 8 days during one of the first 3 courses of maintenance therapy. Patients were followed monthly for 1 year, every 2 months for 1 year, every 3 months for 1 year, every 6 months for 1 year, and then annually thereafter. In the AALL0331 study, which tested whether intensified postinduction therapy that improves survival in children with high-risk B-cell acute lymphoblastic leukemia (ALL) would also improve outcomes for those with standard-risk (SR) ALL, patients received a 3-drug induction with IT cytarabine on day 1; weekly IV vincristine for 4 doses; oral dexamethasone for 28 days; 1 dose of intramuscular PEG on day 4, 5, or 6; IT MTX for 2 to 4 doses (see accessed on 28 September 2022). Bone marrow (BM) aspiration was performed on days 8 and 15 (if the day-8 marrow was M2/M3) to determine the hematologic response by examining morphology. MRD testing was performed at day 29 using flow cytometry. Rapid early response (RER) was defined as <5% BM blasts (M1) by day 15 based on local morphologic interpretation and an M1 BM with MRD < 0.1% at day 29. Slow early responders (SERs) had an M2 (5-25%) or M3 (>25%) BM on day 15 and/or positive MRD (>=0.1% to <1%) at day 29. For patients with M3 marrow at day 29, induction was considered to have failed, and they were taken off protocol therapy. Patients with an M2 marrow or an M1 marrow with MRD >= 1% at day 29 received an extended induction with 2 additional weeks of therapy and continued on study as SERs if they achieved day-43 M1 marrow and MRD < 1%. Those not achieving these criteria were removed from protocol therapy. All patients were initially required to have central testing for triple trisomies of chromosomes 4, 10, and 17 (TT) and BCR-ABL1, ETV6-RUNX1, or KMT2A rearrangement (KMT2A-R) using fluorescence in situ hybridization. After induction, patients were classified into 1 of 3 risk groups: SR low (RER, CNS1, and favorable cytogenetics of TT or ETV6-RUNX1 fusion), SR average (no unfavorable genetic features (BCR-ABL1, KMT2A-R, or hypodiploidy with < 44 chromosomes), RER, and CNS1 or 2 (patients with favorable genetics who were RERs and CNS2)), or SR high (KMT2A-R and RER, anyone with CNS3 at diagnosis, and SERs by morphology or MRD). Patients with overt testicular leukemia were not eligible. Patients with BCR-ABL1 fusion or hypodiploidy did not continue to receive therapy after induction. Patients with SR-low disease were randomly assigned to regimens with or without 4 additional doses of PEG at approximately 3-week intervals, with the backbone of standard consolidation (SC) and initially standard IM with weekly oral MTX. All patients with SR-low disease received standard DI and maintenance. Patients with SR-average disease were randomly assigned initially in a 2-by-2 factorial design to 1 of 4 treatment regimens: SS (SC and standard IM and DI), SA (SC with intensified IM (AIM) and DI (ADI)), IS (intensified consolidation (IC) and standard IM/DI), and IA (IC, AIM, and ADI). IC was identical to the augmented Berlin-Frankfurt-Munster (BFM) consolidation used in COG AALL0232, AIM was identical to the Capizzi-style escalating IV MTX and PEG, and DI incorporated additional doses of VCR and PEG, as used in AALL0232. Patients with SR-high disease were nonrandomly assigned to receive full augmented BFM therapy, as administered in CCG 1961, including IC, AIM1, ADI1, AIM2, ADI2, and maintenance. CNS3 patients underwent 18-Gy cranial irradiation. In all arms of AALL0331, the length of therapy from the start of IM1 was 2 years for girls and 3 years for boys. In 2008, the results of CCG 1991 became available, showing that escalating IV MTX without leucovorin rescue improved EFS compared to standard IM with oral MTX. AALL0331 amendment 2C replaced the oral MTX IM phase with escalating IV MTX for all patients with SR-average disease. All patients with SR-average disease received IM with IV escalating MTX and standard DI. This amendment also changed dexamethasone administration in DI to discontinuous dosing (days 1-7 and 15-21) rather than a continuous schedule (days 1-21) because of increased rates of osteonecrosis in AALL0232 with continuous dexamethasone during DI. When the results of AALL0232 demonstrated that high-dose MTX was superior to Capizzi MTX, amendment 7 (May 2011) changed therapy for patients with SR-high disease who had not yet begun maintenance cycle 2. They then received an additional IM phase with high-dose MTX. 26 patients out of the 1126-patient complete set (2.3%) of the TARGET database for B-ALL received a transplant compared to 6 patients out of 141 RNAseq subset (4.3%) who received a transplant (p = 0.2). Within the 141-patient RNAseq subset, none of the 21 CD22E12low patients received transplants compared to 6 out of 120 (5%) remaining patients from the RNAseq subset (Fisher's Exact Test, p = 0.6). No information is available regarding the type or timing of the transplants. No patient received inotuzumab-ozogamicin. We excluded the data from 43 additional patients with an unknown cell of origin/immunophenotype information for leukemia cells. In addition, data files reporting the RPKM metric for CD22 gene exon-level quantification of mRNA for CD22 exons 1-4 were downloaded from the TARGET phase 2 project accessed on 28 September 2022). The expression level of each exon was mean-centered to the average RPKM values across exons 1 to 4 (CD22E1-4) for each of the 141 B-ALL patients (RPKM-normalized). 2.4. Hierarchical Clustering Analysis to Identify CD22E12low B-ALL Patients A one-way hierarchical clustering technique was used to organize the RNAseq-based mRNA expression patterns for the CD22 exons 11, 13, and 14 side-by-side with the expression of CD22E12 across 141 B-ALL patients. The expression level of each CD22 exon was mean-centered to the average RPKM values across CD22E11-14 such that patient level and exon-level expression patterns displayed similar expression profiles that were grouped together using the average distance metric (default Euclidean distance and Wards linkage implemented using the heatmap.2 function in the R package gplots_3.1.1). The cluster analysis revealed a subset of patients whose cells exhibited a markedly and selectively reduced expression level of CD22E12 compared to CD22E11, CD22E13, and CD22E14 ("CD22E12low subset"). To confirm the selective reduction of CD22E12 relative to CD22E11 and CD22E13 in CD22E12low patients, the corresponding normalized RPKM expression values were compared utilizing a two-factor ANOVA model: patient grouping and exon ID were used as fixed variables, and patient grouping x exon ID was an interaction term (p-values were adjusted for multiple comparisons by controlling the false discovery rate to less than 0.01 (multcomp_1.4-17 and emmeans_1.7.0 packages ran in R version 4.1.2 (1 November 2021) with Rstudio front end (RStudio 2021.09.0 + 351 "Ghost Orchid" Release)). Bar chart graphics were constructed using the ggplot2_3.3.5 R package. 2.5. Normalization of Gene Level RNAseq Data Derived from Primary B-ALL Cells We downloaded gene-level RNAseq data from the TARGET program accessed on 9 July 2022) using the web-scraping utility implemented in R version 4.1.2 (1 November 2021) (rvest_1.0.2 and stringr_1.4.0). These data files reported the Ensembl gene IDs, raw read counts, median length of each gene, and RPKM values. Gene identifications were converted from ensemble IDs to gene symbols using the Bioconductor database org.Hs.eg.db_3.14.0, which was interrogated using the functions provided in AnnotationDbi_1.56.1. We compared the gene level RNAseq data for B-ALL samples that exhibited substantially reduced levels of CD22E12 mRNA (n = 21; CD22E12low) versus all other B-ALL samples (n = 120) using the DESeq2 package (DESeq2_1.34.0) obtained from (accessed on 28 September 2022) and implemented using R version 4.1.2 (1 November 2021) . DESeq2 employs a generalized linear model for each gene that fits raw read counts to negative binomial distribution to calculate mean and variance estimates, whereby the mean is taken as a quantity proportional to the concentration of cDNA fragments from the gene in the sample and scaled by a normalization factor across all samples. The normalization method in the DESeq2 algorithm determines the counts divided by sample-specific size factors calculated from the median ratio of gene counts relative to the geometric mean per gene across all samples that accounts for the sequencing depth and RNA composition of each gene. This method allows for fold change comparisons across treatment groups in the GLM model . The statistical significance of differences in gene expression levels was assessed by testing the null hypothesis that there is no differential expression across the two sample groups (Log2 fold change = 0) using the Wald test , reporting the test statistic and p-value for each gene. To visualize the gene expression profiles in heatmaps, we calculated the normalized log2 values from the RNAseq count data using the statistical package implemented in R, vsn_3.62.0 . This method uses a robust variant of the maximum likelihood estimator for the stochastic model of count data that employs data calibration, accounting for the dependence of variance of mean intensity and variance stabilizing data transformation. Low-count values tend to generate large fold changes; therefore, to calculate a more accurate log2 fold change estimate, we applied a shrinkage of the log2 fold change estimates toward zero when the read counts were low and variable ("normal" function in the DESeq2 package) . 2.6. Gene Set Enrichment Analysis (GSEA) for Evaluation of Reactome Pathways in B-ALL Patients with Low CD22E12 Expression Data files reporting raw read counts determined using gene-level quantification of mRNA were downloaded from the TARGET phase 2 project (accessed on 9 July 2022)). We determined the differential expression of genes comparing patients that exhibited low CD22 exon 12 expression (n = 21; CD22E12low) with all other patients (n = 120) using DESeq2 package (DESeq2_1.34.0 implemented in R). We used GSEA (fgsea_1.20.0 implemented in R) and the rank-ordered Wald statistic for the comparison of the 21 CD22E12low patients versus the remaining 120 patients regarding representation patterns of reactome pathways (reactome.db_1.77.0 obtained from Bioconductor: accessed on 9 July 2022). We focused our initial analysis on pathways grouped under transcription, translation (including mRNA processing, mRNA transport, and post-translational modification), and cell cycle because our previously published cluster analysis of highly enriched gene sets revealed that transcriptional, translational and cell cycle processes were significantly upregulated in all three comparisons of CD22DE12 Tg mice compared to BCR-ABL Tg, Em-MYC Tg, and WT mice (GSE58874 and GSE58872) . In addition, pathways were analyzed and grouped by signal transduction based on our previously published phosphoproteome data for CD22DE12-Tg mice (GSE58873 and GSE 58874). The GSEA evaluated the enrichment score (ES) values, representing observed rankings compared to the expected null distribution calculated from the permutation of gene assignments to the ranking scores. Nominal p-values were computed by comparing the tails of the ES scores for observed and permutation-generated null distributions following 100,000 permutations. The significance of the association was assessed using weighted Kolmogorov-Smirnov statistics. In order to compare the differences in gene expression levels across gene sets, normalized enrichment scores (NES) were calculated based on the number of genes in the gene set. Low-expression genes (base mean values calculated in the Dseq2 procedure > 10 normalized counts across all samples) were filtered before GSEA analysis for representation in reactome pathways. This resulted in 22,068 genes that were processed for GSEA, comparing CD22E12low B-ALL patients with all other patients for gene set enrichment in 1256 in reactome pathways (gene sets ranged from 10-100 genes; 100,000 permutations were performed to calculate enrichment scores and associated p-values). The expression of significantly affected genes was visualized using heatmaps and dendrograms represented in a cluster figure (R package gplots_3.1.1) depicting normalized expression levels in CD22E12low B-ALL samples mean-centered to all other samples. 2.7. Analysis of Treatment Outcomes according to RNAseq-Based CD22E12 mRNA Expression Levels The outcome data were retrieved from the TARGET clinical annotation files TARGET_ALL_ClinicalData_Phase_II_Discovery_20211118.xlsx and TARGET_ALL_ClinicalData_Phase_II_Validation_20211118.xlsx. The Kaplan-Meier (KM) method, log-rank chi-square test, and the software packages survival_3.2-13, survminer_0.4.9, and survMisc_0.5.5, which were operated in the R environment, were used to compare the treatment outcomes of patients, including time to relapse, relapse-free survival (LFS), and overall survival (OS). Graphical representations of the treatment outcomes were generated using three graph-drawing packages implemented in the R programming environment: dplyr_1.0.7, ggplot2_3.3.5, and ggthemes_4.2.4. We compared the outcomes of CD22E12low patients (n = 21) vs. all other patients (n = 120) in an effort to evaluate the prognostic significance of the CD22E12low status. The statistical significance of differences in the outcomes of the compared patient subsets was examined using the log-rank chi-square test, and p-values less than 0.05 were deemed significant. 2.8. Multivariate and Univariate Cox Regression Models to Test for the Independent Effect of CD22E12low Status Multivariate analysis of the poor prognostic impact of CD22DE12 was performed using a Cox proportional hazards model in which we examined if the CD22E12low status observed in 21 of 141 B-ALL patients remained a significant predictor of adverse outcomes after controlling for other patient characteristics of established prognostic significance. We compared the hazard ratios (HR) from the multivariate Cox model with univariate Cox models for each of the prognostic factors used as covariates in the multivariate model. Estimates of the life table HR were calculated using the exponentiated regression coefficient for Cox regression analyses implemented in R (survival_3.2-13 was run with R version 4.1.2 (1 November 2021)). Forest plots were utilized to visualize the HR values obtained in the Cox proportional hazards model (survminer_0.4.9 was run with R version 4.1.2 (1 November 2021)). A total of 141 patients were evaluable in the Cox proportional hazards regression model. Analyses were performed both for all 141 patients as well as for the high-risk subset of 90 patients. The patient characteristics analyzed in the Cox proportional hazards model included the following: (i) CD22E12low status, (ii) age, (iii) gender, (iv) cytogenetic features including molecular markers, (v) WBC at diagnosis (both linear and categorized as >=20 x 109/L or < 20 x 109/L), and (vi) measurable residual disease (MRD) burden at the end of induction therapy on day 29 (0% vs. >0%; 0% defined as < 0.001% or <1 x 10-5), as measured by using 6-color flow cytometry. 3. Results 3.1. Interpatient Heterogeneity in Microarray-Based CD22E12 and qRT-PCR-Based CD22DE12 mRNA Expression Levels among Newly Diagnosed B-ALL Patients CD22DE12 is associated with a selective reduction in expression levels of CD22E12 mRNA . We first examined the distribution of CD22E12 mRNA expression levels in primary leukemia cells from 421 B-ALL patients, as measured by the CD22E12 index values based on the transcriptome profiling data obtained using the genome expression microarray platform . The CD22E12 index values for B-ALL samples showed interpatient variability (mean +- SE = -0.29 +- 0.03; median = -0.29; range = -1.92-1.92; n = 421) . The density graph of the CD22E12 index values for B-ALL cells showed broad multipeak distributions consistent with marked patient-to-patient heterogeneity in CD22E12 expression levels. Next, we used qRT-PCR to examine the CD22DE12 expression levels in primary leukemia cells from 24 pediatric B-ALL patients . The displayed DCt values demonstrated marked interpatient heterogeneity and broad multipeak distributions in CD22DE12 expression levels. The data on the microarray-based CD22E12 index values combined with the qRT-PCR-based data on CD22DE12 Ct and DCt values indicate that the biological impact of CD22DE12 may vary from patient to patient due to varying levels of normal CD22 and truncated CD22 levels. 3.2. Interpatient Heterogeneity in Selective Reduction of RNAseq-Based CD22E12 Expression Levels among B-ALL Patients We next examined the relative expression levels of CD22E12 in primary leukemia cells from 141 patients with B-ALL by interrogating the archived exon-level quantitative RNAseq data from the TARGET program. In accordance with the results obtained with the microarray platform and qRT-PCR data, the RNAseq data showed marked heterogeneity in the magnitude of the selective reduction of CD22E12 mRNA expression levels, as evidenced by the heat map of the cluster figure and the broad distribution of the normalized RPKM values for CD22E12 . By using the method of hierarchical clustering, a subset of 21 patients ("CD22E12low") with selective reduction CD22E12 levels relative to CD22E11, CD22E13, and CD22E14 levels was identified, in which the normalized RPKM value for CD22E12 mRNA was <0.8 . The mean CD22E12 expression level (in normalized RPKM) for the CD22E12low patients was 0.714 +- 0.014 (median = 0.728; range = 0.572-0.785), which was significantly lower than the mean CD22E12 expression level of 0.934 +- 0.006 (median = 0.935; range = 0.805-1.133) for the remaining 120 patients (two-way ANOVA, linear contrast, p-value < 10-15) . The CD22E12 expression level for this subset was significantly lower than the expression levels for exons CD22E11 (mean = 1.101 +- 0.018; median = 1.109; range = 0.839-1.224; p-value < 10-15), CD22E13 (mean = 1.073 +- 0.011; median = 1.076; range = 0.961-1.151; p-value < 10-15), and CD22E14 (mean = 1.112 +- 0.015; median = 1.103; range = 1.026-1.279; p-value < 10-15). . In addition to CD22DE12, CD22 exon 2 (CD22E2) skipping that results in very low CD22E2 mRNA levels also occurs in B-ALL and is associated with resistance to CD22-directed immunotherapies due to reduced expression of the target CD22 protein. As both events are caused by aberrant splicing, we next evaluated CD22E2 mRNA levels in CD22E12low patients in an effort to determine if CD22E12low and CD22E2low subsets overlap in the studied B-ALL patient population (n = 141). A subset of 34 patients (24.1%) with CD22E2 reductions (CD22E2low) were identified via examination of the RPKM values for CD22E2 and the adjacent CD22 exons 1 (CD22E1), 3 (CD22E3), and 4 (CD22E4) . The normalized RPKM value for each patient in this CD22E2low subset was less than 0.397. The mean CD22E2 expression level for the CD22E2low patients was 0.295 +- 0.016, which was significantly lower than the mean CD22E2 expression level of 0.565 +- 0.014 for the remaining 107 patients (Welch two-sample t-test, T = 12.673, df = 83.3, p-value < 10-15) . Among the 21 CD22E12low patients and 120 others, 8 (38%) and 26 (22%) were CD22E2low (Fisher's exact test, p = 0.16). The density plots for CD22E2 mRNA expression for CD22E12low vs. other patients displayed a near-complete overlap . The mean CD22E2 expression level for the CD22E12low patients was 0.46 +- 0.039, which was not significantly different from the mean CD22E2 expression level of 0.507 +- 0.016 for the remaining 120 patients (Welch two-sample t-test, T = 1.13, df = 27.2, p-value = 0.27). The CD22E2 expression levels among the 34 CD22E2low patients were very similar for the 8 CD22E12low subset vs. the remaining 26 patients (0.298 +- 0.032 vs. 0.295 +- 0.019). Likewise, the CD22E2 expression levels for the 107 non-CD22E2low patients did not show significant differences between 13 CD22E12low patients and the remaining 94 patients (0.56 +- 0.039 vs. 0.566 +- 0.015) (two-way ANOVA, FDR-adjusted p-value = 0.96 for both CD22E2low and all other patients comparisons) . These results demonstrate that CD22E12low status applies to a smaller fraction of B-ALL patients (14.9% vs. 24.1%, p = 0.16, taking into account eight patients (6%) who were both CD22E12low and CD22E2low) and does not show an apparent relationship to the more frequent CD22E2low status. 3.3. Presenting Features of CD22E12low B-ALL Patients We next sought to determine if the CD22E12low patient subset is characterized by an enrichment of high-risk prognostic markers within the confines of a relatively small sample size (n = 141). As shown in Table 1, the patient characteristics exhibited similar ages and gender/race/ethnicity distribution, and they did not show marked differences between CD22E12low patients and the remainder of the patient population (Table S1 and Table 1). The mean age was 8.2 +- 1.2 years (median = 7.6 years) for CD22E12low patients vs. 7.9 +- 0.5 years (median = 6.4 years) for other patients (p = 0.8). A total of 11 of 21 (52.4%) CD22E12low patients vs. 53 of 120 (44.2%) other patients were in the high-risk age category (age < 2 years or >=10 years) (p = 0.6, Table 1). There was no enrichment for adult patients (viz.: >18 years of age; 1/21 (4.8%) CD22E12low patients versus 4/120 (3.3%) others; p = 0.6). The mean WBC was 45.5 +- 13.1 x 109/L (median = 15.9 x 109/L) for CD22E12low patients and 76.8 +- 12.0 109/L (median = 33 x 109/L) for other patients (p = 0.2). A total of 11 of 21 (52.4%) CD22E12low patients vs. 79 of the remaining 120 patients (65.8%) had NCI high-risk ALL (Fisher's Exact, 2-tailed test, p = 0.3, Table 1). There was no enrichment for patients with higher WBC (viz.: WBC >= 20 x 109/L (10/21 (47.6%) vs. 73/120 (60.8%), p = 0.3), CNS2 or CNS3 category (5 of 21 CD22E12low patients (23.8%) versus 23 of 120 (19.2%) other patients, p = 0.6), poor-risk cytogenetics assessed by karyotyping (pseudodiploidy, hyperdiploidy, or hypodiploidy with structural chromosomal abnormalities (SCA) (i.e., 7 of 12 (58.3%) evaluable CD22E12low patients versus 71 of 94 (75.5%) evaluable other patients, p = 0.3). None of the evaluable CD22E12low patients were t(9;22)/BCR-ABL1+ or MLL-R/t(4;11)+. Three out of twenty (15%) evaluable CD22E12low patients were TCF3-PBX1+ compared to 11/112 (9.8%) evaluable other patients (p = 0.4). We noticed that none of the 20 evaluable CD22E12low patients had the favorable prognosis markers ETV6-RUNX1 or hyperdiploidy with trisomy 4 and 8. By comparison, among the remaining 112 evaluable other patients, 11 (9.8%) were ETV6-RUNX1+ (p = 0.2), and 10 (8.9%) had trisomy 4 and 10 (0/21 (0%) vs. 21/112 (18.8%), p = 0.042). Notably, there was no apparent evidence for intrinsic resistance to induction chemotherapy. There were only two induction failures in this group of patients; none of the 21 CD22E12low patients and 2 of the 119 other patients in the RNA-seq subset experienced an induction failure. At the end of the induction therapy, 57.1% of CD22E12low patients and 46.7% of the remaining patients had no measurable residual disease (MRD), as measured with 6-color flow cytometry (p = 0.5). The mean day 29 MRD values were 0.07 +- 0.03% for CD22E12low patients and 0.87 +- 0.35% for the remaining patients (p = 0.4). End-of-consolidation MRD data was available for only three CD22E12low patients, and they all were zero (Table 1). Within the NCI high-risk subset of 90 patients, only 3 of 52 patients (6%) with MRD > 0 and 8 of 38 patients (21%) with MRD = 0 were CD22E12low (Fisher's exact p-value = 0.048). 3.4. Gene Set Enrichment Analysis of Reactome Pathways in CD22E12low B-ALL Patients We used GSEA to examine the transcriptomes of primary leukemia cells from CD22E12low B-ALL patients for selective disruptions of reactome pathways that are selectively affected in murine B-ALL cells from CD22DE12-Tg mice . Notably, the expression of several genes represented in reactomes involved in transcription , mRNA processing/mRNA transport , translation , post-translational protein modification , signal transduction , and cell cycle were dysregulated in primary leukemia cells from CD22E12low patients. Table 2 compares the affected reactome pathways in CD22E12low human B-ALL cells vs. murine B-ALL cells originating from CD22DE12-Tg mice . The most significantly upregulated genes in primary leukemia cells from CD22E12low B-ALL patients, according to the affected reactome pathways they are represented in, exhibited fold-increase values over the expression values in primary leukemia cells from other patients ranging from 1.5 to 2.3 and included (i) CCNK, NELFA, GATAD2A, and NUDT21 (transcription); (ii) DDX20, HNRNPD, SMN1, and KHSRP (mRNA processing); (iii) SRRM1, SRSF3, RAE1, and POLDIP3 (mRNA transport); (iv) ETF1, EIF5, EIF4E, and EIF4H (translation); (v) EP300, CREBBP, UBE2G1, and RTF1 (post-translational protein modification); (vi), PPP2CA, SKP1, PSMC2, and NFKB1 (signal transduction); (vii) MAPRE1, DYNC1LJ1, CHMP4B, and FZR1 (cell cycle) . 3.5. Clinical Prognostic Significance of the Interpatient Heterogeneity in Selective Reduction of RNAseq-Based CD22 Exon 12 Expression Levels among B-ALL Patients We next evaluated the potential impact of reduced CD22 exon 12 expression on the treatment outcomes in B-ALL by comparing the outcomes of CD22E12low patients to the outcomes of the remaining patients. The median follow-up time was 963 days (range = 77-4175 days; interquartile range = 549-1948 days) for the 141 B-ALL patients with RNA-seq data. Among these patients, the median follow-up times were 867 days (range = 77-3830 days; interquartile range = 528-1220 days) for the 21 CD22E12low patients and 1017 days (range = 98-4175 days; interquartile range = 558-2426 days) for the remaining 120 patients. A total of 101 of 141 patients experienced a relapse after attaining remission. CD22E12low patients had a significantly higher incidence of relapse (19/21; 90.4%) than other patients (82/120 (68%) (Fisher's exact test, p = 0.039). The probability of relapse within five years was 90.5 +- 6.4% for CD22E12low subset and 69.2 +- 4.4% for other patients (p = 0.023) . Further, the 685-day median time to relapse (95% CI: 531-1129) in CD22E12low patients was significantly shorter than the median time to relapse in the remaining patients (median: 1012, 95% CI: 819-1191 days; log-rank chi-square = 5.19, p-value = 0.023) . CD22E12low patients had significantly worse LFS outcomes than other patients . The probability of surviving leukemia-free at 5-years was 9.5 +- 6.4% for the CD22E12low subset and 29.8 +- 4.3% for other patients (p = 0.039). The median LFS time for CD22E12low patients was 685 (95% CI: 531-1129) days, which was significantly shorter than the median LFS time of 958 (95% CI: 801-1178) days for other patients (log rank chi-square = 4.48, p-value = 0.034) . The OS outcome of CD22E12low patients was significantly worse than the OS outcome of other patients . The probability of being alive after five years was 19.0 +- 8.6% for the CD22E12low subset and 53.9 +- 4.6% for other patients (p = 0.004). The median OS time for CD22E12low patients was 1008 days (need 95% CI = 883-1715), which is significantly shorter than the median OS time of 2029 days (95% CI = 1456-NA) for the remaining patients (log-rank chi-square = 7.82, p-value = 0.005) . We next asked if CD22E12low status remained a poor prognostic indicator for LFS and OS in the 90-patient subset of NCI high-risk B-ALL patients. CD22E12low patients (n = 11) within the high-risk subset of patients had worse treatment outcomes than the remaining patients (n = 79) . CD22E12low high-risk B-ALL patients had a shorter time to relapse (median values: 625 days (95% CI = 520-NA) vs. 1083 days (95% CI = 881-NA); log-rank chi-square = 4.19, p-value = 0.04) , shorter LFS (median values: 625 days (95% CI = 520-NA) vs. 1040 days (95% CI = 863-NA); log rank chi square = 3.7, p-value = 0.05) , and shorter OS (median values: 1008 days (95% CI = 736-NA) vs. 2029 days (95% CI = 1413-NA); log-rank chi-square = 4.58, p-value = 0.03) than other high-risk B-ALL patients . The probability of high-risk B-ALL patients to be alive and leukemia-free after five years was 18.2 +- 11.6% for the CD22E12low subset and 46.4 +- 5.6% for other patients (p = 0.1). The probability of high-risk patients to be alive after five years was 18.2 +- 11.6% for the CD22E12low subset and 54.3 +- 5.7% for other patients (p = 0.025). We also examined the effects of CD22E12low status as an indicator of poor prognosis associated with a poor LFS as well as poor OS in univariate and multivariate Cox proportional hazards models. These models include as variables the following candidate poor prognostic characteristics for hazard ratio (HR) determinations: (i) CD22E12low status; (ii) age < 2 y or >= 10 y; (iii) male; (iv) poor risk classification based on molecular markers (BCR-ABL1+, MLL-R+, or TCF3-PBX1+); (v) WBC at diagnosis (as a linear covariate); and (vi) end-of-induction day 29 MRD burden > 0 (defined as MRD >= 0.001%). CD22E12low status was associated with an increased hazard ratio for shorter LFS in both univariate (HR = 1.7 +- 0.3, 95% CI: 1.0-2.8, p-value = 0.04) and multivariate models (HR = 1.8 +- 0.3, 95% CI: 1.1-3.0, p-value = 0.03) . Similarly, CD22E12low status was associated with an increased hazard ratio for shorter OS in both univariate (HR = 2.1 +- 0.3, 95% CI: 1.2-3.6, p-value = 0.006) and multivariate models (HR = 2.3 +- 0.3, 95% CI: 1.3-4.0, p-value = 0.004) . In the multivariate Cox model, the HR values for CD22E12low status (viz.: 1.8 for LFS and 2.3 for OS) were not as high as those associated with a poor-risk molecular marker profile (viz.: 4.0 for LFS and 3.3 for OS) but higher than those associated with any other poor risk variable analyzed. Notably, the comparison of the LFS and OS outcomes for the subset of 90 evaluable high-risk B-ALL patients also showed a significant increase in HR for patients with CD22E12low status (n = 11) compared to other patients (n = 79) . In the multivariate Cox regression model, CD22E12low status was found to be a significant and independent predictor of poor LFS outcomes (HR = 3.1 +- 0.4, p-value = 0.01) as well as poor OS outcomes (4.0 +- 0.5, p-value = 0.003). The HR values for CD22E12low status (viz.: 3.1 for LFS and 4.0 for OS) were higher than those associated with any other poor risk variable included in the multivariate Cox model. 4. Discussion We had originally hypothesized that CD22DE12 might act as an oncogenic protein by competitively binding to the cis ligands of CD22 and preventing residual wildtype CD22 from in cis ligand binding, thereby contributing to the increased proliferation and defective apoptosis of leukemic B-cell precursors from B-ALL patients caused by the CD22DE12-associated impaired regulatory function of CD22 . Expression of a truncated CD22DE12 protein was indeed associated with aggressive in vivo growth of primary B-ALL cells in immunodeficient NOD/SCID mice . Lentiviral-based overexpression of truncated CD22DE12 protein but not full-length CD22 in B-ALL cells resulted in a marked increase in the sizes of blast colonies in vitro, consistent with increased self-renewal and clonogenicity . Further, CD22DE12 depletion via CD22DE12-specific small interfering RNA (siRNA) and their liposomal formulations inhibited the in vitro and in vivo clonogenicity of B-ALL cells . These experimental findings collectively support our hypothesis regarding the oncogenic function of CD22DE12 protein and demonstrate that CD22DE12 expression is associated with the selective survival and growth advantage of B-ALL cells . Our initial studies demonstrated that CD22DE12, with the selective reduction of CD22E12 levels, is a characteristic splicing defect in primary leukemia cells from newly diagnosed high-risk and relapsed B-ALL patients . We now report for the first time that in newly diagnosed B-ALL, CD22E12low patients with very low CD22E12 levels, who represent 14.9% of the patient population, had significantly worse LFS and OS outcomes than other patients. Our study thereby fills a significant gap in our understanding of the clinical significance of CD22DE12 in B-ALL. The cumulative proportion of patients in the analyzed population of 141 newly diagnosed B-ALL patients who survived after five years was 19.0 +- 8.6% for the CD22E12low subset (n = 21) and 53.4 +- 4.6% for the remaining 120 patients (p = 0.004). The median OS time for CD22E12low patients was 1008 days, which is significantly shorter than the median OS time of 2029 days for the remaining patients (log-rank chi-square = 7.8, p-value = 0.005). Likewise, in the 90-patient subset of NCI high-risk B-ALL patients, CD22E12low patients (n = 11) had significantly worse treatment outcomes than the remaining 79 patients (n = 79). Importantly, CD22E12low status was associated with a significantly increased hazard ratio for shorter PFS and OS in both univariate and multivariate models. In the multivariate Cox regression model for the NCI high-risk subset that also included patient age, sex, WBC at presentation, end-of-induction MRD burden, and poor-risk cytogenetics/FISH markers (BCR-ABL1+, MLL-R+ or TCF3-PBX1+) as covariables, we found CD22E12low status to be a significant and independent predictor of poor LFS outcomes (HR = 3.1 +- 0.4, p-value = 0.01) as well as poor OS outcomes (HR = 4.0 +- 0.5, p-value = 0.003). These new results significantly extend a previous study that implicated CD22DE12 as a driver lesion, contributing to the aggressive biology of relapsed pediatric B-ALL . CD2E12low status at presentation may have clinical utility as a poor prognostic biomarker and may help guide the early allocation of risk-adjusted, patient-tailored treatment regimens as well as refine risk classification in high-risk B-ALL. Forced overexpression of the mutant CD22DE12 in transgenic mice caused fatal B-ALL, demonstrating that CD22DE12 alone may be sufficient as a driver lesion for the leukemic transformation and aggressive in vivo growth of B-cell precursors . Notably, genes related to transcriptional, translational, signal transduction-related, and cell cycle-related reactome pathways were significantly upregulated in B-ALL cells from CD22DE12 Tg mice . We previously reported that the CD22DE12 signature transcriptome encodes a phosphoproteome that is differentially overexpressed in CD22DE12-Tg B-ALL cells, confirming that CD22DE12 corrupts the regulation of multiple signaling networks. Several anti-apoptotic proteins such as mTOR, AKT, NFkB, transcription factors implicated in oncogenesis, and serine kinase signaling pathway proteins such as MAPK, PKC, and PKD were among the most significantly overexpressed members of the CD22DE12 signature phosphoproteome . In the current study, we used GSEA in gene sets obtained from the Bioconductor Reactome Database to examine the transcriptomes of primary leukemia cells from CD22E12low B-ALL patients for selective disruptions of reactome pathways we had previously discovered to be selectively dysregulated in murine B-ALL cells from CD22DE12-Tg mice . Notably, the expression of several genes represented in reactomes involved in transcription, mRNA processing/mRNA transport, translation, post-translational protein modification, signal transduction, and cell cycle were selectively amplified in primary leukemia cells from CD22E12low patients. These findings demonstrate that the regulation of gene expression is corrupted in CD22E12low B-ALL cells across multiple reactomes, which is reminiscent of the CD22DE12-associated transcriptome changes in transgenic mice . We propose that the observed differences in gene expression profiles of CD22E12low vs. other B-ALL patients may contribute to the seemingly more aggressive biology of the CD22E12low subset. RNAi therapeutics targeting CD22DE12 may disrupt the signaling networks that promote the proliferation and survival of CD22DE12+ B-ALL cells . We previously reported preclinical data regarding the in vitro and in vivo anti-leukemic activity of nanoformulations of CD22DE12-specific siRNA as an innovative new treatment platform for CD22DE12+ B-ALL . Further development and optimization of this experimental platform may have clinical potential. The clinical development of personalized nanomedicines against the CD22DE12 poor-risk B-ALL might address an unmet challenge in treating B-ALL by improving the landscape of effective treatment modalities. The observed poor prognosis of newly diagnosed B-ALL patients with CD22DE12-associated CD22E12low status, as reported here, supports the notion that further exploration of the clinical potential of CD22DE12-targeting RNAi therapeutics is warranted. Black et al. reported mutations in splicing factor genes, including the genes for hnRNPs, as a possible mechanism for aberrant splicing in B-ALL . Pathogenic intronic mutations were implicated in aberrant splicing and human disease . In patients with CD22DE12, we previously reported multiple homozygous mutations within a 132-bp mutational hotspot segment of the intronic sequence between exons 12 and 13, some of which involved locations of known single nucleotide polymorphisms (SNP) . Within this intronic segment, we identified multiple accessible potential binding sites for the heterogenous nuclear ribonucleoprotein (hnRNP) family of splicing factors that act as global regulators of alternative splicing . The documented mutations within the hot spot region were associated with secondary structure conformation and folding patterns that affected the target motifs for hnRNP-E2/PCBP, hnRNP-I/PTB, and hnRNP-L as well as the surrounding structure of the predicted pre-mRNA . Therefore, we proposed that these mutations might contribute to aberrant pre-mRNA splicing by affecting the recognition of the 5' splice site of CD22E12 via the splicing factors and preventing an orderly assembly of the splicesome assembly . In addition to CD22DE12, CD22E2 skipping by aberrant splicing also occurs in B-ALL, which results in very low CD22E2 mRNA levels and is associated with inherent resistance to CD22-directed immunotherapies such as inotuzumab, ozogamicin, and CAR-T cells due to reduced expression of the target CD22 protein. As both events are caused by aberrant splicing, we evaluated CD22E2 mRNA levels in CD22E12low patients in an effort to determine if CD22E12low and CD22E2low subsets overlap in the studied B-ALL patient population. Our findings indicate that the CD22E12low status applies to a smaller fraction of B-ALL patients and does not show an apparent relationship to the more common CD22E2low status. Therefore, CD22-targeting immunotherapeutics remain a viable treatment modality for a significant portion of CD22E12low patients without evidence of CD22E2 skipping and/or a marked reduction of CD22 expression levels. The present study has a significant limitation owing to a patient selection bias caused by the availability of RNA-seq data for only 12.5% of patients in the TARGET database who had worse leukemia-free survival and overall survival outcomes than the total patient population in the database. A number of statistically significant differences in patient characteristics suggests that the 141-patient RNA-seq subset was likely enriched for cases with a biologically more aggressive disease, including a higher mean WBC at diagnosis in the RNA-seq subset (72.2 +- 10.4 63.7 +- 3.2, p = 0.046), a higher portion of patients with CNS 2 or CNS 3 at diagnosis in the RNA-seq subset (19.9% vs. 11.6%, p = 0.003), a higher incidence of CNS relapse in the RNA-seq subset (10.6% vs. 5.1%, p = 0.003, odds ratio: 2.6), a higher portion of patients with MRD > 0 on day 29 in the RNA-seq subset (51.8 vs. 41.8%, p = 0.014), and a higher portion of patients with structural chromosomal abnormalities in the RNA-seq subset (73.6% vs. 64.4%, p = 0.04, odds ratio: 1.6) (Table S9). Although these differences might have contributed to poor survival outcomes, it was not possible to decipher the exact reasons of the worse-than-expected survival outcomes in the analysis population, as patient-specific treatment information was not archived in the TARGET database. Another limitation of the study relates to the fact that some of the prognostically relevant data, such as the MRD values at the end of consolidation, were not collected for all patients. Although the characteristics of the CD22E12low patients within the RNA-seq subset were very similar to those of the remainder of patients in the RNA-seq subset, which allowed an accurate comparison of the outcomes of the CD22E12low and CD22E12high patients (Table 1, Table S1), a hypothesis-testing prospective validation study will be necessary to confirm the poor prognostic effect of CD22E12low status, preferably with RT-qPCR and RNA-seq in a larger B-ALL patient population treated according to a contemporary standard of care regimen. 5. Conclusions Our study demonstrates that newly diagnosed B-ALL patients with very low levels of residual wildtype CD22 ("CD22E12low"), as measured by RNAseq-based CD22E12 mRNA levels, have significantly worse LFS as well as OS than other B-ALL patients. CD22E12low status was identified as a poor prognostic indicator in both univariate and multivariate Cox proportional hazards models. CD22E12low status at presentation shows clinical potential as a poor prognostic biomarker that may guide the early allocation of risk-adjusted, patient-tailored treatment regimens and refine risk classification in high-risk B-ALL. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Identification of B-ALL patients with low CD22 Exon 2 (CD22E2) expression, Figure S2: Newly diagnosed B-ALL patients exhibited similar expression of CD22 exon 2 in CD22E12low and all other patients, Figure S3: Significantly overexpressed transcription pathway genes in CD22E12low B-ALL patients, Figure S4: Significantly overexpressed mRNA processing and transport pathway group of genes in CD22E12low B-ALL patients, Figure S5: Significantly overexpressed translation and post-translational protein modification pathway genes in CD22E12low B-ALL patients, Figure S6: Significantly overexpressed signal transduction pathway genes in CD22E12low B-ALL patients, Figure S7: Significantly overexpressed cell cycle pathway group of genes in CD22E12low B-ALL patients, Figure S8: Unfavorable impact of CD22DE12-associated selective reduction of CD22E12 expression on treatment outcomes in newly diagnosed high-risk B-ALL, Figure S9: CD22E12low status in high-risk B-ALL as a poor prognostic indicator in univariate and multivariate Cox proportional hazards models comparing LFS and OS outcomes; Table S1: Patient characteristics, Table S2: Dysregulated expression of transcription pathway group of genes in CD22E12low B-ALL patients, Table S3: Expression of mRNA processing pathway group of genes in CD22E12low B-ALL patients, Table S4: Expression of mRNA_transport pathway group of genes in CD22E12low B-ALL patients, Table S5: Expression of translation pathway group of genes in CD22E12low B-ALL patients, Table S6: Expression of post-translational protein modification pathway group of genes in CD22E12low B-ALL patients, Table S7: Expression of signal transduction pathway genes in CD22E12low B-ALL patients, Table S8: Expression of cell cycle pathway genes in CD22E12low B-ALL patients; Table S9: Comparison of the clinical features of the 141-patient RNAseq subset with those for the total TARGET B-ALL patient population. Click here for additional data file. Author Contributions F.M.U. conceived, designed, and directed the project, directed the data compilation and analysis, and prepared the initial draft of the manuscript. F.M.U. and S.Q. analyzed the data. S.Q. performed statistical and bioinformatic analyses. Each author reviewed and revised the manuscript and provided final approval for submission of the final version. No medical writers were involved. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement De-identified cells from B-ALL patients were used in RT-PCR assays in this study. The secondary use of de-identified leukemia cells for subsequent laboratory studies did not meet the definition of human subject research per 45 CFR 46.102 (d and f) because it did not include identifiable private information, and it was approved by the IRB (CCI) at the Children's Hospital Los Angeles (CHLA) (Protocol #' CCI-09-00304 approved on 16 December 2009 and CCI-10-00141 approved on 27 July2010), Human Subject Assurance Number: FWA0001914. Informed Consent Statement Not applicable. Data Availability Statement We used the publicly available archived gene expression profiling datasets GSE13159, GSE11877, and GSE13351, which were generated in the GeneChip Human Genome U133 Plus 2.0 Array platform (ThermoFischer Scientific, Waltham, MA, USA), to examine the relative expression levels of CD22 exons 11-14 in primary leukemia cells from 421 newly diagnosed B-ALL patients. We downloaded the RNAseq data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program accessed on 28 January 2022). The data files with exon-level quantification for the CD22 exons 11, 12, 13, and 14 were manually downloaded from the TARGET repository. The clinical outcome data were retrieved from the TARGET clinical annotation files TARGET_ALL_ClinicalData_Phase_II_Discovery_20211118.xlsx and TARGET_ALL_ClinicalData_Phase_II_Validation_20211118.xlsx. Our previously reported archived datasets on gene expression profiles (GSE58874 and GSE58872) and phosphoproteomes (GSE58873 and GSE58874) of B-ALL cells from CD22DE12-Tg mice were used for comparison in our efforts to identify the dysregulated reactome pathways in CD22E12low B-ALL patients. The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author. Conflicts of Interest Author F.M.U. is employed by Ares Pharmaceuticals, and author S.Q. serves as a consultant for Ares Pharmaceuticals. All authors declare no other competing interests. Figure 1 CD22DE12 in pediatric B-ALL. (A,B) Reduced expression levels of CD22E12 in primary leukemia cells from B-ALL patients. (A) Distribution of CD22E12 mRNA expression in primary leukemia cells from B-ALL patients (GSE13159, GSE11877, and GSE13351) using the density graph of the CD22E12 index values fitted by applying a Gaussian smoothing kernel density estimation for B-ALL samples (mean = -0.288 +- 0.03 (median = -0.287; interquartile range = -0.67-0.08; range = -1.921-1.917; n = 421) (ggplot2_3.3.5 R package). The CD22E12 index values were calculated by subtracting the mean expression values obtained with the six probes for CD22E11, CD22E13, and CD22E14 in the 217422_s_at probe set from the mean expression values obtained using the three CD22E12 probes. (B-D) Detection of CD22DE12 mRNA in primary leukemia cells from 24 pediatric B-ALL patients using quantitative RT-PCR. The PCR primer pair was designed to amplify a 113-bp fragment spanning from exon 11 to exon 13 of the human CD22 cDNA, as described in Materials and Methods. Depicted in (B,C) are the Ct values for CD22DE12 and b-actin (as the mRNA of a control house-keeping gene). Depicted in (D) are the DCt values (CD22DE12 expression normalized for the expression level of b-actin). The results in (B-D) are visualized as superimposed box plots and kernel density plots. The grey boxes depict, as horizontal lines within the box, the median values for CD22DE12 Ct (in (C)), b-Actin Ct (in (C)), and CD22DE12 DCt (in (D)); the boxes represent the 75th and 25th quantiles, and the whiskers represent the 3rd quartile + 1.5x(interquartile range) and 1st quartile--1.5x(interquartile range) of the values. The colored density plots (violin plots with mirrored density on the vertical axis) visualize the distribution of the individual Ct and DCt values, where increased broadness of the plot indicates an increase in the density of Ct and DCt values. Figure 2 Identification of newly diagnosed B-ALL patients who exhibited CD22DE12-associated selective reductions of CD22E12 relative to the expression of CD22 exons 11 to 14. Data files reporting the "reads per kilobase million (RPKM)" metric for CD22 gene exon-level quantification of mRNA for CD22 exons 11-14 were downloaded from the TARGET phase 2 project accessed on 9 July 2022). The expression level of each exon was mean-centered to the average RPKM values across exons 11 to 14 for each of the 141 B-ALL patients to obtain the "normalized" RPKM values. A subset of 21 patients with CD22DE12-associated selective reductions of CD22E12 (CD22E12low) were identified via examination of the RPKM values for CD22E12 and the adjacent CD22 exons 11 (CD22E11), 13 (CD22E13), and 14 (CD22E14). (A) The cluster figure depicts the average normalized RPKM values for CD22 exons 11, 13, and 14 (top row) and 12 (bottom row) for each patient (across columns). Heat map: Blue represents underexpression, and red represents overexpression. The clustering algorithm (Euclidean distance and Wards linkage) identified 21 patients with low levels of CD22 exon 12 expression relative to exons 11, 13, and 14 (black bar for CD22E12low patients). (B) Depicted are histograms of the distribution profile of normalized RPKM values for CD22E12 in (i) CD22E12low patients (n = 21) as blue lines and in (ii) other patients (n = 120) as red lines. The density plots under the histograms shown as blue (CD22E12low patients) or red (all other patients) bars represent the normalized RPKM values. For CD22E12low patients, the normalized RPKM values were <0.8. The mean value for CD22E12 expression level (in normalized RPKM) for CD22E12low patients was 0.714 +- 0.014 (median = 0.728; range = 0.572-0.785), which was significantly lower than the mean CD22E12 expression level of 0.934 +- 0.006 (median = 0.935; range = 0.805-1.133) for the remaining 120 patients (two-way ANOVA, linear contrast, p-value < 10-15). (C) The average (mean +- SEM, normalized RPKM) expression levels for CD22E11, CD22E12, CD22E13, and CD22E14 depicted in bar charts for the CD22E12low patient subset (n = 21) illustrate the selective reduction of CD22E12 (Exon12) relative to exons 11, 13, and 14. CD22E12 expression levels for CD22E12low patients (mean = 0.714 +- 0.014; median = 0.728; range = 0.572-0.785) were significantly lower than the expression levels for CD22E11 (mean = 1.101 +- 0.018; median = 1.109; range = 0.839-1.224; p-value < 10-15), CD22E13 (mean = 1.073 +- 0.011; median = 1.076; range = 0.961-1.151; p-value < 10-15), and CD22E14 (mean = 1.112 +- 0.015; median = 1.103; range = 1.026-1.279; p-value < 10-15). Figure 3 Most significantly overexpressed genes in CD22E12low patients for reactomes representing transcription, translation, signal transduction, and cell cycle. We determined the differential expression of genes comparing CD22E12low patients (n = 21) with all other patients (n = 120) using DESeq2 package (DESeq2_1.34.0 implemented in R). The cluster figures display the variance-stabilized, normalized log2 expression values in CD22E12low B-ALL patients mean-centered to the expression levels in all other patients (blue represents underexpression and red represents overexpression in CD22E12low patients). See Supplemental Figures S3-S7 and Tables S2 -S8 for more details regarding dysregulated gene sets, including up and downregulated genes. Depicted in (A-G) are, for each group of the seven reactome gene sets, the four genes with the highest values for Wald Statistics comparing CD22E12low versus all other patients. Fold Increase values were calculated from the baseline mean of counts determined using the DESeq2 algorithm following removal of low-expression genes (mean <= 10 counts); median count for the depicted 28 genes was 14,492 (range = 546 - 60391; interquartile range = 5322 -24229 counts). Figure 4 Unfavorable impact of CD22DE12-associated selective reduction of CD22E12 expression on treatment outcomes in newly diagnosed B-ALL. Treatment outcomes were compared using Kaplan-Meier analysis for the CD22E12low subset (n = 21) vs. other patients (n = 120). See Table 1 for patient characteristics. (A) Relapse. (B) LFS. (C) OS. CD22E12low patients exhibited a higher probability of relapse, shorter time to relapse, worse LFS with shorter times to first event (relapse or death), and worse OS. See text for discussion of results. Figure 5 CD22E12low status in B-ALL as a poor prognostic indicator in univariate and multivariate Cox proportional hazards models comparing LFS and OS outcomes. We examined the effects of CD22E12low status as an indicator of poor prognostic prognosis that is associated with worse LFS and OS outcomes in univariate and multivariate Cox proportional hazards models. These models include as variables the following candidate poor prognostic characteristics for hazard ratio (HR) determinations: (i) CD22E12low status; (ii) age < 2 y or >=10 y; (iii) male; (iv) poor-risk classification based on molecular markers (BCR-ABL1+, MLL-R+, or TCF3-PBX1+); (v) WBC x 109/L at diagnosis as a linear covariate; and (vi) end-of-induction day 29 MRD burden > 0 (i.e., MRD >= 0.001%). (A) Depicted are the Forest plots for LFS along with the corresponding HRs and p-values for each covariate in the multivariate Cox proportional hazards model. * p < 0.05; *** p < 0.001. (B) The HR for LFS and corresponding p-values are provided for each variable in both the univariate and multivariate models. CD22E12low status (HR = 1.7 +- 0.3, p-value = 0.036) and having a poor prognostic molecular marker (HR = 3.0 +- 0.2, p-value = 8 x 10-6) were significant predictors of poor LFS in the univariate model. Both CD22E12low status (HR = 1.8 +- 0.3, p-value = 0.03) and having a poor prognostic molecular marker (HR = 4 +- 0.3, p-value = 2 x 10-6) also exhibited statistically significant increases in HR for LFS in the multivariate model. (C) Depicted are the Forest plots for OS along with the corresponding HRs and p-values for each covariate in the multivariate Cox proportional hazards model. * p < 0.05; *** p < 0.001 (D) The HR for OS and corresponding p-values are provided for each variable in both the univariate and multivariate models. CD22E12low status (HR = 2.1 +- 0.3, p-value = 0.006) as well as having a poor prognostic molecular marker (HR = 2.6 +- 0.3, p-value = 4.2 x 10-4) were identified as predictors of poor OS in the univariate model. Both variables were also identified as significant and independent predictors of poor OS outcome in the multivariate model (HR for CD22E12low status = 2.3 +- 0.3, p-value = 0.004; HR for having a poor prognostic molecular marker = 3.3 +- 0.3, p-value = 2.2 x 10-4). cancers-15-01599-t001_Table 1 Table 1 Patient Characteristics According to CD22E12low Status. Variable CD22E12low (N = 21) All Others (N = 120) p-Value Mean/Median(Range) orN (% Evaluable) Mean/Median(Range) or N (% Evaluable) Mann-Whitney U Test or Fisher's Exact Age (yrs) Mean +- SEM/Median (Range) 8.2 +- 1.2 7.6 (1.4-18.1) 7.9 +- 0.5 6.4 (1.2-30) 0.8 WBC (x109/L) Mean +- SEM/Median (Range) 45.5 +- 13.1 15.9 (1.3-214.5) 76.8 +- 12 33 (1.1-1149) 0.2 MRD at Day 29 Mean +- SEM/Median (Range) 0.07 +- 0.03 0 (0-0.57) 0.9 +- 0.4 0 (0-26) 0.4 MRD at End of Consolidation Mean +- SEM/Median (Range) 0 +- 0 (N = 3) 0 (0-0) 1.6 +- 1.4 (N = 23) 0 (0-31.5) 0.3 Age category Adult (>=18 yrs) 1/21 (4.8%) 4/120 (3.3%) 0.6 CNS Status at Diagnosis CNS 2 + CNS 3 Induction Failure 5/21 0/21 (23.8%) (0%) 23/120 2/119 (19.2%) (1.7%) 0.6 1.0 NCI Risk High Risk 11/21 (52.4%) 79/120 (65.8%) 0.3 Age risk Poor (Age <2 yrs or >=10 years) 11/21 (52.4%) 53/120 (44.2%) 0.6 WBC category >=20 x 109/L MRD at Day 8 MRD > 0 10/21 7/7 (47.6%) (100%) 73/120 33/33 (60.8%) (100%) 0.3 1.0 MRD at Day 29 MRD > 0 MRD at End of Consolidation MRD > 0 9/21 0/3 (42.9%) (0%) 64/120 8/23 (53.3%) (34.8%) 0.5 0.5 Cytogenetics (N = 106) Pseudodiploid 5/12 (41.7%) 38/94 (40.4%) 1.0 Pseudodiploid + Hypodiploid or Hyperdiploid with SCA 7/12 (58.3%) 71/94 (75.5%) 0.3 Molecular Markers/FISH (N = 132) BCR-ABL1 0/20 (0%) 5/112 (4.5%) 1.0 MLL/KMT2A rearranged 0/20 (0%) 4/112 (3.6%) 1.0 TCF3-PBX1 3/20 (15%) 11/112 (9.8%) 0.4 Hyperdiploid with Trisomy of chromosomes 4 and 10 0/20 (0%) 10/112 (8.9%) 0.4 ETV6-RUNX1 0/20 (0%) 11/112 (9.8%) 0.2 ETV6-RUNX1 + Trisomy of chromosomes 4 and 10 0/20 (0%) 21/112 (18.8%) 0.04 cancers-15-01599-t002_Table 2 Table 2 Significantly Affected Reactome Pathways in CD22E12low B-ALL and CD22DE12-Tg mice. Reactome Pathway Enrichment Score in CD22E12low B-ALL Enrichment Score in CD22DE12-Tg Mice NES p-Value NES p-Value Reactomes Involved in Transcription mRNA 3'-end processing 2.4 2.8 x 10-5 2.4 1.3 x 10-5 RNA polymerase II transcription termination 2.3 2.8 x 10-5 2.5 1.3 x 10-5 Transport of mature mRNA derived from an intronless transcript 2.1 2.7 x 10-5 2.4 1.4 x 10-5 RNA polymerase II pretranscription events 1.8 4.7 x 10-4 2.6 1.2 x 10-5 RNA polymerase II transcription elongation 1.7 1.6 x 10-3 2.4 1.3 x 10-5 Transcriptional regulation by small RNAs 1.5 9.9 x 10-3 2.4 1.3 x 10-5 Positive epigenetic regulation of rRNA expression 1.5 1.9 x 10-2 2.0 1.3 x 10-5 Reactomes Involved in mRNA Processing Regulation of mRNA stability by proteins that bind AU-rich elements 1.8 2.4 x 0-4 2.5 1.2 x 10-5 mRNA splicing--minor pathway 1.6 1.3 x 10-2 2.3 1.3 x 10-5 tRNA processing in the nucleus 1.5 2.3 x 10-2 2.5 1.3 x 10-5 Metabolism of non-coding RNA 1.5 3.0 x 10-2 2.6 1.3 x 10-5 Reactomes Involved in mRNA Transport Transport of mature transcript to cytoplasm 2.6 3.0 x 10-5 2.6 1.2 x 10-5 Transport of mature mRNA derived from an intron-containing transcript 2.5 2.9 x 10-5 2.6 1.3 x 10-5 Transport of mature mRNAs' intronless transcripts 2.2 2.7 x 10-5 2.4 1.3 x 10-5 Reactomes Involved in Translation Formation of a pool of free 40S subunits 3.0 3.1 x 10-5 2.8 1.2 x 10-5 Eukaryotic translation elongation 3.0 3.0 x 10-5 2.8 1.2 x 10-5 Peptide chain elongation 2.9 3.0 x 10-5 2.7 1.2 x 10-5 Eukaryotic translation termination 2.6 3.0 x 10-5 2.7 1.2 x 10-5 Ribosomal scanning and start codon recognition 2.6 2.8 x 10-5 2.6 1.3 x 10-5 Translation initiation complex formation 2.6 2.8 x 10-5 2.6 1.3 x 10-5 Activation of the mRNA upon binding of the cap-binding complex and eIFs and subsequent binding to 43S 2.4 2.8 x 10-5 2.6 1.3 x 10-5 Formation of the ternary complex and, subsequently, the 43S complex 2.4 2.7 x 10-5 2.5 1.3 x 10-5 Reactomes Involved in Post-Translational Protein Modification SUMOylation of RNA binding proteins 2.2 2.7 x 10-5 2.4 1.3 x 10-5 Synthesis of active ubiquitin: roles of E1/E2 enzymes 2.2 2.5 x 10-5 2.0 1.8 x 10-4 SUMOylation of SUMOylation proteins 2.1 7.7 x 10-5 2.3 1.4 x 10-5 SUMOylation of DNA replication proteins 2.0 1.1 x 10-4 2.4 1.3 x 10-5 SUMOylation of ubiquitinylation proteins 2.0 2.9 x 10-4 2.3 1.4 x 10-5 Protein ubiquitination 2.0 8.6 x 10-5 2.3 1.3 x 10-5 SUMOylation of transcription cofactors 1.9 3.2 x 10-4 1.9 7.9 x 10-5 SUMOylation of chromatin organization proteins 1.8 1.1 x 10-3 2.3 1.3 x 10-5 SUMOylation of DNA damage response and repair proteins 1.6 7.1 x 10-3 2.4 1.2 x 10-5 Reactomes Involved in Signal Transduction RAF activation 2.2 2.6 x 10-5 1.7 8.7 x 10-3 MAP kinase activation 1.9 2.5 x 10-4 1.5 1.5 x 10-2 RHOBTB2 GTPase cycle 1.9 2.1 x 10-3 1.8 2.7 x 10-3 Regulation of RAS by GAPs 1.9 2.6 x 10-4 2.0 1.2 x 10-5 MAPK6/MAPK4 signaling 1.8 4.5 x 10-4 2.1 1.2 x 10-5 Reactomes Involved in Cell Cycle Pathway Postmitotic nuclear pore complex (NPC) reformation 1.9 1.5 x 10-3 2.1 4.2 x 10-5 Nuclear envelope (NE) reassembly 1.8 9.7 x 10-4 2.2 1.2 x 10-5 Mitotic telophase/cytokinesis 1.8 1.2 x 10-2 1.9 1.3 x 10-5 Regulation of apoptosis 1.7 3.8 x 10-3 2.2 1.3 x 10-5 Establishment of sister chromatid cohesion 1.7 2.4 x 10-2 1.9 1.3 x 10-3 Nuclear pore complex (NPC) disassembly 1.7 7.9 x 10-3 2.3 1.4 x 10-5 Nuclear envelope breakdown 1.6 1.3 x 10-2 2.3 1.3 x 10-5 Amplification of signal from unattached kinetochores via a MAD2 inhibitory signal 1.5 1.3 x 10-2 2.7 1.2 x 10-5 Amplification of signal from the kinetochores 1.5 1.3 x 10-2 2.7 1.2 x 10-5 APC/C-mediated degradation of cell cycle proteins 1.5 1.6 x 10-2 2.4 1.2 x 10-5 Regulation of mitotic cell cycle 1.5 1.6 x 10-2 2.4 1.2 x 10-5 Enrichment scores are presented for each of the reactome gene sets selectively dysregulated in B-ALL cells from CD22DE12-Tg mice (in comparison to B-ALL cells from Em-MYC Tg and BCR-ABL Tg mice) and primary leukemia cells from CD22E12low patients (in comparison to primary leukemia cells from other B-ALL patients). The non-parametric GSEA enrichment scores yielded significantly overexpressed reactomes, and Wald statistics were utilized to identify overexpressed genes. See Figure 3, Figures S3-S7 and Tables S2-S8 for details. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000518 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050993 foods-12-00993 Article Multiple Organic Contaminants Determination Including Multiclass of Pesticides, Polychlorinated Biphenyls, and Brominated Flame Retardants in Portuguese Kiwano Fruits by Gas Chromatography Fernandes Virginia Cruz *+ Podlasiak Martyna + Vieira Elsa F. Rodrigues Francisca Grosso Clara Moreira Manuela M. Delerue-Matos Cristina Lu Xiaonan Academic Editor Hu Yaxi Academic Editor Zhang Guowen Academic Editor REQUIMTE/LAQV, Instituto Superior de Engenharia do Porto, Instituto Politecnico do Porto, Rua Dr. Antonio Bernardino de Almeida 431, 4249-015 Porto, Portugal * Correspondence: [email protected] + These authors contributed equally to this work. 26 2 2023 3 2023 12 5 99310 1 2023 20 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Global production of exotic fruits has been growing steadily over the past decade and expanded beyond the originating countries. The consumption of exotic and new fruits, such as kiwano, has increased due to their beneficial properties for human health. However, these fruits are scarcely studied in terms of chemical safety. As there are no studies on the presence of multiple contaminants in kiwano, an optimized analytical method based on the QuEChERS for the evaluation of 30 multiple contaminants (18 pesticides, 5 polychlorinated biphenyls (PCB), 7 brominated flame retardants) was developed and validated. Under the optimal conditions, satisfactory extraction efficiency was obtained with recoveries ranging from 90% to 122%, excellent sensitivity, with a quantification limit in the range of 0.6 to 7.4 mg kg-1, and good linearity ranging from 0.991 to 0.999. The relative standard deviation for precision studies was less than 15%. The assessment of the matrix effects showed enhancement for all the target compounds. The developed method was validated by analyzing samples collected from Douro Region. PCB 101 was found in trace concentration (5.1 mg kg-1). The study highlights the relevance of including other organic contaminants in monitoring studies in food samples in addition to pesticides. pesticides environmental contaminants QuEChERS gas chromatography kiwano Fundacao para a Ciencia e TecnologiaUIDB/50006/2020 UIDP/50006/2020 LA/P/0008/2020 Fundacao para a Ciencia e TecnologiaSFRH/BPD/109153/2015 CEECIND/03436/2020 CEEC-IND/03988/2018 CEECIND/01886/2020 CEECIND/02702/2017 This work received financial support from national funds (FCT/MCTES, Fundacao para a Ciencia e Tecnologia and Ministerio da Ciencia, Tecnologia e Ensino Superior) through projects UIDB/50006/2020, UIDP/50006/2020, and LA/P/0008/2020. Virginia Cruz Fernandes thanks FCT/MCTES and ESF (European Social Fund) through NORTE 2020 (Programa Operacional Regiao Norte) for funding her Post doc grant ref. SFRH/BPD/109153/2015. Clara Grosso (CEECIND/03436/2020), Elsa F. Vieira (CEEC-IND/03988/2018), Francisca Rodrigues (CEECIND/01886/2020) and Manuela M. Moreira (CEECIND/02702/2017) thank FCT (Fundacao para a Ciencia e Tecnologia) for funding through the Scientific Employment Stimulus-Individual Call. pmc1. Introduction The consumers' interest in new and exotic fruits has intensified, mainly due to the growing knowledge regarding their bioactive composition and biological activities with pro-healthy effects. Kiwano (Cucumis metuliferus E. Mey), belonging to the Cucurbitaceae family, is a plant naturally occurring in South Africa, Nigeria, Namibia, Botswana, and Southern Sahara, being also sporadically found in Yemen . In the last years, its exportation has grown in countries such as Kenya, New Zealand, France, and Portugal . The ripe kiwano fruit is characterized by an orange skin with many blunt thorns on its surface and green, jelly flesh inside . Kiwano fruit has low levels of carbohydrates and calories but high contents of water, minerals including magnesium, calcium, potassium, iron, phosphorus, zinc, copper, and complex B vitamins, vitamin C, and b-carotene . Some pharmacological properties of this exotic fruit have been recently revised by Vieira et al. , including anticardiovascular, antidiabetic, antiulcer, antioxidant, anti-inflammatory, antimalarial, and antiviral activities. Due to these beneficial properties, its production, exportation, and consumption have increased, leading to intensive cultivation. As such, these particular fruits contribute directly and importantly to food security and nutrition in most producing zones, however, some food safety issues are still little explored in these matrices. There are several ways of improving plant cultivation. One of them is the use of plant protection products, commonly known as pesticides, which may have a chemical source as well as a natural origin . Pesticides are used to protect crops from the harmful activity of other plants, microorganisms, insects, or even animals . Although higher yields of cultivation can be obtained by using pesticides , they represent a threat to animals and human health and lives. Other toxic chemical substances that are present in the environment due to man-made activity derived from different sources (e.g., plastics, industrial, etc.), are referred to as environmental pollutants (e.g., polychlorinated biphenyls (PCB), polybrominated diphenyl ethers (PBDE), polycyclic aromatic hydrocarbons (PAH), heavy metals). Many of these compounds can be resistant to environmental degradation and accumulate in soil and food . Further, prolonged exposure to these agricultural chemicals, particularly by contaminated food consumption, may lead to chronic disorders, such as cancer, hormone disruption, diabetes, asthma, or infertility and neurodegenerative disorders . As an example of the pesticide family, organophosphorus pesticides (OPP) are highly toxic chemical compounds used as insecticides for crop protection . These chemicals are neurotoxic, as they inhibit acetylcholinesterase (AChE), which causes malfunctions in muscular activity leading to seizures, paralysis, or even death . Further, persistent organic pollutants (POP), including organochlorine pesticides (OCP), PCB, PBDE, and PAH, are organic lipophilic chemicals that bioaccumulate in fatty tissues, also causing adverse effects on human health and the environment . Exposure to POP is associated with malfunctions in the reproductive and endocrine systems , being also responsible for the development of many cancer types. Apart from human health, the use of pesticides is deleterious to the environment. Because of this, many flora and fauna species are exposed to multiple contaminants. Water, soil, and air pollution caused by the use of chemicals leads to disturbances in the ecosystem and poses a threat to biodiversity . Therefore, their use must be restricted . Due to the toxicity of environmental pollutants, their content needs to be continuously monitored, and attention to them is crucial. Besides that, surveys of pesticide residues in fruit are important to validate conformity with strict regulations of newly open markets for the exportation of exotic fruit. The European Commission establishes the maximum residue levels (MRLs) for pesticides to minimize the exposure of humans to harmful levels in food or feed . Pesticides and several environmental pollutants have been reported in the literature on food . However, there is a lack of studies regarding new fruits that are not yet legislated even though there is a high demand, and environmental contaminants are also not legislated . Even more, one of the ambitious goals set by the European Green Deal and the Farm to Fork Strategy includes a 50% reduction in the use of pesticides by 2030. This strikes a challenge to analytical chemistry, namely in the development and validation of sensitive analytical methods. One of the best approaches for multiresidue analysis (simultaneously pesticide and other contaminants) in food samples is the extraction by Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method . It is a very convenient, reagent-saving solid-phase extraction-based procedure consisting of two major steps . In the first step, the fruit, vegetable, or other food sample is subjected to extraction with acetonitrile (MeCN) and salts (e.g., MgSO4, NaCl), followed by a second step in which a sample clean-up via dispersive solid-phase extraction (d-SPE) is performed . Afterward, the extracted and purified compounds are commonly analyzed with the use of gas chromatography (GC)-based methods . Particularly, GC coupled with a mass spectrometer (MS) is favored for such a complex multiple contaminants identification due to the low limits of detection (LOD) . Tandem mass spectrometry, specifically GC-MS/MS and LC-MS/MS, and other selective detectors were reported to be more efficient in simultaneously detecting multiple contaminants . Considering the beneficial properties associated with the kiwano and its increasing consumption, it becomes urgent to develop methodologies and evaluate this fruit's safety . To the best of our knowledge, there are no analytical methods developed or monitoring studies that report the chemical safety in terms of pesticides and other environmental contaminants, namely plastic-related chemicals and others associated with anthropogenic sources, in kiwano fruit samples. Therefore, the aim of this study was to optimize and validate an extraction methodology for the simultaneous analysis of 30 multiple contaminants (6 OPP, 12 OCP, 5 PCB, and 7 BFR) from kiwano fruit samples using QuEChERS method and d-SPE clean-up to detect trace levels of these contaminants using GC techniques. 2. Materials and Methods 2.1. Reagents and Standards Analytical standards of high purity (>=97%) for seven brominated flame retardant (BFR) compounds (2,4,4'-tribromodiphenyl ether (BDE28), 2,2',4,4'-tetrabromodiphenyl ether (BDE47), 2,2',4,4',5-pentabromodiphenyl ether (BDE99), 2,2',4,4',6-pentabromodiphenyl ether (BDE100), 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE153), 2,2',4,4',5,6'-hexabromobiphenyl ether (BDE154), and 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE183)) were obtained from Isostandards Material, S.L. (Madrid, Spain). The five PCB standards (2,4,4'-trichlorobiphenyl (PCB28), 2,2',4,5,5'-pentachlorobiphenyl (PCB101), 2,3',4,4',5-pentachlorobiphenyl (PCB118), 2,2',4,4',5,5'hexachlorobiphenyl (PCB153), and 2,2',3,4,4',5,5'-heptachlorobiphenyl (PCB180)) were acquired from Riedel-de Haen (Seelze, Germany). The eighteen pesticides with analytical grade (12 OCP (hexachlorobenzene (HCB), a-, b-, and z-hexachlorocyclohexane (HCH), [1,1,1-trichloro-2-(2-chlorophenyl)-2-(4-chlorophenyl)ethane] (o,p'-DDT), 2,2-bis(4chlorophenyl)-1,1-dichloroethylene (p,p'-DDE), 1-chloro-4-[2,2dichloro-1-(4-chlorophenyl)ethyl]benzene (p,p'-DDD), aldrin, dieldrin, a-endosulfan, methoxychlor, and lindane) and 6 OPP (chlorfenvinphos, chlorpyrifos, chlorpyrifos-methyl, dimethoate, parathion-methyl, and malathion) were obtained from Sigma-Aldrich (St. Louis, MO, USA). The internal standards (IS) 4,4'-dichlorobenzophone and triphenyl phosphate were from Sigma-Aldrich (St. Louis, MO, USA). QuEChERS extraction kits, clean-ups, and SampliQ GCB (Graphitized carbon black) SPE Bulk Sorbent were from Agilent Technologies (Santa Clara, CA, USA). Chromatography grade n-hexane and acetonitrile (MeCN) were purchased from Merck (Darmstadt, Germany) and Carlo Erba (Val de Reuli, France), respectively. Ultrapure water (UPW) with water sensitivity >18.2 MOcm at 25 degC was produced with a Milli-Q water purification system (Millipore, MA, USA). 2.2. Samples Ten kiwano fruits were supplied by a local farm located at Cinfaes, Douro, Portugal. The mature fruits were collected in February 2019 from 10 different plants (random sampling) to obtain a representative set of fruits. The pulp of kiwano was separated from the orange skin, ground in a miller, homogenized, and finally, stored at -18 degC. 2.3. Extraction Procedure: Optimization and Validation The 30 multiple contaminants were extracted from the kiwano samples based on the previously reported QuEChERS method with d-SPE clean-up . The procedure, whose schematic illustration is shown in Figure 1, included five steps: (1) 5 g of kiwano pulp sample was weighed into a 50 mL polypropylene tube, (2) 8 mL of MeCN and 2 mL of UPW were added, and the tube was thoroughly vortexed for 1 min, EN QuEChERS (4 g MgSO4, 1 g NaCl, 1 g NaCitrate, 0.5 g disodium citrate sesquihydrate) were added, the tubes were shaken for 1 min with a vortex, and centrifuged for 5 min at 2490 rcf at room temperature, (3) 1 mL of the supernatant was transferred to the 2 mL d-SPE clean-up tube (150 mg of MgSO4, 50 mg of PSA, and 25 mg of GCB) and the tubes were vortexed for 1 min and centrifuged for 5 min at 2490 rcf at room temperature, (4) 900 mL of the final extract was transferred to a labelled vial, the extract was dried under nitrogen flow, and it was redissolved in 900 mL of n-hexane, and finally, (5) the sample was vortexed and 150 mL of the extract with the addition of 100 mg L-1 of the IS was added in the vial and was placed in the autosampler for the gas chromatography (GC) analysis. The IS was used to control the analytical quality of the GC analysis. Extractions were performed in triplicate. For the optimization of the methodology, pre-spiking and post-spiking experiments were carried out to evaluate the extraction efficiency. The procedure for pre-spiking was the same as described above , with the difference that the sample in step 1 was contaminated with 7.5 mg kg-1 from the mixture of 30 multiple contaminants. The following steps remained the same, as shown in Figure 1. The procedure for the post-spiking had a change in step 4. Before injection in the GC, 7.5 mg kg-1 of the 30 multiple contaminants was added to the vial and redissolved in the kiwano fruit extract. The extraction efficiency was studied in terms of recoveries percentages comparing the results obtained between the pre-spiking and post-spiking studies. The validation of the method developed was performed following the Eurachem guidelines and SANTE/11312/2021 document by studying several analytical parameters, such as the linearity, recovery at three spiking levels (7.5, 11.2, 14.9 mg kg-1) and 5 replicates matrix effects, and intra-day and inter-day precision (experiments with the 7.5 mg kg-1 spiking level by five repeated measurements in the same and intercalary days). Quantification was performed using matrix-matched calibration (linearity between 1.5-18.7 mg kg-1) and solvent calibration (linearity between 10-125 mg L-1). The analytical validation was performed in the GC coupled to an electron capture detector (GC-ECD) and GC coupled to a flame photometric detector (GC-FPD), and with the regression analysis, the linearity was evaluated, and the limits of detection and quantification (LOD and LOQ) were determined. 2.4. Equipment The GC analysis was performed according to Dorosh et al. . Briefly, the halogenated organic compounds (5 PCB, 7 BFR, and 12 OCP) were analysed using GC-ECD (GC-2010, Shimadzu, Quioto, Japan) and OPP using a GC -FPD (GC-2010, Shimadzu, Quioto, Japan). The presence of contaminants was confirmed by GC/MS. Confirmation was based on a comparison of sample GC retention time and product ion abundance ratios (mass to charge ratio, m/z) against those obtained for a reference standard. The system control and the data acquisition were performed in Shimadzu's GC Solution software in GC-ECD and GC-FPD and Xcalibur software in GC/MS. The GC analysis was performed in triplicate. 2.4.1. GC-ECD The analysis was performed using a capillary GC column Zebron-5MS (30 m x 0.25 mm x 0.25 mm) (Phenomenex, Madrid, Spain). The oven temperature was programmed at 40 degC for 1 min, increased to 120 degC at a rate of 15 degC/min where it was kept for 1 min. Then, the temperature was increased once more at a rate of 10 degC/min to 200 degC, where it was kept for 1 min, and lastly, the temperature was increased from 7 degC/ min to 290 degC and held for 10 min. The injection was performed in splitless mode. The temperatures of the injector and ECD were 250 degC and 300 degC, respectively. Helium was used as a carrier gas (1.3 mL/min), and nitrogen as a makeup gas (30 mL/min). 2.4.2. GC-FPD The GC-FPD column was the same as the one described in Section 2.4.1. The carrier gas was helium at 1 mL/min with a linear velocity of 25.4 cm s-1. The detector was at 250 degC in injection was performed in splitless mode, and the analytes were detected at 290 degC. The column was programmed at 100 degC, which was kept for 1 min before increasing it to 150 degC at a rate of 20 degC/min, where it was held for 1 min. Following, the temperature was increased to 180 degC at 2 degC/min and kept for 2 min, and finally, increased at 20 degC/min to 270 degC, where it was kept for 1 min. 2.4.3. GC/MS Analysis According to SANTE guidelines, confirmation of samples should be performed by MS detector. GC/MS analysis was performed with similar conditions of GC-ECD only in the positive samples observed in GC-ECD in order to have confirmation. GC/MS instrument, TRACE GC Ultra (Thermo Fisher Scientific, Austin, TX, USA) gas chromatograph coupled with a Polaris Q ion trap mass spectrometer was used. The transfer line and the ion source temperature were 260 and 270 degC, respectively. Data acquisition was performed first in full scanning mode from 50 to 500 m/z to confirm the retention times of the analytes. All standards and sample extracts were analyzed in selective ion monitoring (SIM) mode. PCB101 confirmation was performed with the identification of three m/z ions 326 > 324 > 286. 2.5. Statistical Analysis Two-way ANOVA statistical analysis was applied to estimate significant differences among different analytical procedures using GraphPad software. Multiple comparisons were performed where each mean value was compared to each group of contaminants. 3. Results and Discussion The extraction and clean-up steps for kiwano' matrices were a challenging part of the method development due to its rich composition in carotenoids, steroids, alkaloids, saponins, glycosides, flavonoids, tannins, and phenolic compounds . The optimization of analytical methods for the determination of 30 contaminants in kiwano samples included the two crucial steps of the QuEChERS procedure: (1) Sample extraction and (2) the d-SPE clean-up. Figure 2 shows the chromatogram obtained when the mixture of the 30 multiple contaminants was analyzed by GC-ECD and FPD in the method described previously in Section 2.4.1.1 and Section 2.4.2. The extraction recovery of the method was evaluated by spiking the kiwano sample with the multiple contaminant solutions at 7.5 mg kg-1. Four protocols were tested: (1) QuEChERS AOAC with additional d-SPE clean-up CL1 (150 mg of MgSO4, 50 mg of PSA, and 50 mg of GCB), (2) QuEChERS AOAC with additional d-SPE clean-up CL2 (150 mg of MgSO4, 50 mg of PSA, and 25 mg of GCB), (3) QuEChERS EN with additional d-SPE clean-up CL1, and (4) QuEChERS EN with additional d-SPE clean-up CL2. The study of the evaluation of the method's efficiency was carried out according to the guidelines of the SANTE document , being the range of recovery established 70 to 120%. In Figure 3, poor extraction recoveries were observed for some of the chemical families using QuEChERS AOAC. The OCP, PCB, and BFR compounds presented recoveries of less than 70% using the QuEChERS AOAC and CL1, while for QuEChERS AOAC and CL2 only the PCB compounds. Since recovery percentages after the clean-up CL1 (150 mg of MgSO4, 50 mg of PSA, and 50 mg of GCB) for QuEChERS AOAC evaluation were not satisfactory, the approach testing test other QuEChERS contents (EN) and another d-SPE clean-up (CL2) was followed. After reducing GCB in the CL2 clean-up and using QuEChERS EN, an improvement in extraction recoveries for all targeted multiple compounds was stated. The most evident result on extraction efficiency is the negative influence of the amount of GCB used in the second step of the extraction. As previously reported, GCB adsorbs compounds such as pigments, anthocyanins, and carotenoids, as well as planar compounds . Therefore, reducing its quantity in the cleaning step is one of the optimizations of this process. Although the lower amount of GCB did not absorb all the coloring compounds like the previous CL1 clean-up, the samples were still suitable for GC analysis. ANOVA statistical analysis was used to compare the mean recoveries of each cleaning test (CL1, CL2) between the target chemical groups (OCP, OPP, PCB, BFR). The two-way ANOVA statistical study showed that the recoveries are significantly different comparing the two different clean-up sets (CL1 and CL2) for OCP and BFR using QuEChERS AOAC while for QuEChERS EN all chemical groups were statistically different. Overall, the results showed that most of the compounds are in the 70-120% range when QuEChERS EN and CL2 are used. Figure 4 shows a summary of the results of the recovery studies. It was observed that in the satisfactory range 70-120%, the highest number of contaminants was achieved with QuEChERS EN and CL2. As previously reported, a detailed optimization is an extremely important step as it reveals which compounds show the best results. As reported by Fernandes et al. , this extraction method is suitable but needs to be optimized and studied for each group of compounds and matrices. The results, displayed in Figure 3 and Figure 4, allowed us to assess that the best extraction and cleaning procedures for kiwano were QuEChERS EN with a clean-up CL2 (150 mg of MgSO4, 50 mg of PSA, and 25 mg of GCB), and this was selected for all further investigations. 3.1. Matrix Effects In the present work, the matrix effect was evaluated by comparing the slope obtained with the calibration curves of each compound in the matrix phase and n-hexane. This evaluation was complemented by comparing the retention times of the chromatograms with the same concentration in the matrix phase and n-hexane, and no significant differences were observed. It is well described in the literature that some analytes in fruit extracts exhibit a matrix signal enhancement/suppression effect when analyzed by GC . This effect occurs when interferences from fruit matrices (such as pigments, lipids, acids, etc.) compete with the target analytes in the GC injector . Figure 5 shows that the different chemical families (OCP, OPP, PCB, and BFR) analyzed in kiwano fruits presented different matrix effects behaviors. The signal enhancement was observed with the use of both QuEChERS AOAC and EN with the CL2 cleaning step. Additionally, with QuEChERS AOAC and CL2 clean-up, the mean matrix factor value was higher than 1.2 in all the chemical families. The BFR are those with the highest signal increase. The QuEChERS EN showed a satisfactory matrix factor with CL1 clean-up. However, as shown in Section 3, the extraction efficiency was not acceptable with this extraction procedure. In any case, this study confirmed that the matrix effect was more evident when the lowest amount of GCB sorbent was used. 3.2. Method Validation Method validation is an important requirement in the practice of an analytical method process. The reliability and robustness of the method to be used for real sample analysis should be studied considering several analytical parameters. Linearity, extraction recovery at three spiking levels (7.5, 11.2, 14.9 mg kg-1), precision, LODs and LOQs obtained by the regression analysis (based on the standard deviation of the response of the curve and the slope of the calibration curve), as well as matrix effects, were the parameters studied for the validation of analysis of multiple contaminants in kiwano samples. Table 1 summarizes the analytical parameters in order of retention time obtained by GC-ECD and GC-FPD. Considering the matrix effects described in the previous section, the analytical validation process was carried out in kiwano extract. Matrix-matched calibration curves were obtained in kiwano extracts of the 30 target analytes with a coefficient of determinations greater than 0.991. LODs and LOQs ranged from 0.2 to 2.2 and 0.6 to 7.4 mg kg-1, respectively (Table 1). The mean recoveries at the three spiking levels of 7.5, 11.2, and 14.9 mg kg-1 ranged from 90% and 122% (99% on average) with relative standard deviation (RSD) values between 8% and 15%. The method precision was determined through intra-day and inter-day repeatability experiments by five repeated measurements, and the results were less than 15% of RSD, which is suggested as the acceptable precision (Table 1). When compared to other studies on exotic fruits , we can say that for organochlorine pesticides, for example, the analytical parameters, namely the LOD and LOQ, are much better in the present work. As for the BFR, a study in capsicum cultivars already reported presents higher LOD and LOQ values than those obtained for Kiwano. Although the European Union legislation for pesticides does not include the kiwano fruit, the analytical parameters obtained for this method meet the requirements. As for the other studied compounds, most of them are not included in the food legislation, despite being frequently detected in food products. As an example, EFSA recommends BFR monitoring studies in food samples . 3.3. Kiwano Sample Analysis After the method validation, the optimized method was applied to evaluate possible contamination in kiwano samples. Since the study was carried out on the kiwano pulp, as it is the edible part, the results are presented by pulp mass. The screening of the 30 multiple contaminants in a total of 10 kiwano samples led to the identification and quantification of PCB 101 (5.1 mg kg-1 in the kiwano pulp) in a single sample. GC/MS analysis confirmed the presence of PCB 101 . It was also confirmed that, except for one sample, the kiwano fruit samples are safe in terms of 12 OCP, 6 OPP, 7 BFR, and 5 PCB studied. The presence of pesticides is well reported in the literature on fruits , concerning other contaminants, the works are less represented. However, PCBs, mostly associated with anthropogenic sources, have been reported in grapes, and other several fruits and BFR in red fruits , capsicum cultivars , among others . This work was performed in a small number of samples, and Portugal is still in the beginning regarding this crop. However, it shows the great importance of including these fruits in monitoring studies and that it should be extended to a larger number of samples from different production sites. Furthermore, the results suggest the importance of including other organic contaminants in monitoring studies on food samples in addition to pesticides. 4. Conclusions An analytical methodology based on an optimized QuEChERS technique was effectively applied for the simultaneous analysis of 30 multiple contaminants (12 OCP, 7 OPP, 5 PCB, and 7 BFR) in kiwano samples. The optimized QuEChERS procedure encompassed the study of two QuEChERS compositions (QuEChERS AOAC and EN) in addition to two d-SPE clean-up compositions (CL1 and CL2). Although matrix effects were observed, it was found that QuEChERS EN, in combination with CL2 clean-up, offered an improvement in overall extraction recovery of the multiple target contaminants. Based on these results, it can be concluded that analytical method optimization studies are crucial for the analysis of multiple compounds in complex matrices. The methodology meets the analytical requirements in terms of accuracy, sensitivity, and precision. The novelty of this study allows the evaluation of multiple contaminants in kiwano samples, ensuring their safe commercialization in terms of the presence of pesticides and other organic contaminants. The presence of PCB 101 in one kiwano fruit reinforces the need for monitoring studies of organic contaminants, such as PCBs and BFRs. Acknowledgments This work received support from PT national funds (FCT/MCTES, Fundacao para a Ciencia e Tecnologia and Ministerio da Ciencia, Tecnologia e Ensino Superior) through the projects UIDB/50006/2020, UIDP/50006/2020 and LA/P/0008/2020. Virginia Cruz Fernandes thanks FCT/MCTES and ESF (European Social Fund) through NORTE 2020 (Programa Operacional Regiao Norte) for her Post doc grant ref. SFRH/BPD/109153/2015. Clara Grosso (CEECIND/03436/2020), Elsa F. Vieira (CEECIND/03988/2018), Francisca Rodrigues (CEEC-IND/01886/2020) and Manuela M. Moreira (CEECIND/02702/2017) thank FCT (Fundacao para a Ciencia e Tecnologia) for her contracts through the Scientific Employment Stimulus - Individual Call. Author Contributions Conceptualization, V.C.F.; methodology, V.C.F. and M.P.; validation, V.C.F.; formal analysis, V.C.F. and M.P.; investigation, V.C.F., M.P., E.F.V., F.R., C.G. and M.M.M.; resources, C.D.-M.; data curation, V.C.F. and M.P.; writing--original draft preparation, V.C.F. and M.P.; writing--review and editing, V.C.F., M.P., E.F.V., F.R., C.G. and M.M.M.; visualization, V.C.F., E.F.V., F.R., C.G., M.M.M. and C.D.-M.; supervision, V.C.F.; project administration, E.F.V. and V.C.F.; funding acquisition, C.D.-M.; All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data are available from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Scheme of the experimental procedure. Figure 2 (A) Chromatogram of the injection by GC-FPD of a standard mixture of 7 organophosphorus pesticides at 7.5 mg kg-1. (B) Chromatogram of the injection by GC-ECD of a standard mixture of 23 halogenated organic compounds (5 PCB, 7 BFR and 12 OCP) 7.5 mg kg-1. Figure 3 Mean extraction recoveries (%) of the targeted multiple contaminants divided into four chemicals groups (OCP, p-value = 0.006; OPP, p-value = 1; PCB, p-value = 0.06 and BFR, p-value = 0.0002) using QuEChERS AOAC (A) and QuEChERS EN (B). Two-way ANOVA analysis with Sidak's multiple comparisons test (ns: Non-significant; **/***/****--significant). Figure 4 Number of contaminants obtained in the ranges lower than 70%, between 70 and 120% and higher than 120%, using QuEChERS AOAC (A) and EN (B). Figure 5 Matrix factor results for the chemical families studied using QuEChERS AOAC (A) and EN (B). Figure 6 (A) GC-ECD chromatogram overlapping kiwano sample and 100 mg L-1 mixture standard solution and (B) GC-MS spectrum of confirmation of the presence of PCB 101 (m/z 286, 324, 326). foods-12-00993-t001_Table 1 Table 1 Data including correlation to the matrix-matched calibration curve, the limit of detection (LOD) and limit of quantification (LOQ), mean recoveries (from three spiking levels), and precision obtained for the 30 target contaminants. Linearity Range mg kg-1 Coefficient of Determination LOD mg kg-1 LOQ mg kg-1 Mean Recovery (n = 3)% Precision (n = 5) Intra-Day Inter-Day % a-HCH 2.2-18.7 0.9922 2.1 6.9 95 10 14 HCB 2.2-18.7 0.9933 2.0 6.6 94 14 15 b-HCH 2.2-14.9 0.9936 2.2 7.3 90 9 11 Lindane 2.2-14.9 0.9941 2.1 7.1 103 9 13 z-HCH 2.2-14.9 0.9926 1.8 5.9 91 8 11 PCB 28 2.2-18.7 0.9928 2.2 7.3 90 9 10 Aldrin 1.5-18.7 0.9989 1.2 4.2 99 8 9 PCB 101 1.5-18.7 0.9986 1.4 4.7 110 10 12 End I 1.5-18.7 0.9995 0.8 2.8 105 12 15 p,p'-DDE 2.2-18.7 0.9939 1.7 5.6 99 8 9 Dieldrin 1.5-18.7 0.9990 1.1 3.6 114 8 10 PCB 118 1.5-18.7 0.9987 1.1 3.7 90 9 12 BDE 28 1.5-18.7 0.9999 0.3 1.0 99 8 11 p,p'-DDD 1.5-18.7 0.9998 0.2 0.6 91 10 14 o,p'-DDT 1.5-18.7 0.9992 1.0 3.2 90 13 15 PCB 153 1.5-18.7 0.9996 0.7 2.2 106 9 11 Methoxychlor 2.2-18.7 0.9965 1.9 6.3 93 9 14 PCB 180 1.5-18.7 0.9983 1.3 4.3 122 8 9 BDE 47 1.5-18.7 0.9995 0.7 2.3 108 8 10 BDE 100 2.2-18.7 0.9929 2.0 6.6 99 13 15 BDE 99 1.5-18.7 0.9990 1.0 3.3 103 9 12 BDE 153 1.5-18.7 0.9993 0.8 2.8 122 7 9 BDE 154 1.5-18.7 0.9998 0.4 1.4 95 6 9 BDE 183 1.5-18.7 0.9995 0.7 2.3 91 9 12 Dimethoate 2.2-18.7 0.9938 1.9 6.3 90 8 11 Chlorpyrifos-methyl 2.2-18.7 0.9931 2.2 7.3 93 7 9 Methyl parathion 2.2-18.7 0.9960 1.7 5.7 105 9 10 Malathion 2.2-18.7 0.9929 2.0 6.6 94 10 13 Chlorpyrifos 1.5-18.7 0.9993 0.9 2.9 97 8 10 Chlorfenvinphos 1.5-18.7 0.9989 1.1 3.6 90 13 15 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000519 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051079 foods-12-01079 Review Essential Oils: Recent Advances on Their Dual Role as Food Preservatives and Nutraceuticals against the Metabolic Syndrome Chavez-Delgado Emily L. 1 Jacobo-Velazquez Daniel A. 12* Iriti Marcello Academic Editor 1 Tecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Ave. General Ramon Corona 2514, Zapopan 45138, Jalisco, Mexico 2 Tecnologico de Monterrey, The Institute for Obesity Research, Ave. General Ramon Corona 2514, Zapopan 45201, Jalisco, Mexico * Correspondence: [email protected] 03 3 2023 3 2023 12 5 107916 2 2023 28 2 2023 01 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Essential oils (EO) are compounds synthesized by plants as secondary products and are a complex mixture of volatile molecules. Studies have demonstrated their pharmacological activity in the prevention and treatment of metabolic syndrome (MetS). Moreover, they have been used as antimicrobial and antioxidant food additives. The first part of this review discusses the role of EO as nutraceuticals to prevent metabolic syndrome-related disorders (i.e., obesity, diabetes, and neurodegenerative diseases), showing results from in vitro and in vivo studies. Likewise, the second part describes the bioavailability and mechanisms of action of EO in preventing chronic diseases. The third part presents the application of EO as food additives, pointing out their antimicrobial and antioxidant activity in food formulations. Finally, the last part explains the stability and methods for encapsulating EO. In conclusion, EO dual role as nutraceuticals and food additives makes them excellent candidates to formulate dietary supplements and functional foods. However, further investigation is needed to understand EO interaction mechanisms with human metabolic pathways and to develop novel technological approaches to enhance EO stability in food systems to scale up these processes and, in this way, to overcome current health problems. essential oils metabolic syndrome diabetes obesity neuroprotection antioxidant antimicrobial nanoencapsulation Tecnologico de Monterrey--Institute for Obesity ResearchThis study was based upon research supported by Tecnologico de Monterrey--Institute for Obesity Research. pmc1. Introduction Obesity is the leading risk factor for metabolic syndrome (MetS) due to energetic imbalance; this can cause impaired glucose tolerance, insulin resistance, type 2 diabetes, dyslipidemia, hypertension, and a chronic proinflammatory state . Non-pharmaceutical alternatives, such as nutraceuticals, phytotherapy, and functional foods, have been explored to prevent and treat common diseases, and their use is increasing in the public domain by up to 50-70% . Nevertheless, their long-term safety, efficacy, and dose schemes are being actively researched . Essential oils (EO) are composed of a mixture of natural, volatile, aromatic compounds characterized by a strong odor and are produced as secondary metabolites by aromatic plants in different plant organs, including buds, flowers, seeds, leaves, roots, fruits, wood, twigs or bark . Extraction methods are divided into conventional and non-conventional techniques. Common conventional techniques include hydrodistillation, Soxhlet extraction, water distillation, steam distillation, and organic-solvent extraction. Non-conventional extraction processes include ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), high-pressure (HP), pressurized liquid extraction (PLE), negative pressure cavitations-assisted extraction (NPCE), subcritical water extraction (SWE), supercritical fluid extraction (SFE), enzyme-assisted extraction (EAE), pulsed electric field-assisted extraction (PEF), and accelerated solvent extraction (ASE). These extraction techniques and non-thermal and are categorized as "green", since they use lower amounts of solvents, energy, and time, giving higher yields compared to conventional methods . Organic compounds present in EO vary between 20-200 different types, with the vast majority present in traces, although two or three of these compounds are the most representative ones (20-70%) and are thought to be responsible for the biological activities of the EO . Despite that, terpene hydrocarbons are the primary chemical group found in EO . Terpene hydrocarbons are classified as monoterpenes (C10), which are the major constituents of EO; sesquiterpenes (C15); diterpenes (C20); terpenoids (oxygenated terpenes); and aromatic compounds, such as phenylpropanoids, derived from phenylpropane . Traditional medicinal herbs and their derived EO are phytochemical-rich sources of health-promoting bioactive compounds . As nutraceuticals, some reported health benefits of EO include antioxidative, antimicrobial, antitumor, anticarcinogenic, anti-inflammatory, antiatherosclerosis, antimutagenic, antiplatelet aggregation, and angiogenesis inhibitory activities . Nowadays, EO have been used in the food industry as food additives due to their antioxidant and antimicrobial properties. A large variety of EO from different plants have been incorporated into food systems, such as basil, chamomile flowers, cardamom seeds, and rosemary . There is active research in the study of EO as natural potential candidates to prevent and treat MetS. Their incorporation in proper food vehicles to achieve this goal is a new and interesting approach that deserves particular interest. For this reason, several studies focused on these fields are recapitulated herein. However, to the best of our knowledge, few or no studies are focused on using EO as nutraceuticals and food additives to treat metabolic and non-communicable diseases. Therefore, this review is intended to give a new approach for the production of functional foods using EO as promising molecules. This review is divided into four main sections; the first part discusses the effects of EO in MetS and its comorbidities, specifically in obesity, diabetes, and neurodegenerative diseases, including in vitro and in vivo studies and clinical trials. The second section describes the bioavailability and EO mechanisms of action of their common administration routes (i.e., oral, dermal, and pulmonary administration). The third part presents the incorporation of EO as food additives and discusses current applications in food systems as antimicrobial and antioxidant agents. Finally, the last part focuses on the stabilization and common methods for encapsulating EO in other to preserve their bioactivity and how they could be incorporated into food matrixes. 2. Materials and Methods In this review article, EO bioactivities and additive properties reported were searched in several databases such as Elsevier, Google Scholar, PubMed, and SpringerLink via Tecnologico de Monterrey library system. In these databases, keywords were: "essential oils, anti-obesity, anti-diabetes, metabolic syndrome, adipogenesis inhibition, postprandial hyperglycemia control, neuroprotection, microencapsulation, and antimicrobial and antioxidative properties". Research and review articles were selected based on the use of EO in controlling these pathologies and their incorporation into food matrixes. In the case of anti-obesity, anti-diabetes, and neuroprotection activities, those studies focused only on individual or majority components of EO were excluded since it was intended to show the bioactivity of EO per se. Because this field has been relatively little explored, we aimed to explore extensively what has been reported over the past 18 years (2005-2023). 3. Use of EO for Metabolic Syndrome-Related Disorders Management MetS is a combination of metabolic disorders that comprises central obesity, insulin resistance, hypertension, and atherogenic dyslipidemia. These factors propitiate chronic inflammation, leading to cardiovascular disease (CVD) development. Because obesity rates have been increasing worldwide, MetS has become highly relevant; thus, early prevention and treatment are crucial factors in decreasing mortality rates . It has been reported the use of EO for treating obesity and diabetes. The following sections present in vitro and in vivo studies and clinical trials regarding the use of EO for preventing and treating metabolic syndrome-related disorders. 3.1. Anti-Obesogenic Potential Adipocytes are cells in charge of maintaining energetic homeostasis. These cells are present in white adipose tissue (WAT) and brown adipose tissue (BAT). WAT is important in energy storage, while BAT uses energy to produce heat. Morphologically, WAT is characterized by one single lipid droplet, whereas BAT comprises many multilocular liquid droplets and mitochondria . Excessive fat accumulation results in inflammation and oxidative stress in adipose tissue as a result of a constant elevation of plasma-free fatty acids (FFAs) caused by a growing release from enlarged adipose tissue that activates and upregulates the expression of several proinflammatory cytokines such as tumor necrosis factor-a (TNFa), interleukin (IL)-1b and IL-6, which aggravates metabolic alterations . For instance, the constant liberation of FFAs promotes the synthesis of very low-density lipoprotein, cholesterol, and gluconeogenesis in the liver, thus provoking impaired insulin signaling and glucose metabolism and, by this process, causing insulin resistance . Fat homeostasis is driven by two principal metabolic pathways: lipogenesis and lipolysis. The former is accountable for packaging esterified triglycerides in the liquid droplet when there is an excess of nutrients, thus expanding adipose tissue, which may play a central role in obesity comorbidities. At the same time, the latter hydrolyze lipid triglycerides into glycerol and three fatty acids . Lipogenesis is driven by two principal transcriptional regulators, the Sterol Response Element Binding Protein 1c (SREBP1c) and the Carbohydrate Response Element Binding Protein (ChREBP). The activation of both pathways is due to increased insulin signaling in response to high glucose levels . Lipogenesis inhibition is a promising strategy to prevent fat storage in adipocytes; therefore, WAT and BAT are crucial targets for obesity treatment and related diseases . Adipocyte differentiation, also known as adipogenesis, is a process in which preadipocytes are transformed into mature adipocytes . It plays a vital role in regulating obesity; for instance, combined with adipocyte hypertrophy, it is is the primary mechanism leading to this disorder . In vitro and in vivo experiments on the anti-obesity potential of different EO are presented in Table 1. Regarding adipogenesis, this process compromises several steps guided by different transcription factors regulating adipogenic gene expression. There are two important families, the CCAAT/enhancer-binding proteins (C/EBPs) and the peroxisome proliferator-activated receptors (PPARs). Adipogenesis initiates with the expression of C/EBPb and C/EBPd, which in turn activates C/EBPa and PPARg mRNA. These molecules trigger the transcription of adipogenic genes, resulting in phenotypically and functionally different fat cells. Likewise, extracellular signal-regulated kinases (ERKs), members of the mitogen-activated protein kinases (MAP-Ks), also participate in the signaling cascades of C/EBPa and PPARg expression . As presented in Table 1, many studies demonstrated that using EO led to suppressed lipid droplet accumulation and adipogenesis in a dose-dependent manner. Yen et al. , Ngamdokmai et al. , Hwang et al. , Lee et al. , Ko et al. , Cheng et al. , and Sprenger et al. investigated the effect of various EOs, such as lemon balm, peppermint, lavender, bergamot, cypress, niaouli nerolidol, geranium-rose, revensara, lemon grass, ginger, black pepper, Artemisa annua L., calamus, Pinus koraiensis, and cinnamon. These EOs were all tested in 3T3-L1 preadipocytes treated with different concentrations during the differentiation process, followed by Oil-Red O (ORO) assay to assess lipid accumulation. The outcomes of these studies exhibited that these EOs significantly inhibited lipid accumulation through the downregulation of 3T3-L1 adipocyte differentiation. Adipogenesis inhibition is due to the suppression of adipogenic transcription factors expression, mentioned above. It is concluded that these EO have anti-obesogenic and hypolipidemic potential via inhibition of PPARg-related signaling. For instance, the studies performed by Ngamdokmai et al. , Lee et al. , Cheng et al. , Sprenger et al. , Lai et al. , and Lai et al. , besides testing EOs per se, also isolated the major component of each and tested their action in the model of study (in vitro or in vivo). It was concluded that those components exerted anti-obesity effects. In the case of olfactory stimulation, the study performed by Hong et al. demonstrated that citronellol is a volatile and prominent patchouli EO (PEO) compound that is accountable for diminishing food intake, thus preventing obesity. Moreover, a-patchoulene and b-patchoulene release the PEO odor, stimulating the hypothalamus and regulating serum leptin levels, lowering food intake. However, as Russo et al. mentioned, further investigation is required for individual components' action in adipocyte metabolism since EOs are phytochemically complex molecules in which each component is thought to take part in the overall outcome and could regulate the effect of the others, either synergistically or antagonistically. Therefore, it could be uncertain which individual components are the only ones responsible for conferring anti-obesity effects, thus it is preferable to assert results taking into consideration the EO as a whole. Studies in animals have demonstrated that certain EOs exert anti-obesogenic activity. Ko et al. , Cheng et al. , Lai et al. , Lai et al. , Asnaashari et al. , and Ciftci et al. investigated the effect of garlic, Pinus koraiensis, lime, cinnamon, ginger and a mix of thyme, orange peel, bay leaf, and eucalyptus, respectively, on body weight, food intake, serum biochemical metabolites (glucose, insulin, free fatty acids, cholesterol, and triglycerides), and adipose tissue of standard or high-fat diet (HFD) fed animals (mice, rats or quails). EOs tested suppressed--in a dose-dependent manner--increases in fat pads, body weight, and serum biochemical parameters induced by HFD. Scientific reports evaluating the anti-obesity effects of EO compared to orlistat--a specific gastrointestinal lipase inhibitor commonly used in obesity treatment that inhibits the absorption of fat, resulting in weight loss--concluded that sweet orange and cumin EOs are potential candidates to replace pharmacological obesity treatments through downregulation of PPARg expression, consequently preventing preadipocytes . foods-12-01079-t001_Table 1 Table 1 Studies evaluating the effect of essential oils (EO) on the prevention and treatment of obesity. Essential Oil (EO) Study Details Experimental Findings Reference 29 different EOs (lemon balm, Spanish sage, rosemary, marjoram, peppermint, lavender, thyme, basil, orange, bergamot, lemon, mandarin, grapefruit, tea tree, Niaouli nerolidol, eucalyptus, cypress, cedarwood, juniper-berry, black pepper, frankincense, ginger, geranium-rose, fennel, chamomile-roman, pine, and even Sara) In vitro--3T3-L1 preadipocytes were differentiated. Oil-Red O (ORO) stain assay was done to assess lipid accumulation. 3T3-L1 adipocytes were treated with all samples at 60 mL/mL concentration for six days. Lemon balm, peppermint, lavender, bergamot, cypress, niaouli nerolidol, geranium-rose, and revensara inhibited lipid accumulation by 53-90% compared to the control. Spanish sage, rosemary, marjoram, orange, eucalyptus, cedarwood, black pepper, and ginger increased lipid accumulation (110-167%). Thyme, lemon, tea tree, fennel, chamomile-roman, pine, basil, mandarin, grapefruit, juniper-berry, and frankincense did not show effects on lipid metabolism (90-110%). Garlic EO (GEO) In vivo--Six-week-old male C57BL/6J mice were fed a standard or high-fat diet (HFD) with and without GEO for 12 weeks. GEO concentrations were 25, 50, or 100 mg/kg. Blood, liver, subcutaneous, epididymal, and perirenal fats were collected. GEO at 50 mg/kg concentration prevented the increment of subcutaneous, epididymal, and perirenal fat pads in mice fed with HFD, and reduced their elevated glucose levels, insulin, free fatty acids, and triglycerides. Seven different EOs (lemon grass, ginger, black pepper, long pepper, turmeric, cassumunar ginger, and kaffir lime) In vitro--3T3-L1 preadipocytes were differentiated. ORO stain assay was done to assess lipid accumulation. Total triglyceride content was determined using a triglyceride assay kit. All EO inhibited or decreased lipid accumulation, adipogenesis, and triglyceride content. Artemisia annua L. EO In vitro--3T3-L1 preadipocytes were differentiated. ORO stain assay was done to assess lipid accumulation. Inhibited adipogenesis. Calamus EO In vitro--After 3T3-L1 differentiation, a total triglycerides assay, ORO, RT-PCR, and western blot analyses (for analysis of p-ERK1/2, C/EBPb, C/EBPa, and PPARg protein) were conducted. Reduction of intracellular triglyceride content and adipogenesis inhibition was detected. Pinus koraiensis EO (PKEO) In vitro--ORO staining, triglycerides content, and expression levels of adipogenic factors were measured in 3T3-L1 differentiated cells treated with PKEO. In vitro results showed a reduction of intracellular triglyceride content and downregulation of adipogenic transcription factors expression. In vivo--Male Sprague-Dawley rats, at four weeks of age, treated with high-fat diets, whose body weights, retroperitoneal and epididymal fats, and serum lipid metabolites (HDL, LDL, triglycerides) were assessed during six weeks. In vivo results demonstrated that PKEO treatment prevented weight gain and suppressed serum triglyceride, total cholesterol, and LDL cholesterol. Lime EO In vivo--Fifty-six male mice weighing 25-30 g were divided into seven groups for 45 days. Males were subcutaneously treated with normal saline (0.1 mL/mice), DMSO (0.02 mL/mice), ketotifen dissolved in 0.1 mL of normal saline (32 mg/kg), lime EO dissolved in 0.02 mL of DMSO (125, 250, 500 mg/kg), and a mixture of ketotifen and lime EO (32 mg/kg, and 125 mg/kg, respectively) properly dissolved in normal saline and DMSO, respectively. Food intake and body weight changes were studied. Mice treated with lime EO exhibited both body weight loss and food intake reduction. Cinnamon EO (CEO) In vitro--3T3-L1 cells were differentiated with the EO, and their major components, S-(+)-linalool, and R-(-)-linalool. After differentiation, the ORO assay was performed. In vitro results exhibited that treatment with cinnamon EO reduced the accumulation of lipid droplets, S-(+)-linalool, and R-(-)-linalool compared with the control group. Higher doses (100 mg/mL) improved the inhibition effect more than lower ones (10 mg/mL). In vivo--Six-week-old male ICR mice were orally treated with corn oil as control, 250 and 500 mg/kg of CEO, 500 mg/kg of S-(+)-linalool, and 500 mg/kg of R-(-)-linalool, for 14 days. Body weight changes and blood biochemical parameters (glucose, total cholesterol (TC), triglyceride levels (TG)) were monitored. In vivo results demonstrated that the body weight change rate was lower than the control group for those mice treated with CEO and S-(+)-linalool. As well as this, blood glucose, TC, and TG were decreased. Citronella EO Clinical trial--A randomized, double-blind, placebo-controlled clinical trial was conducted with 78 overweight subjects aged between 18 and 60. Participants were divided into three groups: (1) treated with 100 mg EO of Cumin cyminum L. capsule; (2) treated with orlistat120 capsule, and (3) treated with placebo. Treatments were taken three times per day for eight weeks. Anthropometric measures and fasting blood samples were taken at baseline and after treatments. Participants who were treated with EO of Cumin cyminum L. capsule exhibited a decrease in weight and body mass index compared to orlistat120 and placebo. Likewise, cumin EO capsules reduced serum insulin levels. Ginger EO (GgEO) In vivo--Eight-week-old male C57BL/6J mice were fed a standard diet or HFD for 12 weeks with orally administrated GgEO or citral (its main chemical compound). They were divided into four groups: (1) positive control with a standard diet with 13.5% kcal fat content; (2) negative control with an HFD with 60% kcal fat content; (3) HFD + GEO (12.5, 62.5, or 125 mg/kg) and (4) HFD + citral (2.5 or 25 mg/kg). Food intake and body weight were monitored. Serum biochemical parameters (glucose, insulin, free fatty acids, cholesterol, and triglycerides) were assessed. Liver, subcutaneous, epididymal, and perirenal adipose tissue were collected. GgEO and citral treatments reduced average body weight by preventing the HFD-treated mice increasing their amount of subcutaneous, epididymal, and perirenal fat pads in a dose-dependent manner. These same treatments considerably decreased the results of serum biochemical levels in a dose-dependent manner. Grapefruit EO (GpEO) In vivo--Male Wistar rats (250-300 g) and male C57BL/6J mice were subjected to olfactory stimulation with GpEO. Autonomic nerve activities were examined electro-physiologically by placing the nose of the anesthetized rat inside a beaker that contained filter paper soaked in GpEO or water. To assess the effects of GpEO on food intake and body and tissue weights, a gauze soaked in GpEO was placed above the animal cage for 15 min, three times a week, for six weeks. Sympathetic white and brown adipose tissue nerve was increased with GpEO inhalation treatment. GpEO reduced food intake, body weight, and organs and adipose tissue weights. Patchouli EO (PEO) In vivo--Four-week-old male Sprague Dawley rats were divided into four groups: (1) standard diet fed control + 30-min inhalation of distilled water (DW); (2) HFD fed control + 30-min inhalation of DW; (3) and (4) HFD + 0.3% and 1% PEO 30-min inhalation, respectively. All treatments lasted 12 weeks. Body weight, food intake, and serum biochemical parameters (TC, HDL cholesterol, and TG) were measured for all groups. Brain, heart, kidney, liver, white adipose tissue (WAT), and brown adipose tissue (BAT) were extracted. Groups subjected to PEO inhalation treatments exhibited a decrement in food intake and body weight. BAT weight was decreased. HDL cholesterol was increased while LDL was decreased. Sweet orange EO (SOEO) In vivo-- six-week-old male Sprague Dawley rats (190-210 g) were divided into six groups: (1) HFD + 2 mL of normal saline; (2) HFD + 2 mL of b-cyclodextrin; (3) HFD + 19 mg of SOEO + 2 mL of normal saline; (4) HFD + 2 mL suspension of SOEO microcapsules (microcapsules were made with SOEO + b-cyclodextrin); (5) HFD + 2 mL suspension of orlistat powder and (6) rats treated with a low-fat diet. Rats were subjected to treatments for 15 days. Body weight and food intake were assessed every two days. Serum biochemical analysis was done. SOEO microcapsules significantly lowered body weight gain and fat rate compared to HFD-fed rats. Furthermore, SOEO microcapsules decreased total cholesterol and LDL cholesterol levels in serum. Lemongrass EO (LGEO) In vitro--ORO staining, triglycerides content, and expression levels of adipogenic factors were measured in 3T3-L1 differentiated cells treated with LGEO and its major constituents: citral and citral diethyl acetal. LGEO and its major constituents decreased lipid accumulation via adipogenesis inhibition, increased lipolysis, and decreased lipid uptake. Mix of EO (MEO) composed of thyme (50%), orange peel (25%), bay leaf (12.5%), and eucalyptus (12.5%) EO In vivo--15-day-old Japanese quails were divided into three groups and exposed to a low ambient temperature. Treatments were: (1) basal-diet; (2) basal diet + 50 ppm of MEO; and (3) basal-diet + 100 ppm of MEO. Serum biochemical parameters were measured. MEO decreased serum glucose, TG, and TC compared to the control group. 3.2. Antidiabetic Potential Diabetes mellitus (DM) is a chronic, lifelong progressive metabolic disorder caused by impaired insulin secretion or insulin resistance, resulting in chronic hyperglycemia. Metabolic abnormalities in carbohydrates, lipids, and proteins arise as a result of low levels of insulin to achieve adequate response or insulin resistance in target tissues . Two primary factors are involved in the development of type 2 diabetes (T2D): impaired insulin secretion by pancreatic b-cells or a lowered number of b-cell mass, which may also contribute to insufficient secretion of insulin and the inability of insulin-sensitive tissues to respond appropriately to this hormone . Insulin resistance in T2D increases the demand for insulin in insulin-target tissues. However, this increased demand for insulin could not be met by the pancreatic b cells due to defects in the function of these cells, which in turn decreases insulin secretion due to the gradual destruction of b cells, resulting in a vicious cycle of metabolic state worsening that could transform some type 2 diabetes patients from being independent to becoming dependent on insulin . 3.2.1. Postprandial Hyperglycemia Postprandial hyperglycemia has been described in the etiology of T2D and cardiovascular disease (CVD); moreover, it is a significant risk factor for the development of atherosclerosis in nondiabetic people . Postprandial hyperglycemia is an excessive plasma glucose concentration after eating, characterized by hyperglycemic spikes that induce oxidative stress. Even in healthy subjects, short-term postprandial hyperglycemia is accompanied by endothelial dysfunction, elevated adhesion molecules, and proinflammatory cytokines in the blood. Postprandial hyperglycemia is driven by many factors such as timing, quantity, meal composition, carbohydrate content, insulin and glucagon secretion, among others . Regarding adipocytes, they are the principal targets for postprandial glucose uptake . 3.2.2. Starch and Digestive Enzymes Activity Carbohydrates are the main dietary component that affects glycemia . Once a meal rich in carbohydrates is ingested, starch is hydrolyzed quickly by digestive enzymes such as a-amylase and a-glucosidase, which results in a high rise in blood glucose and insulin level . Starch contributes to 40-60% of the total energy intake in the human diet . This complex carbohydrate comprises two glucose polymers: amylose, a linear polymer composed of glucose units linked by alpha-(1-4) bonds, and amylopectin, which is a large branched molecule that also has glucose chains linked by alpha-(1-4) bonds and also has glucose chain branches with alpha-(1-6) bonds . In humans, a-amylases are found in the salivary glands that secrete the enzyme in the mouth and the pancreas, which secretes the enzyme in the small intestine. It hydrolyzes the a-(1-4) glycosidic bonds in the starch molecule leading to the production of maltose, maltotriose, maltotetraose, maltodextrins, and glucose . For its part, a-glucosidase is found on the luminal surface of enterocytes and is secreted in the small intestine. It is a key enzyme that catalyzes the hydrolysis of disaccharides (maltose and sucrose) into monosaccharides (glucose and fructose) and acts predominantly on a-amylase digestion products, rapidly converting them to glucose. Likewise, a-glucosidase can hydrolyze a-(1-6) bonds, which cannot be attacked by a-amylase, removing dextrins and allowing starch digestion to complete . 3.2.3. Diabetes Pharmacological Therapy Diabetes management includes glycemic control, reducing body weight, changes in lifestyle, prevention of micro and macrovascular damage, and others. Glycemia in type 2 diabetes patients can be controlled by pharmacological therapy. Four main groups of antidiabetic drugs act through different mechanisms: (i) biguanides: reduce gluconeogenesis in the liver (e.g., metformin); (ii) insulin secretagogues: stimulate insulin secretion of the pancreas (e.g., sulfonylureas); (iii) insulin sensitizers: improve the sensitivity of peripheral tissues to insulin (e.g., thiazolidinediones); and (iv) insulin or its analogs which provide insulin exogenously in the form of recombinant insulin . In the case of thiazolidinediones, they act via the activation of peroxisome proliferator-activated receptors (PPARs), decreasing insulin resistance and regulating adipocyte differentiation. For instance, biguanides, such as metformin, act by activating adenosine monophosphate-activated protein kinase (AMPK), which plays a significant role in energetic balance, insulin signaling, and metabolism of fats and glucose . Additionally, metformin affects the translocation of GLUT4 in insulin-targeted cells. GLUT4 is an ATP-independent glucose transport protein prevalent in adipose and muscle tissues and enhances glucose uptake. Metformin also activates AMPK phosphorylation in adipose and muscle tissues; this mechanism compromises phosphorylation of insulin receptor substrate 1 (IRS-1) Ser789, which, via cascade signaling, activates phosphoinositide 3 kinase/protein kinase B (PI3K/PKB) signaling, thus increasing blood glucose balance and decreasing insulin resistance. In adipocytes, AMPK activation inhibits lipogenesis while enhancing energy consumption, leading to an anti-obesity effect . Both AMPK activators and PPARs ligands regulate glucose homeostasis and decrease insulin resistance in adipose tissue . Control of postprandial hyperglycemia is an essential factor in diabetes treatment. Currently, there are three main oral antidiabetic drugs: acarbose, miglitol, and voglibose, which regulate glucose availability for intestinal absorption by modifying carbohydrate digestion. All of these drugs are a-glucosidase inhibitors that reversibly and competitively reduce the hydrolytic activity of these enzymes, thereby regulating the availability of glucose for intestinal absorption and the speed and extent of postprandial hyperglycemia . Acarbose has been used as a pharmacological prescription to manage postprandial glucose. It has been reported that it can decrease diabetes progression by 25% . Drug combination therapeutic management has shown better results than drug monotherapy; therefore, acarbose and metformin treatment has been reported to improve effects on patients with T2D . However, acarbose has common gastrointestinal adverse effects, including abdominal pain, diarrhea, and bloating . These side effects result from maltose fermentation, accumulating due to a-glucosidase inhibition . The difference in the mechanism of action of acarbose to miglitol and voglibose is that the former reduces polysaccharides digestion in the upper small intestine. In contrast, the latter reduces disaccharide digestion, thus in the lower small intestine there is a higher polysaccharide content when consuming acarbose; with miglitol and voglibose, there is a higher disaccharide content in the lower small intestine . Postprandial hyperglycemia in nondiabetic people is a predictor of insulin resistance and cardiovascular disease. In the case of patients with T2D, it has a relationship with micro and macrovascular disease. Moreover, sharp long-term changes in blood insulin levels in normal individuals may cause insulin resistance in organs and tissues, a central mark of hyperglycemia and type 2 diabetes. Regulating postprandial hyperglycemia early is a feasible strategy for preventing and managing T2D . 3.2.4. EO as an Alternative to Pharmaceutical Drugs Hence, common pharmaceutical approaches in the management and treatment of T2D compromise AMPK activators, PPARs ligands, and a-amylase and a-glucosidase inhibitors, which moderate the metabolism of dietary carbohydrates . Nevertheless, undesirable effects are displayed by these treatments, which could be attenuated by EOs exerting antidiabetic effects (Table 2). In the case of carbohydrate-related enzymes, which regulate carbohydrate digestion and glucose absorption in the small intestine, it has been reported that partial inhibition of a-amylase and a-glucosidase by EO is a natural alternative in the control of T2D. In the study performed by Radunz et al. , among all the EOs evaluated, thyme offered the most significant a-glucosidase inhibition (98.9%), while sweet orange EO showed the most potently inhibitory effect in a-amylase (95.4%). Their major components, thymol and D-limonene, respectively, are thought to be responsible for inhibitory capacity. All EO evaluated in this study exhibited a better capacity for enzyme inhibition than acarbose, the conventional drug prescribed. Moreover, incomplete enzyme inhibition, and medium and high range inhibition for a-amylase and a-glucosidase, respectively, is proposed for clinical treatment since these ranges allow the control of T2D without compromising nutrients or glucose absorption in the small intestine. According to Rahali et al. , some important factors need to be considered respecting the biological activity of plant EO. Even though its chemical composition is responsible for conferring bioactivities, it is influenced by plant genotype, organ type, extraction type, phenological stage, and environmental conditions. Their study analyzed the chemical composition of different plant organs, such as leaves, flower buds, flowers, and fruits, in terms of the EO of Hertia cheirifolia, and how these differences influenced a-amylase inhibitory activities. It was reported that leaves and fruits EO possessed the highest activity of a-amylase inhibition with 8.32 and 8.84 mg Eq acarbose/g EO, respectively. In this regard, the study performed by Pavlic et al. evaluated different extraction techniques and experimental conditions in peppermint leaves. Extraction methods included conventional hydrodistillation (HD), microwave-assisted hydrodistillation (MWHD), soxhlet extraction (SOX), ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE), and supercritical fluid extraction (SFE). HD and MWHD were applied to obtain the volatile fraction, that is, pure EO. It is expected that polyphenols and flavonoids were not present in these samples. The rest of the techniques aimed to recover lipophilic compounds, which are mixtures of volatile and non-volatile lipids. Its chemical composition varied depending on the extraction method since some monoterpene hydrocarbons (a-pinene, camphene, myrcene, and terpinolene) were absent in SOX, MAE, and UAE. For instance, SFE allows the extraction of terpenoids (oxygenated compounds) and other lipophilic bioactive compounds. Results of this study showed that peppermint EO, obtained by HD and MWHD, was the most potent a-amylase inhibitor, with an activity range of 1.24-1.76 ACEs/g. However, EOs did not exhibit a-glucosidase inhibition, while most lipophilic extracts were potent inhibitors with a 57.96-58.89 mmol ACEs/g activity range. Studies in animals have demonstrated that lemon balm EO has antihyperglycemic effects. The study carried out by Chung et al. demonstrated that supplementation to mice fed with lemon balm EO showed a decrease in glucose concentration and an increment in glucose tolerance. These results indicated that lemon balm EO stimulates glucokinase (GCK) activity and inhibits glucose-6-phosphatase (G6Pase) activity in the liver of mice. The former is stimulated by insulin and enhances glucose consumption and uptake in the liver, while the latter controls hepatic gluconeogenesis and glucose output in the liver; it is inhibited by insulin. When its activity is reduced, it decreases hepatic glucose production. As presented in Table 2, some EO exhibited a lower carbohydrate-enzymatic-related inhibition activity when using acarbose as a positive control . However, the side effects of synthetic drugs used to treat obesity and diabetes are not expected to happen with natural compounds like EO. foods-12-01079-t002_Table 2 Table 2 Studies evaluating the effect of essential oils (EO) on the prevention and treatment of diabetes. Essential Oil (EO) Study Details Experimental Findings Reference Clove, thyme, oregano, and sweet orange Enzymatic assay--EO were extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were assessed. Experimental concentrations for each EO were 250 mg/mL. Acarbose was used as a positive control. a-amylase inhibition Clove, thyme, oregano, sweet orange EO, and acarbose inhibited 93.1, 81.3, 81.4, 95.4, and 73.5% of a-amylase activity, respectively. a-glucosidase inhibition Clove, thyme, oregano, sweet orange EO, and acarbose inhibited 75.5, 98.9, 50.5, 37.3, and 34.5% of a-glucosidase activity, respectively. Wild mint (Mentha longifolia var. calliantha) Enzymatic assay--EO was extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition assays were assessed using 3,5-dinitrosalisylic acid (DNS) and p-nitrophenyl-a-D-glucopyranoside (pNPG) methods, respectively. Enzymes' inhibitory activity was expressed as equivalents of acarbose (ACEs). a-amylase inhibitory activity: 2.74 mmol ACEs/g EO a-glucosidase inhibitory activity: 5.62 mmol ACEs/g EO Hertia cheirifolia Enzymatic assay--EO from leaves, flower buds, flowers, and fruits were extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase inhibition assay was assessed using the DNS method. Results were expressed as equivalent acarbose per gram of EO (ACEs). a-amylase inhibitory activities in different plant organs: Leaves: 8.32 mg ACEs/g EO Flower buds: 2.75 mg ACEs/g EO Flowers: 5.85 mg ACEs/g EO Fruits: 8.84 mg ACEs/g EO Nepeta curviflora Enzymatic assay--EO was extracted utilizing a microwave ultrasonic apparatus. a-amylase and a-glucosidase inhibition assays were assessed using DNS and pNPG, respectively. Experimental concentrations for a-amylase assay were 10, 50, 70, 100, and 500 mg/mL, while for a-glucosidase they were 100, 200, 300, 400, and 500 mg/mL. The highest inhibitory percentage for a-amylase was 65.8%, achieved with a concentration of 500 mg/mL. However, at the same concentration, acarbose presented a higher inhibitory activity (72.54%). Nepeta curviflora EO IC50 in this assay was 45.7 mg/mL. In comparison, acarbose IC50 was 28.84 mg/mL. In the case of a-glucosidase, the highest inhibitory percentage was 92.72% with a concentration of 500 mg/mL. It had a slightly higher inhibitory activity than acarbose at the same concentration (92.28%). Nepeta curviflora EO IC50 in this assay was 54.9 mg/mL. In comparison, acarbose IC50 was 37.15 mg/mL. Oliveria decumbens (OD), Thymus kotschyanus (TK), Trachyspermum ammi (TA), and Zataria multiflora (ZM) EO Enzymatic assay--EOs were extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were assessed. a-amylase inhibition OD IC50: 223 mg/mL TK IC50: 229 mg/mL TA IC50: 218 mg/mL ZM IC50: 216 mg/mL Acarbose IC50: 126 mg/mL a-glucosidase inhibition OD IC50: 220 mg/mL TK IC50: 238 mg/mL TA IC50: 212 mg/mL ZM IC50: 219 mg/mL Acarbose IC50: 139 mg/mL For both assays, all EOs similarly inhibited enzymes but at lower levels than acarbose. Cedrus libani Enzymatic assay--EO from wood, leaves, and cones was extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase inhibition colorimetric assay (DNS) was performed. Experimental concentrations range from 1 mg/mL to 0.1 mg/mL. Wood EO IC50: 0.14 mg/mL Cone EO IC50: >1 mg/mL Leaves did not demonstrate inhibition. Orange and lemon peels EO Enzymatic assay--EOs were extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were assessed. Experimental concentrations for each EO were 0-16 mg/mL. a-amylase inhibition Orange peel IC50: 11.51 mg/mL Lemon peel IC50: 8.16 mg/mL Acarbose IC50: 7.45 mg/mL a-glucosidase inhibition Orange peel IC50: 11.53 mg/mL Lemon peel IC50: 7.56 mg/mL Acarbose IC50: 8.44 mg/mL Lemon peel EO exhibited the highest inhibitory effects in both enzymes. The a-glucosidase inhibition assay has a higher inhibitory effect than acarbose. Black pepper Enzymatic assay--EO was extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were performed. Experimental concentrations for each EO were 0-120 mL/L. a-amylase inhibition IC50: 86.06 mL/L a-glucosidase inhibition IC50: 68.29 mL/L Black pepper EO showed more potent inhibitory activity in a-glucosidase than in a-amylase. Peppermint (Mentha piperita L.) Enzymatic assay--different extraction methods for EO: conventional hydrodistillation (HD); microwave-assisted hydrodistillation (MWHD); soxhlet extraction (SOX); ultrasound-assisted extraction (UAE); microwave-assisted extraction (MAE); and supercritical fluid extraction (SFE). a-amylase and a-glucosidase inhibition colorimetric assays were assessed. a-amylase inhibitory activity range: 1.24-1.76 mmol ACEs/g a-glucosidase inhibitory activity range: 57.96-58.89 mmol ACEs/g Lavender In vivo--15-weeks-old adult male Wistar rats (220-230 g) were divided into four groups: (1) control (nondiabetic rats) treated with 0.9% NaCl; (2) alloxan-induced diabetic rats treated with 0.9% NaCl; (3) nondiabetic rats treated with EO (50 mg/kg body weight); and (4) alloxan-induced diabetic rats treated with EO (50 mg/kg body weight). Treatments lasted 15 days. Serum biochemical parameters were determined. EO was extracted by hydrodistillation for 3 h using a Clevenger apparatus. There was a significant increase in blood glucose levels within alloxan-induced diabetic rat groups; however, treatment with EO significantly reduced this parameter. Origanum vulgare subsp. vulgare and subsp. hirtum Enzymatic assay--EO were extracted by hydrodistillation for 5 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were performed. For a-amylase inhibitory activity, Origanum vulgare subsp. vulgare and subsp. hirtum exhibited similar activity (0.13 and 0.14 mmol ACEs/g oil). The highest a-glucosidase inhibitory activity was achieved by Origanum vulgare subsp. vulgare with 6.04 mmol ACEs/g oil. Clove bud Enzymatic assay--EO was extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-amylase and a-glucosidase inhibition colorimetric assays were performed. Experimental concentrations were 0, 40, 80, 120, and 160 mL/L. Acarbose was used as a positive control. 35-78% inhibition of a-amylase. 58-90% inhibition of a-glucosidase. Clove bud oil EC50 for a-amylase: 88.89 mL/L Clove bud oil EC50 for a-glucosidase: 71.94 mL/L Acarbose EC50 for a-amylase: 18.63 mg/mL Acarbose EC50 for a-amylase: 21.1 mg/mL Acarbose exhibited higher inhibitory activity for both enzymes compared to clove bud EO. Cinnamomum zeylanicum (CZ), Psiadia arguta (PA), Psiadia terebinthina (PT), Citrus grandis (CGp), Citrus hystrix (CH), and Citrus reticulata (CR) Enzymatic assay--EO were extracted by hydrodistillation for 3 h using a Clevenger apparatus. a-glucosidase inhibition assay was assessed using the pNPG method. The inhibition type was determined using the Lineweaver-Burk linearization method. Inhibition % at 500 mg/mL for CH, CR, CGp, CZ, PT, and PA was 85.49, 81.15, 83.19, 93.71, 40.12, and 76.45, respectively. IC50 (mg/mL) values are 276.7, 169.9, 240.6, 64.52, 14,584, and 313, respectively. In the case of inhibition %, all EO exhibited higher activity than acarbose (51.39%). CZ was demonstrated to be the most potent inhibitory activity compared to acarbose. For all EOs, the inhibition type was uncompetitive, except for CZ, which has a competitive inhibition type. Lemon balm (Melissa officinalis) In vivo--15-weeks-old male C57BL/KsJ-db/db (db/db) mice were fed with standard chow or chow supplemented with lemon balm EO. Treatments lasted for six weeks. Serum biochemical parameters were monitored. Oral glucose tolerance tests were assessed, and serum insulin was monitored. EO was extracted by steam distillation. Plasma glucose levels were reduced (up to 64.6%). There was an improvement in glucose tolerance with lemon balm EO administration. Serum insulin was increased. Serum biochemical parameters (total cholesterol, TG and HDL-cholesterol) were reduced. Phoebe bournei (Hemsl.) Yang In vitro--3T3-L1 preadipocytes were differentiated with 40 mg/mL of leaf EO. After 24 h, glucose consumption activity was determined by measuring the medium glucose concentration. Promotion of glucose uptake in adipocytes. Rosemary In vivo--15-weeks-old adult male Wistar rats (220-225 g) were divided into four groups: (1) nondiabetic rats treated with distilled water; (2) alloxan-induced diabetic rats treated with distilled water; (3) nondiabetic rats treated with EO; and (4) alloxan-induced diabetic rats treated with EO. Treatments lasted 15 days. Blood glucose level was measured. EO was extracted by hydrodistillation for 3 h using a Clevenger apparatus. Blood glucose level was higher in alloxan-induced diabetic rats; however, treatments with EO corrected this hyperglycemia. Rhaponticum acaule (L) DC Enzymatic assay--EO was extracted by hydrodistillation for 5 h using a Clevenger apparatus. a-glucosidase inhibition assay was assessed using the pNPG method. The inhibition type was determined using the Lineweaver-Burk method. Rhaponticum acaule EO IC50: 6.7 +- 0.10 mg/mL Acarbose IC50: 280 +- 0.10 mg/mL EO demonstrated high inhibition activity compared to acarbose. Mixed inhibition type. Salvia officinalis L. EO was extracted by hydrodistillation for 2 h using a Clevenger apparatus. Enzymatic assay--a-amylase inhibition assay was assessed using the CNPG3 method. Experimental concentrations were 50, 100, and 200 mg/mL. In vivo--Male Wistar rats (180-200 g) were induced into diabetes with alloxan and divided into five groups: (1) nondiabetic rats treated with water (control); (2) nondiabetic rats treated with EO; (3) alloxan-induced diabetic rats treated with water; (4) alloxan-induced diabetic rats treated with Glymepiride; and (5) alloxan-induced diabetic rats treated with EO. Fasting blood glucose, a-amylase, and hepatic glycogen content were measured. Treatments were daily and orally administered. EO IC50: 38 mg/mL Acarbose IC50: 14.9 mg/mL EO exhibited less inhibition activity than acarbose. EO administration to diabetic rats reduced serum a-amylase activity and fasting blood glucose. Moreover, liver glycogen storage was enhanced by 44%. Langerhans islets were restored to normal size in diabetic rats. 3.3. Other Bioactivities of EO Related to Metabolic Syndrome Comorbidities: Neuroprotection Diabetes is a risk factor for developing Alzheimer's disease (AD) and other types of dementia . In this context, untreated diabetes can cause memory disorders . Because of chemical properties or monoterpenes, they can travel quickly across the single epithelial nasal mucosa, be incorporated into blood circulation, and cross the blood-brain barrier. For those reasons, aromatherapy with EO has been an alternative to AD treatment . Furthermore, cholinesterase inhibitors are the target for preventing and treating AD. These inhibitors impede the cholinergic deficit associated with cognitive dysfunction . Two principal cholinesterases, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), are associated with AD . An increase in these cholinesterases leads to reduced levels of acetylcholine neurotransmitter, which is involved in memory and learning . For instance, AChE is related to b-amyloid plaques and neurofibrillary tangles (NFT) . This inhibition promotes an increase in the level of acetylcholine in neuronal synapsis, which leads to improved stimulation of the cholinergic receptors . Wild mint EO has been evaluated as a potential cholinesterase inhibitor. The study performed by Asghari et al. showed that wild mint (Mentha longifolia var. calliantha) EO has an intense AChE activity. Enzymes' inhibitory activity was expressed as equivalents of galantamine (GALAEs). In the case of AChE, IC50 was 1.82 mg GALAEs, and 2.57 mg GALAEs for BChE. This study mentioned that oxygenated monoterpenes present in the EO were accountable for neuroprotection since 1,8-cineol, the most abundant component, and carvacrol have been reported to be acetylcholinesterase inhibitors. The study by Sarikurkcu et al. suggested that Origanum species are recommended for AD treatment. It was reported that O. vulgare subsp. vulgare and O. vulgare subsp. hirtum exhibited a similar inhibitory action on both AChE and BChE. It is thought that inhibitory properties are due to the high concentration of thymol and carvacrol in O. vulgare subsp. vulgare, while for O. vulgare subsp. hirtum it is because of the high concentration of linalool. Another study conducted by Aumeeruddy-Elalfi et al. proposed that citrus species such as Citrus grandis (CGp), Citrus hystrix (CH), and Citrus reticulata (CR) have comparable activity as galantamine, a common drug used to treat mild to moderate AD. These EO are categorized as an uncompetitive type of inhibitor since there is a decrement in Km and Vmax parameters in their presence. Discovering the inhibition type would be helpful for further investigations to achieve, so as to elucidate the interaction of the EO with cholinesterases. 4. Bioavailability and Mechanisms of Action of EO EOs are a complex mixture of volatile and non-volatile compounds, such as hydrocarbons, fatty acids, sterols, carotenoids, waxes, and flavonoids. In the case of volatile constituents, there are hydrocarbons (e.g., pinene, limonene, bisabolene), alcohols (e.g., linanol), acids (e.g., benzoic acid), aldehydes (e.g., citral), cyclic aldehydes (e.g., cuminal), ketones (e.g., camphor), lactones (e.g., bergaptene), phenols (e.g., eugenol), phenolic ethers (e.g., anethole), oxides (e.g., 1,8 -cineole), and esters (e.g., geranyl acetate) . The biological properties of EO are commonly attributed to the main molecules at the highest concentrations. However, it is thought there is a synergistic relationship between the molecules in the EO. Hence, the other minor molecules could regulate the activity of major components . It has been suggested that crude plant extract administration of EO is better for their bioavailability than purified compounds . Investigation about the absorption, distribution, and metabolism of EO is necessary to extrapolate in vitro to in vivo studies results since therapeutic activities depend on the availability of EO compounds reaching specific target organs . Some studies about the bioavailability and pharmacokinetics of monoterpenes present in EO have been published recently. For instance, oral administration of thymol and carvacrol, which are monoterpene aglycones, have a slow absorption in the bloodstream. Monoterpene aglycones have a nonpolar ending that signifies they can easily travel across cell membranes; nevertheless, their hydrophobicity is challenging. Therefore, future studies are needed to understand these compounds' receptor interaction, activity, and specificity to elucidate their therapeutic potential . It has been reported that EO can be easily absorbed via pulmonary, dermal, or oral administration . Regarding the pulmonary mechanism of action, smells stimulate the olfactory bulb, a part of the limbic system involved in behavioral and emotional responses, which comprises the hippocampus, amygdala, and hypothalamus. When an aromatic compound binds to cilia in olfactory receptor cells, they activate adenylate cyclase, promoting the increment in cAMP concentration. This second messenger binds to Ca2+ channels, causing the entrance of Ca2+ into the cell and depolarizing the cell membrane. Moreover, intracellular Ca2+ activates and causes further membrane depolarization. These signals produce action potentials that are transferred to the glomeruli in the olfactory bulb, which eventually will be transmitted to the limbic system and cerebral cortex . The hypothalamus oversees the autonomic nervous, endocrine, and immune systems. For instance, the autonomic nervous system (ANS) has three different divisions in terms of anatomy: sympathetic (SNS); parasympathetic (PNS); and enteric (ENS) nervous systems. In this way, studies in rats have demonstrated that some fragrances enhance sympathetic nervous activity and suppress parasympathetic activity, while others have the opposite effect on the ANS . Olfactory stimulation studies done by Hong et al. , Batubara et al. , and Shen et al. proved that citronella, grapefruit, and patchouli EO reduce body weight, as well as food intake, appetite, and plasma biochemical parameters (glucose, cholesterol, triglycerides), via sympathetic nerve stimulation in brown adipose tissue, since it promotes thermogenesis (heat production) that converts fatty acids into fuel (energy consumption). This heat generation has been reported to reduce body fat since there is an increment in mitochondria respiration and fatty acid oxidation related to AMPK activation or adipogenesis inhibition. Also, heat production can be enhanced through uncoupling protein 1 (UCP1) activation; consequently, energy consumption and body temperature are raised by uncoupling oxidation from ATP production in mitochondria. In the case of grapefruit EO, in addition to what was previously mentioned, it was also reported that it suppresses parasympathetic gastric nerve activity; as a result, it inhibits nutrient digestion and absorption. Pulmonary absorption depends on subjects' breathing mechanisms, mucosal compound deposition, metabolism, and the type of compound evaluated. Elimination of EO occurs mainly exhaled as CO2 . Regarding dermal absorption, EO can easily be absorbed due to their lipophilic character and can easily penetrate through the skin into the bloodstream. For instance, the absorption rate in cells increases with their hydrophobicity and decreases as their molecular weight increases. Some studies have reported that after dermal administration of linalyl acetate, terpinen-4-ol, citronellol, and a-pinene, they reached their highest level 15-20 min after application and decreased gradually for 2 h . The stratum corneum (SC) is the top layer of the epidermis and is a barrier to the penetration of substances. SC mainly consisted of lipids and protein keratin. EOs have been used as penetration enhancers (PE) in transdermal drug delivery systems. The role of PE is to temporarily provoke a reversible reduction in the barrier function of SC in order to allow safe and effective drug delivery via skin. EO as PE can achieve this through different mechanisms such as (i) intracellular lipid structure rearrangement between corneocytes in SC, (ii) intracellular proteins conformational modifications due to interactions, (iii) enhance drug partitioning into SC, and (iv) enhancement of desmosome connections between corneocytes or metabolic activity alteration within the skin. In this way, EOs and their active constituents can penetrate the epidermis by two different pathways: (1) transcellular (intracellular) permeation across the corneocytes of SC by appendage penetration through hair follicle, sebaceous and sweat glands; and (2) intercellular permeation through intercellular spaces of the SC. Briefly, a drug has to travel across continuous layers of intracellular lipids and proteins to reach blood circulation via the skin . When orally administered, EOs interact with digested food. The kinetic rate depends on digestive enzymes to hydrolyze EO compounds from the fatty acid linkages. In the case of terpenoids and steroids present in EO, they can be digested in the small intestine along with other lipids due to their lipophilic properties. On the other hand, hydrophilic EO compounds, such as polyphenols, flavones, flavanols, lignans, and aromatic acids, are bound to saccharides metabolized in the small intestine. Aglycones that are not absorbed cross to the liver, where they are absorbed and enzymatically degraded. Free hydrophilic molecules are transported into enterocytes via passive diffusion or active transport in the duodenum . Intravenous administration suggests that the elimination half-life of EO in humans is about one hour. However, it has been reported that the highest concentration of active compounds from EO is two hours after administration, and after five hours, the substances have already been effectively eliminated from the bloodstream. Evidence shows that the half-life of carvacrol, thymol, eugenol, and trans-cinnamaldehyde was between 1.84 and 2.05 h. Elimination of EO occurs mainly by renal secretion in the form of glucuronides or exhaled as CO2. EO are non-toxic molecules since they are fast and quickly metabolized; thus, they are not accumulated in the organism and are excreted from the body with urine and feces . 5. EO as Food Preservatives EO have been cataloged as Generally Recognized as Safe (GRAS) for food additives and flavorings. Some EO that are GRAS include basil, cinnamon, clove, coriander, ginger, lavandin, menthol, nutmeg, oregano, rose, sage, and thyme . There is active research on in vitro study of the antimicrobial and antioxidant activities of EO . In the following sections, some studies are presented as novel developments in incorporating EO in different food systems . Active packaging aims to extend food shelf-life and maintain or improve the packaged food's properties. Unlike conventional food packaging, active packaging interacts with the product by incorporating compounds that could be released into the food or absorb substances responsible for the deterioration of the product. Incorporating EOs and their components into food packaging has been reported to increase food shelf-life since they have exhibited antimicrobial and antioxidant activities that can eradicate the presence of pathogen microorganisms and reduce lipid oxidation. Hence, EOs are an alternative to reduce or replace synthetic additives . 5.1. Antimicrobial Properties Several studies demonstrated the antimicrobial activity of EO in food matrices. EO compounds can disrupt the bacterial membrane, damage their metabolic pathways, and prevent the synthesis of bacterial toxins . Nevertheless, Gram-positive bacteria are more vulnerable to attaining antimicrobial effects, since hydrophobic molecules can easily pass through the cell membrane. In contrast, the outer membrane of Gram-negative bacteria can act as a barrier due to lipopolysaccharides' presence, so they are more resistant toward hydrophobic compounds like those presented in EO; however, some phenolic compounds present in EO (i.e., thymol, eugenol, and carvacrol) can interfere with the cell wall outer membrane . Due to their low molecular weight and lipophilic properties, EO can easily pass through the cell membrane and can inhibit bacteria growth by disrupting cell membranes, enzyme systems, and cell division, preventing biofilm formation, inducing bacterial membrane to produce clumps and auto-aggregation, hyperpolarization of cell membrane, altering lipid profile by formation of fatty acid hydroperoxidases caused by the oxygenation of unsaturated fatty acids within the cytosol, and by formation of cell membrane channels which cause leakage of ions, cellular material, and nucleic acids. Cell damage can lead to disruption of proton motive force and can cause ATP loss or affect ATP synthesis, changing the conformation of ATPase and inhibiting the expression of ATPase-related subunits interfere . For instance, it has been reported that Mentha species contain hydrogen peroxide which can damage biomolecules of microorganisms, such as proteins, lipids, nucleic acids, and carbohydrates . In terms of antimicrobial properties related to fungi, it has been reported that interaction of cinnamaldehyde, a major compound of cinnamon oil, with Aspergillus flavus caused elevated Ca2+ and ROS, decrease in mitochondrial membrane potential, release of cytochrome c, activation of metacaspase, and DNA damage. This compound increased the expression levels of apoptosis-related genes . Moreover, EO exert antifungal effects through cell wall disruption causing leakage of cellular contents; it is thought that this disruption is caused by interactions of EO with ergosterol, which is the principal sterol present in fungi cell membranes and which controls permeability and fluidity . Nonetheless, instead of synthetic antibiotics, EOs are commonly used in food systems as natural antiseptics to ensure food safety. The in vitro antimicrobial activity of particular EOs, such as oregano and thyme, against many Gram-positive and Gram-negative bacteria, yeasts, and molds has been thoroughly analyzed and documented . For example, Siroli et al. evaluated the efficacy of oregano and thyme essential oils for lamb's lettuce decontamination and compared it to the efficacy of chlorine. The results showed that by applying EO, a product shelf-life similar to that obtained with chlorine was achieved . Some studies reported by Ribeiro-Santos et al. demonstrated that low-density polyethylene films with linalool and methyl chavicol exhibited antimicrobial activities against Escherichia coli and Listeria innocua in Cheddar cheese packaging previously inoculated with those organisms. Moreover, another polyethylene film with cinnamon EO and cinnamaldehyde, inhibited the growth of fungi (Penicillium islandicum, Penicillium roqueforti, Penicillium nalgiovense, Eurotium repens, Aspergillus flavus, Candida albicans, Debaryomyces hansenii, and Zigosaccharomyces rouxii) and bacteria (Bacillus cereus) at 4% (w/w) of active compounds. In comparison, Listeria monocytogenes and Staphylococcus aureus were inhibited at 8% (w/w), and E. coli, Yersinia enterocolitica, Salmonella choleraesuise, and Pseudomonas aeruginosa at >10% (w/w). Furthermore, Masyita et al. mentioned that L. monocytogenes is one of the major pathogens responsible for diseases in humans and animals. They reported a study in which clove and cinnamon EOs were evaluated in ground beef. Results demonstrated that 10% clove EO could decrease the growth of L. monocytogenes. Additionally, it has been reported that eucalyptus EO reduces Saccharomyces cerevisiae in Orangina juice. 5.2. Antioxidant Capacity Antioxidant capacity exerted by EO is due to the double bonds present in alcohols, ethers, ketones, aldehydes, and phenolic compounds. Both terpenoid and phenylpropanoid families compromise phenolic compounds; these have high reactivity with peroxyl radicals, which are disposed of by hydrogen-atom transfer . In the case of food products, lipid oxidation is the primary source of oxidation which produces rancidity; the use of EO polyphenolic compounds (i.e., terpenoids and phenolic acids) can act as oxygen and free radical scavengers to reduce lipid oxidation . Some EO have been reported to exert in vitro antioxidant capacity. Routinary assays are used to measure radical scavenging properties against 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) and 2,2'-azinobis(3-ethylbenzothiazoline)-6-sulfonic acid radical cation (ABTS). These methods are commonly used in the food industry to evaluate the antioxidant activity of specific compounds within the food matrix. Radunz et al. evaluated the effect of clove, thyme, oregano, and sweet orange EOs using DPPH assay. Results exhibited that clove EO had the highest inhibition percentage (94.3%). The primary compound found in clove EO was eugenol, to which authors attributed the remarkable ability to interact with free radicals compared to the major components of the other EO evaluated. For instance, wild mint (Mentha longifolia var. calliantha) was evaluated by Asghari et al. using DPPH and ABTS radicals to determine the free radical scavenging ability of the EO. It was demonstrated that wild mint EO had moderate antiradical potential in DPPH assay (5.8 mmol TEs/g oil), in contrast to a very high potential in ABTS assay (186 mmol TEs/g oil), expressed as equivalents of standard antioxidant compound Trolox (TEs). It is thought that this strong antioxidant capacity is due to the principal monoterpenes present in the EO, such as 1,8-cineol, linalool, and carvacrol, which are capable of donating hydrogens. Moreover, two different species of oregano were evaluated by Sarikurkcu et al. , Origanum vulgare subsp. vulgare and subsp. hirtum. Besides performing DPPH and ABTS methods to measure radical scavenging, the b-carotene bleaching method was used to measure lipid peroxidation inhibition. In this assay, b-carotene is oxidized by radicals formed by linoleic acid oxidation in an emulsion, in which, eventually, the system loses its chromophore and is monitored spectrophotometrically. The results of this study exhibited that O. vulgare subsp. vulgare obtained 57.23 mg TEs/g oil for DPPH and 176.41 mg TEs/g oil for ABTS. This species exerted higher activity than that of O. vulgare subsp. hirtum in both assays. Due to differences in the chemical profile, the free radical capacity is influenced by the major components of the EO; in this regard, O. vulgare subsp. vulgare has a higher concentration of thymol and carvacrol (58.31 and 16.11%, respectively), which have been reported to be efficient scavengers of free radicals, as reported by Asghari et al. . In terms of the b-carotene bleaching method, it obtained similar results since O. vulgare subsp. vulgare is the better inhibitor of linoleic acid oxidation (99.89%) compared to O. vulgare subsp. hirtum (23.54%). Hence, O. vulgare subsp. vulgare can be helpful for the management of lipid oxidation in the food industry. Regarding the application of EOs as antioxidants in food products, there is active research in the meat industry to prevent oxidation reactions in meat and meat products. Studies reported by Pateiro et al. suggested that oregano EO added at a concentration of 3% w/w significantly reduced oxidation reactions in raw and cooked porcine and bovine ground meat., Sage EO was also evaluated in fresh pork sausages, and there was a protective effect against lipid oxidation; furthermore, it had a higher antioxidant value than synthetic BHT. However, these antioxidant properties can be converted into prooxidants at high concentrations. An example of this was a study in which 150 ppm of rosemary was added to meat, and inhibition of lipid and protein oxidation was achieved. However, at 300 and 600 ppm concentrations, it promoted oxidation reactions because of interactions with fatty acids or concentration of tocopherols present in the product. Hence, it is essential to consider doses and meat matrix components interactions since their activity depends on the concentration utilized. 6. Stability and Formulation of EO In active packaging, EOs are recommended to be introduced as micro or nanoemulsions. Incorporating EOs as micro or nanoemulsions prevents intense aroma . In this regard, several strategies exist to incorporate EO into packaging materials. These techniques include a direct addition into polymeric materials, incorporation into coatings, immobilization with substrates, trapping into physical carries, insertion into headspace, or micro/nanoencapsulation in carriers, followed by incorporation into food matrices . EOs are quite volatile and sensitive in certain conditions of illumination, temperature, and humidity, which are common during food processing. Therefore, researchers have used various encapsulation systems with different shell materials to protect EO from volatilization, oxidation, instability, and insolubility. The most common and effective encapsulation systems include liposomes, chitosan nanoparticles, cyclodextrin, silicon dioxide, nanoemulsions, solid lipid nanoparticles, nanofibers, and edible films. Furthermore, certain packaging methods, including food wraps and nanofibers, have also been proven to protect EO . Recently, Reis et al. published a review that addressed the conventional and most innovative encapsulation methods and the most relevant shell materials used in food systems. For instance, some essential factors have to be considered beforehand when selecting an appropriate encapsulation technique, such as desired particle size, shell materials' physical properties, the core material's solubility, controlled release, layer permeability, and costs. In this way, wall materials have to accomplish three different stages in order to be considered successful: (i) formation of a wall around the core; (ii) core components have to be kept inside the capsule without any release or degradation; and (iii) incorporation of the capsule in food systems and correct release of oil components. Encapsulation techniques are divided into two different categories: physical and chemical methods. Physical methods do not involve polymerization reactions, and microcapsule formation occurs mechanically. This classification includes extrusion, fluidization, lyophilization, solvent removal, spray drying, and supercritical fluid techniques. For its part, chemical methods involve polymerization reactions, and techniques include coacervation, ionic gelation, liposomes, and miniemulsion polymerization. Moreover, common shell materials used in food matrixes include polysaccharides (i.e., starch, dextrin, maltodextrin, modified starch, cyclodextrin, chitosan), gums (i.e., arabic gum, sodium alginate), proteins (i.e., whey, soy, casein, gelatin), cellulose (i.e., modified cellulose), and lipids (i.e., waxes, paraffin, fats) . There is a discussion about emulsification as an encapsulation technique or as a step before encapsulation since the latter guarantees an improvement in storage stability because droplets are immobilized in a solid matrix. At the same time, the former comprises a liquid wall material that could disfavor the core compounds' physical and chemical resistance and retention. Nevertheless, emulsification methods are divided into conventional methods (i.e., colloid mill, high-speed mixer, high-pressure homogenizer, ultrasonic homogenizer) and membrane emulsification methods. Some advantages regarding the membrane emulsification method as a novel technique are lower energy demand, low shear rates, lower temperature elevation, more control of droplet size, and ease of scaling up. However, some disadvantages of this method are fouling phenomena on the membrane surface and pores, the membrane's short lifetime, and more resistance in mass transfer regarding the membrane. Research has shown that nanoencapsulation boosts the preservative potential of plant essential oils in vitro and in food systems. For instance, Jamil et al. investigated the antimicrobial efficacy of cardamom oil encapsulated in chitosan-based nanoparticles. The results demonstrated that the nano-encapsulated EO exhibits excellent antimicrobial potential against Escherichia coli and Staphylococcus aureus . This encapsulation system has been used to protect EO effectively and improve their functional performance in food systems . Amiri et al. used conventional nanoemulsion and fortified nanoemulsion as delivery systems for Zataria multiflora in corn starch and analyzed its effect on the sensory properties of ground beef patties. The results showed that the fortified nanoemulsion had the highest scores for all the sensory parameters, while the control showed the lowest scores . Another study by Viacava et al. also analyzed the effect nanoencapsulation has on sensory attributes. The researchers studied the impact of free and b-cyclodextrin encapsulated thyme EO on the quality of minimally processed Romaine lettuce. The results demonstrated that the lettuce treated with the nano-encapsulated EO exhibited better organoleptic quality scores than the control and free EO-treated lettuce . Therefore, the authors concluded that nanoencapsulation could help improve the organoleptic attributes of food items. Other delivery systems, including surfactant-based systems, films, fibers, and oleogels, are being investigated for their effectiveness. For instance, Chen & Yang have used Quillaja saponin, a natural triterpene, to stabilize orange oil via oleogel . The authors concluded that the oleogels with high gel strength had good thixotropic recovery and reversibility to reconstituted emulsions. Therefore, oleogels show great potential for food, cosmetics, and pharmaceutical applications . Quillaja saponin has also been used by Sedaghat Doost et al. to stabilize thymol nanoemulsions. With this system, the authors could create thymol emulsions with long-term stability that contained a relatively low content of green solvents. Furthermore, the authors reported that, compared to free thymol, emulsification improved its antioxidant activity. Another innovative strategy has been investigated by Silva et al. , as they encapsulated coriander essential oil in cyclodextrin nanosponges to achieve a controlled oil release. The authors reported that cyclodextrin polymers can effectively incorporate and release coriander essential oil and that including this oil inside the nanosponge improves the crystallinity of the polymer, which leads to a more effective controlled release. For instance, in a study performed by Siahbalaei et al. , some EO (Oliveria decumbens, Thymus kotschyanus, Trachyspermum ammi, and Zataria multiflora) were individually encapsulated into a gelatin-pectin nanocomposite consisting of gelatin (7 g), pectin (3 g), 100 mL acetic acid (60%), glycerol (100 mg/g of total polymer), and glutaraldehyde (10 mg/g of total polymer), resulting in a 500 to 700 nm size range. Each composite displayed several bioactivities such as glucose autoxidation inhibition, lipid peroxidation inhibition, protein oxidation, glycation inhibition, and a-amylase and a-glucosidase inhibition activity. 7. Conclusions EOs have been demonstrated to have anti-obesity, antidiabetic activities, and neuroprotective effects. They can be used as a natural alternative to treat these disorders even though further investigation is needed to elucidate the interaction between EO and metabolic pathways involved in developing these diseases at both the cellular level and in living organisms. EO are an attractive alternative for substituting synthetic additives since they show antimicrobial and antioxidant activities that extend food products' shelf-life and guarantee food safety to consumers. EO micro/nanoencapsulation is a novel technological approach for their stabilization and incorporation into different food systems. Nevertheless, the interaction of these compounds with food matrices needs to be studied in detail before their incorporation to obtain the expected results. The scientific information herein presented demonstrates the dual role of EO in preventing and treating metabolic syndrome-related disorders and their well-demonstrated role as antioxidant and antimicrobial food additives. This dual role makes EO excellent candidates to formulate dietary supplements and functional foods. Over the course of this review, there are several research gaps and perspectives in the field that have been identified and need to be further explored. The first of these is that there are several factors, with respect to the raw material used, that must be required when carrying out in vitro or in vivo studies. Among them are the quality, the extraction method, the part of the plant used, and its stage of maturation. Since, depending on this, primary compounds may vary, so too will bioactive properties be impacted as well. Another point to consider is the nanoencapsulation of EO. Besides preserving and/or enhancing bioactivity, it needs to ensure a benefit in the organoleptic properties of food systems, such as flavor, color, aroma, and texture, so that in this way, a high consumption of functional foods fortified with EO is guaranteed. Furthermore, studies about synergistic combinations of EO to exert therapeutical and technological properties in food systems need to be performed, especially regarding the quality and quantity used of each one in food matrixes, in order to offer the promised bioactivity. In this regard, novel technological approaches to enhance EO stability in food systems deserve more research to scale up processes in an industrial manner and, in this way, to overcome current health problems. Author Contributions Conceptualization, E.L.C.-D. and D.A.J.-V.; investigation E.L.C.-D. and D.A.J.-V.; literature search E.L.C.-D.; writing--original draft preparation, E.L.C.-D.; writing--review and editing, E.L.C.-D. and D.A.J.-V. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Essential oils (EO) absorption mechanisms. (A) Olfactory administration. Odor compounds bind to cilia in olfactory receptor cells, which activates G protein-coupled receptors to depolarize cell membranes and promote signal transduction to the limbic system and cerebral cortex. (B) Dermal administration. EO can penetrate the stratum corneum and reach the bloodstream through transcellular or intercellular permeation. (C) Oral administration. 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PMC10000520 | Along with the fact that classical Hodgkin lymphoma (cHL) in older adults is frequently considered biologically different from cHL in younger patients, its most distinctive feature is its dismal clinical outcome due to the decreased effectiveness and greater toxicity of therapies. Although strategies to mitigate specific toxicities (e.g., cardiological and pulmonary) have obtained some results, in general, reduced-intensity schemes, proposed as an alternative to ABVD, have proved to be less effective. The addition of brentuximab vedotin (BV) to AVD, especially in a sequential scheme, has demonstrated good efficacy. However, the problem of toxicity persists even with this new therapeutic combination, with comorbidities remaining an important prognostic factor. The adequate stratification of functional status is necessary to distinguish between those patients who will benefit from full treatment and those who will benefit from alternative strategies. A simplified geriatric assessment based on the determination of ADL (activity of daily living), IADL (instrumental ADL), and CIRS-G (Cumulative Illness Rating Scale--Geriatric) scores is an easy-to-use tool that permits adequate patient stratification. Other factors of considerable impact on functional status such as sarcopenia and immunosenescence are currently being studied. A fitness-based treatment choice would also be very useful for relapsed or refractory patients, a more frequent and challenging situation than that is found in young cHL patients. Hodgkin lymphoma elderly comorbidity functional status geriatric assessment brentuximab vedotin This review received no external funding. pmc1. Epidemiology and General Characteristics Classical Hodgkin lymphoma (cHL) in older adults is seen in the second peak of the incidence of cHL. Although there is no shared definition of "older patient" in the cHL setting, most studies agree that a patient >=60 years of age is "older". If we consider only these patients, cHL in older adults is a rare disease, accounting for about 20% of all cases of cHL, with a median age at diagnosis of around 70 years . Despite accounting for about one-fifth of all new diagnoses of cHL, older patients are under-represented in clinical trials, which typically include less than 5-10% of patients aged >=60 years. This may be due to the "biological diversity" of cHL in older adults as well as to the difficulty of treating these patients, who have poor tolerance and a reduced response to first-line therapy . Furthermore, this under-representation is very unlike what occurs in the setting of diffuse large B-cell non-Hodgkin lymphoma (DLBCL), for example. 2. Is cHL in Older Adults a Biologically Different Disease? With regard to the biological diversity of the disease, many studies have observed the characteristics of the presentation of cHL in older patients that are very specific to this age group and that are more evident than those observed in younger patients. The most relevant clinical features at presentation are primarily related to the higher incidence of advanced stages and to the corresponding reduced incidence of localized stages with mediastinal bulk . In addition, many older patients present with systemic symptoms of disease and elevated erythrocyte sedimentation rate (ESR) levels . Finally, a greater proportion of older patients present with reduced performance status, although it is not easy to assess to what degree this parameter is linked to their more aggressive disease and/or to other age-related organ or functional impairments . In terms of histology, some authors have observed a higher incidence of the mixed cellularity subtype (classic Hodgkin/Reed-Sternberg cells in a diffuse mixed inflammatory background), in some cases finding it even more frequently than nodular sclerosis, by far the most diagnosed subtype of cHL in younger patients . From a cytogenetic point of view, older patients with cHL more frequently present with the overexpression of chromosomal region 9p24.1 due to either polysomy, copy gain, or amplification . It is noteworthy that the 9p24.1 region contains both the PD-L1 and PD-L2 genes, resulting in the overexpression of both proteins in Hodgkin cells and their microenvironment, as PD ligands are the therapeutic targets of effective new drugs such as nivolumab or pembrolizumab. From a biological point of view, many authors have reported more frequent Epstein-Barr virus (EBV) infection of Reed-Sternberg cells , identified mostly through in situ hybridization methods commonly implemented in clinical practice. It is not entirely clear whether latent EBV infection plays a primary oncogenic role in cHL, although some authors support it . Nevertheless, the prognosis of patients with EBV-positive cHL appears to be worse than that of EBV-negative patients, mainly due to a reduced response to first-line therapy, which tends to translate into reduced survival . In general, some clinical and biological features can be observed that point to cHL being more aggressive in older patients than in younger patients. However, it should be emphasized that this evidence is drawn mostly from retrospective or population-based studies and, more generally, refers to a therapeutic paradigm that is not entirely current. There is, therefore, a need for large prospective studies in this setting aimed at extensively evaluating the prognostic factors (both lymphoma-related and /or therapy-related) within the current therapeutic scenario. 3. The Main Problem: Worse Outcome Compared with That in Younger cHL Patients The greatest problem in the treatment of cHL in older patients is that their outcome is considerably worse than that usually observed in younger patients. Certainly, the overall outcomes for patients with cHL lymphoma have improved over time, as better supportive care and, more recently, better salvage and even first-line therapies have become available. This improvement has also benefitted older cHL patients, with the possible exception of those aged > 80 years, as reported in some studies. However, even with this improvement, the prognosis of cHL in older patients remains markedly poorer than that of cHL in younger patients and considerably different from that of the general age-matched population . The possible greater biological aggressiveness of the disease, as outlined in the previous section, may be one of the causes of this different trend. In fact, it has been well documented that older patients tend to have a lower response rate to first-line therapy and a greater tendency to relapse. However, other factors may explain this inferior outcome: a certain tendency towards therapeutic inertia, the greater interval between diagnosis and treatment, the use of reduced or less effective therapeutic regimens, the greater toxicity experienced by older patients with traditional therapy regimens, and the tendency to treat them in smaller or less experienced centers . Of these factors, the most studied is therapy-related toxicity in older patients. Ever since ABVD became the paradigm of first-line treatment of cHL, it has been observed that this course of therapy is decidedly more toxic in this patient population. In fact, older patients have more marked hematological toxicity, not only in terms of a greater likelihood of anemia and thrombocytopenia, with a greater need for transfusion support, but above all of the chemo-induced neutropenia, especially febrile neutropenia. The use of granulocyte colony-stimulating factor (G-CSF) in this setting has certainly reduced the incidence of neutropenia, particularly febrile neutropenia. However, it has partly contributed to another important ABVD-related toxicity, that of bleomycin. The bleomycin toxicity that we are interested in analyzing here is pulmonary toxicity, which is known to take on different clinical features, from only a reduction in the alveolar-capillary diffusion of carbon monoxide to pneumonia and pulmonary fibrosis . Bleomycin toxicity is quite typical of the ABVD regimen, where it is much more frequently documented than other types of therapy. Several studies have documented an incidence of bleomycin toxicity in older patients that ranges from 5% to 35%, with an associated mortality of up to over 30% . The most recognized risk factors for bleomycin toxicity are the use of G-CSF, the administration of more than two ABVD cycles, and, invariably, age >60 years. The association with cigarette smoking, however, appears milder and not always confirmed . A third important toxicity in older patients is cardiological toxicity, certainly linked to the greater incidence of cardiological comorbidities (ischemic heart disease, arterial hypertension, and rhythm abnormalities) and/or risk factors (diabetes mellitus and dyslipidemia). The use of anthracycline in these patients is undoubtedly burdened by a greater risk of cardiovascular problems. However, it is well known that not only its use but also an adequate dose rate seem to be remarkably important for the patient's prognosis . 4. First-Line Therapy: Reduced-Intensity Regimens The issue of therapy toxicity in older cHL patients is so important that there have been multiple attempts over the last 20 years to create the so-called low-intensity treatment regimens, including ChLVPP (chlorambucil, vinblastine, procarbazine, and prednisolone) , VEPEM-B (vinblastine, cyclophosphamide, procarbazine, etoposide, mitoxantrone, bleomycin, and prednisolone) , P-VAG (prednisone, vinblastine, doxorubicin, and gemcitabine) , and others. These regimens do not start from the ABVD backbone but are alternative polychemotherapy combinations, some including an anthracycline, while others do not. These regimens have almost always been the subject of small, prospective phase 2 studies whose aim was to find an adequate cycle and then ideally be able to compare the regimen with ABVD. A rare example of a randomized clinical trial compared ABVD and VEPEMB in 54 older patients with cHL (17 localized and 37 advanced); in this selected patient population, it was possible to observe in patients a superiority of ABVD over VEPEMB that, while not statistically significant, was certainly clinically significant, with a 5-year progression-free survival (PFS) of 70% versus 48% (p = 0.06) . All these low-intensity regimens aimed to (1) be less toxic and therefore better tolerated, (2) be completed while maintaining an adequate dose rate, (3) lead to a high rate of overall and complete responses, and (4) lead to an improvement in overall (OS) and disease-free survival (DFS). However, while reduced acute toxicity and a high rate of completion of chemotherapy protocols with adequate dose rates have almost always been observed, the high overall response rates (ORRs) and complete response rates (CRRs) observed did not translate into an improvement in survival curves due to the high recurrence rates seen. Ultimately, less intensity means less toxicity, but it also seems to mean less cure, at least in the setting of older cHL patients. 5. First-Line Therapy: Is There a Reference Treatment? A second strategy is to work on the ABVD backbone to reduce its most frequent toxicities. An interesting attempt in this sense is the one published by Salvi F et al., who replaced the standard doxorubicin in the ABVD scheme with a non-pegylated liposomal formulation, known for its lower incidence of acute and late toxicity (especially as hypokinetic heart disease) in other histologies. In this experience, 47 older and/or cardiac patients were treated. Although neither OS nor PFS was greater than the known rates for these indicators (3-year OS 70%, 3-year PFS 43%), the authors documented how a "standard" ABVD-like therapy in this "protective formulation" was feasible even in patients who would perhaps not have been candidates for anthracycline therapy . Another direction of research is obviously to reduce or omit bleomycin. In the RATHL trial , the authors stated that the omission of bleomycin from the ABVD regimen (AVD) after negative findings on interim PET resulted in a lower incidence of pulmonary toxic side effects compared with continued ABVD but not in significantly lower efficacy (3-year PFS 84.4% in the AVD arm versus 85.7% in the ABVD arm). In another study, carried out by the German Hodgkin Study Group (GHSG) , the upfront omission of bleomycin from the front-line therapy actually led to a reduction in cure rates, although much smaller than that with the omission of dacarbazine. However, the need to reduce and even eliminate bleomycin toxicity is much greater in older patients. In this setting, in a retrospective series of 147 patients , a French group observed how the reduction in or omission of bleomycin (chosen on a clinical basis) did not translate into worse survival rates in the entire population (hazard ratio (HR) for OS: 1.74; 95% confidence interval (CI) 1.0-3.0; p = 0.051), while reporting a worse outcome for patients in an advanced stage versus those in a localized stage. A recent Nordic group study retrospectively evaluated registry data from >=60-year-old patients treated between 2000 and 2021 in Sweden, Norway, and Denmark, who received ABVD (n = 671), AVD (n = 122), CHOP (n = 465), or other regimens (n = 296). In this work, no difference in PFS or OS was observed between ABVD and AVD (63% and 64%, respectively, at 5 years), although patients who received AVD were older than those treated with ABVD (74 vs. 66 years). We can therefore conclude that, at least in the setting of older patients, AVD is a preferable treatment. Using AVD as a reference and having already discussed the inferiority of attempts to devise low-intensity cycles, we can evaluate which modified AVD cycles are currently available so as to improve AVD efficacy. 6. "AVD Plus" Chemotherapy: Attempts to Improve Efficacy The greatest advance in the treatment of cHL in recent years has undoubtedly been the optimization of first-line therapy with the addition of brentuximab vedotin (BV) to AVD in the ECHELON-1 study . In this phase 3 study, patients with advanced newly diagnosed cHL were 1:1 randomized to receive ABVD or BV + AVD. Of the entire study population, 186 (14%) patients were aged >=60 years (median age 67 years, range 60-83); an analysis of this subgroup was published in 2022 . With regard to toxicity, the majority of these patients were given a dose reduction or modification of both BV (80% of patients in the BV + AVD arm) and bleomycin (71% of patients in the ABVD arm). The most relevant findings were the high treatment-related mortality in both groups (3.6% BV + AVD vs. 5.1% with ABVD) and the high rate of febrile neutropenia (37% BV + AVD vs. 17% ABVD). The authors reported that the high incidence of febrile neutropenia decreased after the mandatory introduction of primary prophylaxis with G-CSF. Eighteen percent of the patients in the BV + AVD arm experienced grade >=3 peripheral polyneuropathy but also a substantial reduction in pulmonary toxicity (2% versus 13% in the ABVD arm). In terms of efficacy, 5-year PFS was 67.1% in the BV + AVD group versus 61.6% in the ABVD group (p = 0.443). Based on these findings on the older population included in ECHELON-1, BV + AVD can be proposed as an effective bleomycin-free alternative for these patients. The combination of BV and AVD was also proposed as a sequential therapy (BV 1.8 mg/kg every 21 days for 2 cycles, followed by AVD for 6 cycles, followed by BV 1.8 mg/kg every 21 days for 4 cycles) in a phase 2 study on 48 consecutive newly diagnosed older cHL patients . In this study, the combined sequential modality obtained an ORR of 95% (with CRR of 93%) and a PFS at 2 years of 84%, with low toxicity (4% grade >=3 peripheral polyneuropathy and 8% febrile neutropenia). Although not investigated further in subsequent studies, a sequential modality such as that proposed by Evens et al. represents a potentially good way forward for the care of older patients . Although the main side effects of the combination of BV + AVD are apparently lower in sequential combination therapy, they should not be overlooked. Along with febrile neutropenia, which can be effectively prevented with G-CSF primary prophylaxis and adequately treated with early empiric antibiotic therapy, grade 3 peripheral polyneuropathy is also an important side effect. Although it is often transient and frequently resolves or improves over time, it can result in a reduction in the ability to perform common activities of daily living (ADLs) and must therefore be appropriately assessed in older patients. Furthermore, despite the most modern therapies, some factors specific to older patients, such as the presence of comorbidities, continue to play an important prognostic role in terms of overall survival , probably due to their influence on chemotherapy-related toxicity and on the possibility of achieving adequate dose intensity. It is therefore clear that correct patient selection must be addressed. 7. The Need for Patient Selection and the Role of Simplified Geriatric Assessment Adequate patient selection for treatments with different intensities or intent should be pursued for a number of reasons, including the possible toxicity of "standard" first-line treatments (as discussed above), the growing incidence of different types of frailty in the older population, and the availability of new effective therapies even for patients not eligible for standard therapy. There is no univocal definition of frailty in the literature, much less in the setting of patients suffering from hematological cancers, especially in the specific case of patients suffering from cHL. Nevertheless, the literature does demonstrate that frailty, no matter how it is defined, increases as a person ages. The data of Fogg et al. , part of a large national study on over 2 million patients in England, showed that frailty (measured with a multiparametric electronic frailty score) was found in 10% of patients aged 50-64 years but in 43.7% of those over age 64 years, reaching very high percentages in the older segments of the population. Along with fragility, it is also very important to perform an accurate assessment of a patient's life expectancy. The life expectancy of an older patient with lymphoma is the number of years that separates that patient from the target age that he or she would reach without lymphoma or if the lymphoma can be adequately treated. For a correct estimate of life expectancy, using the reference tables of many Departments of Health, which are updated yearly, and/or online calculators, which are based on these tables, is suggested . By way of an example, in 2023, an 80-year-old woman newly diagnosed with cHL has a life expectancy, in the absence of lymphoma, of about 9.6 more years. Finally, in the specific setting of cHL, it has been demonstrated that full-dose first-line therapy can produce the best survival results in patients who can tolerate it, resulting in a reduction in mortality from all causes . Indeed, Orellana-Noia et al. observed that receiving conventional therapy had a survival advantage over receiving alternative therapy . In light of the above, it is clear that the accurate assessments of present frailty and life expectancy allow clinicians to distinguish between those patients who will benefit from full-dose treatment and those who will benefit from other treatment options. A method to stratify patients based on their frailty was developed and tested by the Fondazione Italiana Linfomi (FIL) group, who recently published their results on the usefulness of a simplified geriatric assessment (sGA) in patients with DLBCL. In the FIL study, a baseline assessment of ADL , instrumental ADL (IADL) , and Cumulative Illness Rating Scale--Geriatric (CIRS-G) made it possible to divide patients into three functional status groups (FIT, UNFIT, and FRAIL), with different outcomes (3-year OS of 75%, 58%, and 43% for FIT, UNFIT, and FRAIL, respectively) (Table 1). Moreover, very similar to what was found in a study conducted by Isaksen et al. , the FIL group showed that it was possible to use the stratification of a patient's functional status for therapeutic indications as well. For example, in patients defined as UNFIT, it was observed that there were no differences in terms of outcome between patients treated with full-dose R-CHOP therapy and those treated with the same therapy at reduced doses (i.e., R-mini-CHOP) . The usefulness of such a tool is also related to its practicality: It takes less than 10 min to perform sGA, even in an outpatient setting. The applicability and usefulness of the sGA have yet to be validated in the setting of cHL in older adults; to this end, a prospective study is currently being conducted by the FIL group . 8. New Ways to Improve Defining Patients' Functional Status: Sarcopenia and Immunosenescence Beyond the extremely useful, practical tools to stratify patients in terms of their fitness, it is increasingly evident that functional status is a complex concept involving multiple factors. Sarcopenia (defined as a mainly cancer-related reduction in muscle mass, strength, and performance) has been widely demonstrated to be a reproducible, effective indicator of the outcome and, to some extent, the tolerance to therapy of patients of any age undergoing chemotherapy in the oncological setting . More recently, sarcopenia, particularly as a CT-scan measured reduction in muscle mass, was demonstrated to be useful in predicting the outcome of patients with lymphomas as well . Immunosenescence--an age-related decrease in immune function--is emerging as another important aspect related to lymphoma prognosis and cure. This complex biological process occurs in both the innate and adaptive components of the immune system and results in increased sensitivity to infections, increased autoimmune disorders, reduced immune surveillance, and cancer development . Little is known about any possible correlation between immunosenescence and frailty, but it is worth mentioning that in the FIL study published by Tucci et al. , the non-FIT DLBCL patients did not benefit from potentially life-saving therapies: The OS of patients treated with a curative regimen was the same as that for those treated with a palliative regimen (2-year OS 19.8% vs. 26.1% for patients treated with curative or with palliative intent, respectively; p = 0.85). We could argue that, at least in this study, non-FIT patients may have intrinsic refractoriness to the disease rather than a poor tolerance to treatment, which could be due to the reduced immune surveillance of the tumor. Immunosenescence plays an essential but not entirely understood role in the development of lymphoma, and further studies are needed to better define it. 9. Alternative First-Line Therapies (Mainly) for Non-FIT Patients At this point, a reasonable approach to treatment layering based on the functional status of patients could and should foresee the following factors:- For FIT patients, a standard chemotherapy regimen (similar to that for younger patients); - For UNFIT patients, the same standard chemotherapy but with careful monitoring for toxicities and broader use of prophylaxis, or a reduced-dose chemotherapy pathway (not yet validated); - FRAIL patients represent the most challenging group, as no standard treatment for them currently exists. However, we must bear in mind that numerous treatment schemes have been published in recent years that offer potential alternative therapies for patients who are not candidates for standard chemotherapy. 9.1. Brentuximab Vedotin One type of therapy is based on the use of BV alone or in combination. BV monotherapy as a first-line treatment in older cHL patients has been shown to achieve a good ORR and CRR (92% and 73%, respectively), although of short duration, with a median duration of response and PFS of around 10 months . The good efficacy and low toxicity of BV have led to its evaluation in combination with monochemotherapy, in particular with bendamustine and dacarbazine. BV + bendamustine has proved extremely effective in achieving high ORR and CRR (100% and 88%, respectively) and has very good disease control over time, with a median PFS not reached after a follow-up of approximately 1 year. However, a total of 65% of the patients examined experienced adverse events, and 10% died of treatment-induced toxicity, resulting in the discontinuation of the BV + bendamustine arm of the study . In the same study by Friedberg et al. , the combination of BV and dacarbazine proved to be less toxic but adequately effective: for the 22 treated patients, the ORR was 100% (CRR 62%), with a median PFS of 17.9 months (not reached in patients obtaining CR versus 10.8 months in patients without CR) . 9.2. Anti-PD1-Containing Therapies Anti-PD1-containing therapies represent a great opportunity, especially given their extreme efficacy in cHL (greater than that observed in any other histology of oncological disease) and their good toxicity profile, making them an extremely interesting pharmacological class, especially for older patients. Considering their use as first-line therapy in this population, anti-PD1-containing combinations have been primarily studied in order to improve the efficacy of standard treatments: the combination of nivolumab with AVD in the phase 2 CheckMate 205 study obtained an 84% ORR (CRR 67%) in a cohort of 51 patients, with 9-month PFS of 92% and 9-month OS of 98% . The use of anti-PD1-containing therapy alone or in combination with other drugs allows clinicians to offer appropriate treatment to those patients who are not candidates for standard therapy and who therefore may not be offered treatment at all. In this context, the combination of BV + nivolumab has proved to be well tolerated and effective. Although the ACCRU trial discontinued its enrollment after the interim analysis because it had not achieved the primary CRR objective (at the final evaluation of 46 patients, the authors observed an ORR of 61% and a CRR of 48%), it illustrated that the responses obtained were long-lasting (median PFS 18.3 months for the entire population, in particular, not reached for patients with CR, versus 6 months for patients with PR, with a median follow-up of 21.2 months). The efficacy of this combination was also demonstrated by Yasenchak et al. , who documented an ORR of 95% (CRR 79%) in their 19 patients, with a median PFS not reached at a median follow-up of 19.4 months. The French NIVINHO trial on 56 patients consisted of a first phase of treatment with nivolumab monotherapy (240 mg flat dose) every 14 days for 6 administrations and subsequent continuation based on response: The patients in complete metabolic response continued nivolumab monotherapy for an additional 18 cycles, while those in partial response or stable disease were treated with a combination of nivolumab and vinblastine every 14 days for 18 cycles. Thanks to this scheme, this difficult-to-treat population (median age 75 years, median CIRS-G 10) achieved an ORR of 46.5% and a CRR of 28.6% (16% post-nivolumab in monotherapy), with a median PFS of 9.8 months at a median follow-up of over 20 months . Finally, several study protocols are about to be activated (e.g., the GHSG HD20 study "Indie trial" NCT04837859 and the announced GHSG HD19 and UK RATIFY trials) in which anti-PD1-containing therapies will be used to reduce the toxicity or duration of first-line therapy and, in some cases, to allow the omission of chemotherapy in patients in complete metabolic response. 10. What Second-Line Options Are Available and Effective? Salvage therapy in relapsed/refractory (R/R) older cHL patients is even more complex since the issues encountered in first-line therapy naturally increase in a salvage setting due to the presence of a clearly more aggressive disease and to the patient's prior treatment regimens (including in terms of toxicity). It is also evident that the problem of salvage therapy in a patient population in which the diminished efficacy of first-line therapies is well known is even larger because of the greater frequency of patients with R/R disease. A well-developed study by the GHSG a few years ago revealed an advantage, in terms of response to second-line therapy and overall survival, for "low-risk" patients who were treated with polychemotherapy schemes compared with patients who were candidates for an intensification procedure (autologous transplantation) or palliative therapy. The authors described a simple prognostic score for recurrence based on the presence of advanced disease, anemia, and early relapse: Patients with no or only one risk factor had a 3-year OS of 59%, whereas patients with two or all three risk factors had a 3-year OS of only 9%. At present, the results of this work encounter some application limitations: In particular, the clinical trend of patients in general (both on the first line and on the subsequent lines) and the prognostic value of the identified score are strongly affected by the new therapeutic scenario. On the one hand, the advent of new drugs (especially BV and anti-PD1) has decidedly increased the possibility of saving even older patients. On the other hand, the increasingly early use of these drugs, even in first-line therapy, is radically changing the treatment paradigm of patients with cHL. Finally, an adequate assessment of the patient's functional status could be useful in the setting of second-line therapy as well; more intensive and potentially effective approaches with low toxicity could be offered to FIT patients, reserving more conservative approaches to patients with the most compromised functional status (e.g., BV or pembrolizumab monotherapy). The possible advantage of an adequate patient selection is demonstrated by the fact that in a small series of 15 highly selected older patients aged 60-67 years (median age 64 years), an autologous stem cell transplant (ASCT) with alternative conditioning regimen (etoposide 60 mg/kg i.v. over 8 h on day-4, melphalan 180 mg/m2 i.v. over 30 min on day-3) proved to be safe and effective, with no transplant-related deaths and with a 3-year PFS and OS of 73% and 88%, respectively . In a French retrospective study by Stamatoullas et al. on 128 FIT patients undergoing ASCT with BEAM conditioning, ASCT showed low toxicity and achieved good disease control over time (5-year PFS and OS of 54% and 67%, respectively). The GELTAMO group analyzed a retrospective series of 121 patients aged 50 years or older who underwent ASCT , including 42 patients aged >=60 years. The authors were able to demonstrate very good disease control, with a PFS and OS at 10 years of 51% and 57%, respectively, without any substantial differences between younger and older patients. Moreover, in the multivariable analysis, excluding pre-transplant disease status, the only factor associated with an unfavorable outcome was comorbidities, not age. In all these investigations, the correct stratification of patients' functional status emerged as a real need, with an evident clinical impact, allowing most FIT patients to start intensifying programs that allow them to obtain high disease-free and global survival rates. Currently, however, no comprehensive GA validation studies are available in this setting. Most older patients with R/R cHL are not eligible for an ASCT intensification strategy. Frequently, gemcitabine-based or bendamustine-based approaches have been used as salvage treatments , but the most valid therapeutic alternatives are based on the use of new drugs. BV monotherapy can achieve OR and CR rates of 56% and 38%, respectively, although disease control over time is not optimal, with a median PFS of 9 months (18.5 months for CR patients) . Anti-PD1-containing therapies are also good alternatives, but once again, the studies on the older population are extremely few. An interesting exception is the KEYNOTE-204 study, which randomized 300 patients with R/R cHL to receive BV or pembrolizumab. Of these patients, 49 aged >=65 years achieved a PFS of 8.2 months with pembrolizumab versus 5.5 months with BV . Unfortunately, no data regarding the functional status of these older patients were collected, and the number of patients was too small to draw definitive conclusions. Currently, patients with R/R elderly cHL who are not eligible for intensification strategies are in most cases candidates for treatment programs with more containment than curative purposes. In this situation, a case-by-case discussion of the treatment program with the patient, including not only the expected benefits but also the foreseeable side effects, is fundamental. Therapeutic alternatives with similar efficacy but lower costs must also be considered. A subset of low-risk patients, unfit for ASCT, may be salvaged with radiotherapy , which can also be widely and safely used in the setting of elderly cHL treatment as a post-chemotherapy consolidation strategy or as a palliative approach. 11. Conclusions cHL in older adults remains challenging because of both its greater biological aggressiveness and the unsatisfactory response to first-line therapy. AVD can be considered the gold standard in these older patients, and attempts to improve its efficacy with the addition of BV (especially as sequential therapy) seem to translate into better outcomes. Adequate patient stratification at baseline by employing sGA tools that include ADL, IADL, and comorbidity scores remains essential. FIT patients may be considered for treatment approaches similar to those for younger patients, while new effective, more suitable therapies for UNFIT and FRAIL patients are emerging, such as the combinations of BV with dacarbazine or nivolumab. There is a growing need for prospective studies to better characterize these patients, to validate an sGA that includes emerging factors such as sarcopenia and immunosenescence, and to investigate new therapies both in the first-line and salvage settings, with particular focus on the role that new agents can play. Author Contributions V.R.Z. conceptualized the review, searched the data, critically analyzed the data, and took part in the writing and editing of the manuscript. C.M. searched the data, critically analyzed the data, and took part in the writing of the manuscript. C.P. searched the data and critically analyzed the data. E.R. (Emanuele Ravano) searched the data and critically analyzed the data. E.M. searched the data and critically analyzed the data. R.D. searched the data and critically analyzed the data. E.R. (Erika Ravelli) searched the data and critically analyzed the data. R.C. searched the data, critically analyzed the data, and took part in the writing of the manuscript. A.R. searched the data, critically analyzed the data, and took part in the writing of the manuscript. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest The authors declare no conflict of interest related to the present manuscript. Figure 1 Bleomycin-related pulmonary toxicity: in this CT scan, bilateral severe fibrosis extended to all lung fields is represented. A 55-year-old woman experienced this fatal toxicity at the end of ABVD therapy for 6 cycles (with which she obtained CR). cancers-15-01515-t001_Table 1 Table 1 FIL criteria for sGA assessment. Criteria FIT UNFIT FRAIL ADL >=5 a <5 a 6 a <6 a IADL >=6 a <6 a 8 a <8 a CIRS-G 0 score = 3-4, <=8 score = 2 >=1 score = 3-4, >8 score = 2 0 score = 3-4, <5 score = 2 >=1 score = 3-4, >=5 score = 2 Age <80 <80 >=80 >=80 Abbreviations: ADL, activity of daily living; CIRS-G, Cumulative Illness Rating Scale--Geriatrics; IADL, instrumental ADL; sGA, simplified geriatric assessment. a Number of residual functions. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000521 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050735 cells-12-00735 Article Molecular Mechanisms of Nemorosone-Induced Ferroptosis in Cancer Cells Fernandez-Acosta Roberto Conceptualization Validation Investigation Data curation Writing - original draft Visualization 1 Hassannia Behrouz Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing - review & editing Visualization 234 Caroen Jurgen Investigation Writing - review & editing 5 Wiernicki Bartosz Investigation 23 Alvarez-Alminaque Daniel Investigation 6 Verstraeten Bruno Software Investigation 23 Van der Eycken Johan Investigation Writing - review & editing 5 Vandenabeele Peter Conceptualization Methodology Formal analysis Investigation Resources Writing - review & editing Supervision Funding acquisition 237 Vanden Berghe Tom Conceptualization Methodology Formal analysis Writing - review & editing Supervision 234 Pardo-Andreu Gilberto L. Conceptualization Methodology Validation Formal analysis Investigation Writing - review & editing Visualization Supervision Funding acquisition 6* Amos Samson Academic Editor Corazzari Marco Academic Editor 1 Department of Pharmacy, Institute of Pharmacy and Food, University of Havana, 222 St. # 2317, La Coronela, La Lisa, Havana 13600, Cuba 2 Cell Death and Inflammation Unit, VIB Center for Inflammation Research (IRC), 9052 Ghent, Belgium 3 Department of Biomedical Molecular Biology (DBMB), Ghent University, 9052 Ghent, Belgium 4 Laboratory of Pathophysiology, Department of Biomedical Sciences, University of Antwerp, 2000 Antwerp, Belgium 5 Laboratory for Organic and Bio-Organic Synthesis, Department of Organic and Macromolecular Chemistry, Ghent University, 9000 Ghent, Belgium 6 Center for Research and Biological Evaluations, Institute of Pharmacy and Food, University of Havana, 222 St. # 2317, La Coronela, La Lisa, Havana 13600, Cuba 7 Methusalem Program, Ghent University, 9052 Ghent, Belgium * Correspondence: [email protected] 24 2 2023 3 2023 12 5 73516 12 2022 01 2 2023 14 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Ferroptosis is an iron-dependent cell death-driven by excessive peroxidation of polyunsaturated fatty acids (PUFAs) of membranes. A growing body of evidence suggests the induction of ferroptosis as a cutting-edge strategy in cancer treatment research. Despite the essential role of mitochondria in cellular metabolism, bioenergetics, and cell death, their function in ferroptosis is still poorly understood. Recently, mitochondria were elucidated as an important component in cysteine-deprivation-induced (CDI) ferroptosis, which provides novel targets in the search for new ferroptosis-inducing compounds (FINs). Here, we identified the natural mitochondrial uncoupler nemorosone as a ferroptosis inducer in cancer cells. Interestingly, nemorosone triggers ferroptosis by a double-edged mechanism. In addition to decreasing the glutathione (GSH) levels by blocking the System xc cystine/glutamate antiporter (SLC7A11), nemorosone increases the intracellular labile Fe2+ pool via heme oxygenase-1 (HMOX1) induction. Interestingly, a structural variant of nemorosone (O-methylated nemorosone), having lost the capacity to uncouple mitochondrial respiration, does not trigger cell death anymore, suggesting that the mitochondrial bioenergetic disruption via mitochondrial uncoupling is necessary for nemorosone-induced ferroptosis. Our results open novel opportunities for cancer cell killing by mitochondrial uncoupling-induced ferroptosis. nemorosone ferroptosis mitochondrial uncoupling fibrosarcoma neuroblastoma Vlaamse Interuniversitaire Raad (VLIR)-Belgium/Ministerio de Educacion Superior (MES)CU2018TEA457A103 Ministerio de Ciencia Tecnologia y Medio AmbientePN223LH010-035 FWOG.0C76.18N G.0B71.18N G.0B96.20N G.0A93.22N 30826052 40007512 Special Research Fund UGentBOF16/MET_V/007 20/IBF/039 Foundation against CancerF/2016/865 F/2020/1505 This work was partially supported by the Vlaamse Interuniversitaire Raad (VLIR)-Belgium/Ministerio de Educacion Superior (MES)-Cuba Project CU2018TEA457A103, and by project PN223LH010-035 from the Ministerio de Ciencia Tecnologia y Medio Ambiente (Cuba), Programa de Ciencias Basicas y Naturales. Research in the Vandenabeele unit is supported by grants from the FWO (research grants G.0C76.18N, G.0B71.18N, G.0B96.20N, G.0A93.22N, EOS MODEL-IDI Grant (30826052), and EOS CD-INFLADIS (40007512)), grants from the Special Research Fund UGent (Methusalem grant BOF16/MET_V/007 and iBOF ATLANTIS grant 20/IBF/039), and grants from the Foundation against Cancer (F/2016/865, F/2020/1505), the CRIG and GIGG consortia, and VIB. pmc1. Introduction The natural product nemorosone was isolated in 1996 through the extraction of floral resins from Clusia rosea, an evergreen tropical plant with several medicinal applications . Its chemical structure was unraveled in 2001 as a type A polyisoprenylated benzophenone . The high interest in nemorosone mainly resides in its cytotoxic anti-cancer activity, as shown in a broad spectrum of different human cancer models such as leukemia, colorectal, pancreatic, hepatic, and breast cancer . In most cases, apoptosis was reported as its mode of cytotoxicity along with the arrest of cell cycle progression. Recently, its antimetastatic potential through the modulation of molecules related to the epithelial-mesenchymal transition (EMT) was also described . Furthermore, several research works have reported antimutagenic activity without a genotoxic effect, selectivity toward cancer cells, and the capacity to circumvent multidrug-resistance mechanisms . Altogether, these previous studies show that nemorosone can be considered as a lead compound for the development of novel antiproliferative drugs for cancer therapy. On the other hand, we found that nemorosone disrupts the mitochondrial bioenergetic status by acting as a potent protonophoric mitochondrial uncoupler . Therefore, despite the well-established capacity of nemorosone to induce apoptosis , other modes of regulated cell death could be induced depending on the cell type. Since the conceptualization of ferroptosis in 2012, several compounds previously described as inducers of apoptosis, such as cisplatin, sorafenib, and withaferin A, have been found to elicit ferroptosis . Moreover, the induction of ferroptosis has also been identified in a myriad of natural products . Ferroptosis is a form of regulated necrosis mediated by iron-catalyzed excessive lipid peroxidation , often referred to as biological rust of lipid membranes . Ferroptosis can be induced by inactivating glutathione peroxidase 4 (GPX4), which detoxifies lipid hydroperoxides. GPX4 can be inactivated through direct targeting and inhibition, by class II and III inducers, or alternatively by indirect mechanisms through the depletion of intracellular GSH, an essential co-factor of GPX4, by class I inducers . Furthermore, ferroptosis can be activated by the increase in the cellular labile iron pool (LIP), which is the intracellular non-protein bound redox-active iron, or iron oxidation mediated by class IV inducers . Recently, Gao et al. showed that mitochondria play a central role in cysteine-deprivation-induced and erastin-induced ferroptosis (Class I FINs), but not in the case of the ferroptosis induced by GPX4 inhibition (Class II FINs). Mechanistically, cysteine deprivation leads to a transient hyperpolarization of the mitochondrial membrane potential and lipid peroxide production . On the other hand, cell death induced by mitochondrial uncoupling is accompanied by depolarization of the mitochondrial membrane potential, reduced ATP levels, increased ROS, and diminished antioxidant defense by decreasing GSH levels . The latter may resemble a similar cellular effect observed in erastin-treated cells. Therefore, we hypothesized and examined whether mitochondrial uncoupling by nemorosone could initiate a ferroptotic response. Using different cell lines, we found that nemorosone triggers ferroptosis, as detected by lipid peroxidation. We elucidated that nemorosone-induced ferroptosis involves a double-edged mechanism. Nemorosone decreases the glutathione levels by blocking the cystine/glutamate antiporter and induces lipid peroxidation as an early event. At later time points, nemorosone administration results in activation of the KEAP1-NRF2-HMOX1 axis, causing an increase in the intracellular labile Fe2+ pool and consequent reactive oxygen species (ROS) production. Methylnemorosone, a structural variant of nemorosone that has lost the capacity to uncouple mitochondrial respiration, does not trigger cell death anymore. The classical mitochondrial uncoupler carbonyl cyanide 3-chlorophenylhydrazone (CCCP) has a similar biological effect as nemorosone, in inducing ferroptosis. In summary, our results demonstrate that nemorosone as well as other mitochondrial uncouplers drive intrinsic ferroptosis. The present findings could open new perspectives for a better insight into ferroptosis initiated by mitochondrial dysfunction and for the development of novel ferroptosis inducers for cancer treatment. 2. Materials and Methods 2.1. Antibodies and Reagents The following antibodies were used in this study: b-tubulin (Abcam, Cambridge, UK, ab21058), GPX4 (Abcam, ab41787), HMOX1 (Enzo Life Sciences, Farmingdale, NY, USA, ADI-SPA-896-F), NRF2 (Abcam, ab62352), and KEAP1 (Proteintech, Rosemont, IL, USA, 10503-2-AP). The following chemicals were used: SytoxGreen (Thermo Fisher Scientific, Waltham, MA, USA, S7020): 1.7 mM, BODIPY 581/591 C11 probe (Invitrogen, Waltham, MA, USA, D-3861): 2 mM, SytoxBlue (Thermo Fisher Scientific, S11348): 1.25 mM, DRAQ7 (BioStatus, Loughborough, UK, DR71000): 0.3 mM, TMRE: tetramethylrhodamine ethyl ester (Thermo Fisher Scientific, T669): 200 nM, FeRhoNox-1 (Goryo Chemical, Sapporo, Hokkaido, Japan, GC901): 10 mM, MitoSOX Red (Thermo Fisher Scientific, M36008): 5 mM, erastin (Selleckchem, Houston, TX, USA, S7242): 10 and 20 mM, CCCP: carbonyl cyanide 3-chlorophenylhydrazone (Sigma, St. Louis, MO, USA, Cat#C2759), Nec-1s (Calbiochem, San Diego, CA, USA, 480065): 10 mM, Fer1 (Xcess Biosciences, Chicago, IL, USA, 053224): 1 mM, DFO (Sigma-Aldrich, St. Louis, MI, USA, D-9533): 50 mM, and CPX (Sigma-Aldrich, C0415): 5 mM. Z-VAD-FMK (Bachem, Bubendorf, Switzerland, N-1510), a caspase peptide inhibitor, was used at a concentration of 10 mM, while DEVD-AMC (Pepta Nova, Sandhausen, Germany, 3171-V), a fluorogenic substrate for caspase-3, was used at 20 mM. The mitochondrial complexes inhibitors rotenone (Sigma, Cat#R8875), antimycin A (Sigma, Cat#A8674), and oligomycin (Sigma, Cat#75351) were used at 0.5 and 10 mM, 0.5 and 50 mM, and 1.5 mM, respectively. Hemin (Sigma-Aldrich, H9039) was used at 5 and 10 mM, zinc protoporphyrin: ZnPP (Enzo Life Sciences, ALX-430-049-M025) was used at 1 mM, and ferrous ammonium sulfate: Fe(NH4)2(SO4)2*6H2O (Sigma-Aldrich, FX0245) was used at 1 mM. Trimethylsilyldiazomethane (Sigma-Aldrich, 362832): a 2.0 M solution in hexanes was used. Toluene, methanol, n-hexane, and diethyl ether were purchased from Chem-Lab NV (Zedelgem, Belgium, HPLC grade). 2.2. Nemorosone Isolation and Characterization. Synthesis and Characterization of Methylated Derivative TLC was performed using precoated silica gel plates (Macherey-Nagel SIL G-25 UV254). Chemical shifts for the 1H NMR and 13C NMR spectra, recorded on a Bruker Avance 400 spectrometer, were reported in parts per million with reference to the residual solvent signal (CDCl3: 7.26 ppm; CD3OD: 3.30 ppm and 49.00 ppm). Coupling constants (J) are expressed in hertz. Electrospray mass spectra were recorded by means of an Agilent 1100 series single quadrupole MS detector type VL, with APCI and API-ES sources, and provided with a Phenomenex Luna C18 (2) column (5 mm 250 mm x 4.60 mm). An Agilent 1100 series connected to a 6220A TOF-MS detector, equipped with an APCI-ESI multi-mode source, was used to conduct high resolution mass spectrometry (HRMS). A Perkin-Elmer 1000 FT-IR infrared spectrometer (HATR) was utilized to record the infrared spectra. A Perkin Elmer 241 polarimeter was used to measure optical rotation. Nemorosone was isolated, as previously described , from the floral resin of Clusia rosea. Concisely, an EtOH-H2O solution was used to crystallize nemorosone from the resin of the flowers of this plant species. Figure S1A shows the structure of nemorosone: C33H42O4, a mixture of tautomers (1S,5R,7R)-5-benzoyl-4-hydroxy-6,6-dimethyl-1,3,7-tris(3-methylbut-2-en-1-yl)bicyclo [3.3.1]non-3-ene-2,9-dione and (1S,5S,7R)-1-benzoyl-4-hydroxy-8,8-dimethyl-3,5,7-tris(3-methylbut-2-en-1-yl)bicyclo[3.3.1]non-3-ene-2,9-dione. Purity of isolated nemorosone was >99%, as determined via reversed-phase HPLC, with detection at 214/254 nm . Eluting conditions: eluent A/eluent B (50/50) for 30 s, followed by gradient elution (A/B from 50/50 to 0/100) over 6 min (eluent A: 0.1% HCOOH in water; eluent B: acetonitrile) on a Phenomenex Luna C18 (2) column (5 mm 250 mm x 4.60 mm). Analytical data are in agreement with the literature and identical to recorded data of commercially available nemorosone (purchased from Cayman Chemical, Ann Arbor, MI, USA, 24256). Rf 0.22 in hexane/EtOAc 8/2 [Lit: 0.21 ]. 1H NMR (CD3OD, 400 MHz): 7.53 (br d, J = 7.7 Hz, 2H), 7.43 (app tt, J = 7.4 Hz/1.2 Hz, 1H), 7.22-7.28 (m, 2H), 4.96-5.11 (m, 3H), 3.13 (dd, J = 15.0 Hz/7.8 Hz, 1H, A-part of ABX-system), 3.07 (dd, J = 14.8 Hz/7.4 Hz, 1H, B-part of ABX-system), 2.54 (dd, J = 14.7 Hz/7.8 Hz, 1H, A-part of ABX-system), 2.47 (dd, J = 14.5 Hz/7.3 Hz, 1H, B-part of ABX-system), 2.09-2.19 (m, 1H), 2.01 (br dd, J = 13.1 Hz/2.7 Hz, 1H), 1.65-1.85 (m, 2H), 1.68 (s, 3H), 1.64 (app s, 12H), 1.58 (s, 3H), 1.39-1.50 (m, 1H), 1.33 (s, 3H), 1.10 (s, 3H) ppm. 13C NMR (CD3OD, 100 MHz): 209.26 (C), 194.88 (C), 138.23 (C), 135.25 (C), 134.24 (C), 133.66 (C), 133.12 (CH), 129.61 (CH), 128.78 (CH), 123.99 (CH), 122.12 (CH), 121.18 (C), 120.79 (CH), 44.64 (CH), 30.40 (CH2), 28.19 (CH2), 26.30 (CH3), 26.02 (CH3), 24.35 (CH3), 22.32 (CH2), 18.30 (CH3), 18.11 (CH3), 17.97 (CH3), 16.20 (CH3) ppm. [a]D20 +99deg (c 0.095, MeOH) [Lit: -98.3deg (ent-nemorosone, c 1.19, MeOH) ]. IR (HATR): 3534 (m), 3418 (m), 2966 (m), 2916 (m), 2882 (m), 1711 (s), 1699 (s), 1582 (vs), 1446 (m), 1391 (m), 1368 (vs), 1317 (m), 1262 (m), 1242 (m), 1215 (s), 1197 (m), 1185 (m), 1172 (m), 1157 (m), 1128 (m), 1101 (m), 1063 (m), 1032 (w), 1019 (m), 1003 (w), 959 (w), 936 (w), 922 (w), 897 (w), 839 (s), 799 (m), 772 (w), 751 (m), 730 (w), 690 (m), 666 (m) cm-1. HRMS (ESI, positive mode): calculated for C33H43O4+ [M+H+]: 503.3156, found: 503.3149. Data on isolated natural nemorosone: ; data on synthetic ent-nemorosone: ; data on synthetic racemic nemorosone: . Copies of 1H and 13C (APT) spectra can be found in Supplementary Materials . For the synthesis of O-methylated nemorosone, to a solution of nemorosone (200 mg, 0.398 mmol, 1 eq) in toluene/methanol (10 mL, 4/1), trimethylsilyldiazomethane (1.2 mL, 2.0 M in hexanes, 2.4 mmol, 6 eq) was added dropwise. After stirring the reaction mixture (a pale yellow solution) at room temperature for 30 min, silica was added to quench the excess of reagent. The resulting suspension was filtered and, under reduced pressure, the filtrate was concentrated. The 1H NMR spectrum of the crude mixture of both formed isomers was consistent with findings in the literature data on pure individual compounds ; integration of diagnostic methyl ester signals showed an isomer ratio of 78/22 . The residue was partially purified using flash chromatography (gradient elution: hexane/ether 99/1-93/7), affording pure major isomer (48 mg, 0.093 mmol, 23% yield) and a mixture of major and minor isomers . Eluting conditions: eluent A/eluent B (100/0) during 30 s, followed by gradient elution (A/B from 100/0 to 0/100) over 6 min (eluent A: 5 mM NH4OAc in water; eluent B: acetonitrile) on a Phenomenex Luna C18 (2) column (5 mm 250 mm x 4.60 mm). Major isomer: Rf 0.25 in hexane/ether 9/1. HRMS (ESI, positive mode): calculated for C34H45O4+ [M + H+]: 517.3312, found: 517.3335. Minor isomer: Rf 0.17 in hexane/ether 9/1. HRMS (ESI, positive mode): calculated for C34H45O4+ [M + H+]: 517.3312, found: 517.3330. 2.3. Conditions for Cell Culture DMEM medium supplemented with 10% (v/v) fetal calf serum (FCS), sodium pyruvate (1 mM), l-glutamine (1 mM), and non-essential amino acids (1 mM) was used to cultivate U87MG and U373MG human glioblastoma cells and HT22 cells (non-tumorigenic mouse hippocampal neuronal cell line); while IMR-32 (human neuroblastoma cell line) and HT1080 human fibrosarcoma cells were cultured in RPMI 1640 and EMEM medium, respectively, both supplemented in the same way as DMEM medium. Each cell line was obtained from ATCC. Every 3-4 days, cells cultures were split using a trypsin/EDTA solution and maintained at 37 degC in a humid 5% CO2 environment. It is important to highlight that these cancer cell lines were chosen both for their clinical relevance (they are representative cell lines of tumors refractory to conventional therapy) and for their reported sensitivity to the induction of non-apoptotic regulated cell death . In addition, nemorosone had not been tested in any of these cell lines. 2.4. Analysis of Cell Death and Caspase-3 Activity Using the FLUOstar Omega fluorescence plate reader (BMG Labtech GmbH), cell death and caspase-3 activity were measured as previously reported . Briefly, cells were seeded in a 96-well plate, and all experiments were carried out in triplicate. The following day, after being preincubated with the selected inhibitors, cells were treated with stimuli at desired concentrations in the presence of SytoxGreen and DEVD-AMC. At 1 h intervals, the fluorescence intensity of both fluorescent probes was measured. Percent cell death was calculated using Triton X-100 (0.05%) as a reference for 100% cell death. Following this same procedure, live cell images of seeded cells were obtained using a Zeiss LSM780 confocal microscope. The ImageJ program was used to merge the images. To analyze the induction of cell death, SytoxBlue staining was also used in conjunction with flow cytometry (BD LSR-Fortessa, BD Biosciences, Franklin Lakes, NJ, USA). 2.5. Lipid ROS Analysis Lipid ROS generation was determined by a previously described methodology . In short, in a 6-well plate, HT1080 (300,000 cells/well) and IMR-32 (500,000 cells/well) cells were seeded. Cells were stimulated the following day and harvested. Fluorescent probes, C11-BODIPY and DRAQ7, were added to the wells 10 min prior to each time point, and lipid ROS accumulation was measured by flow cytometry (BD LSRFortessa, BD Biosciences). B530 (C11-BODIPY) and R780 (DRAQ7) channels were used to measure fluorescence. Only non-permeable live cell fluorescence was evaluated. Per condition, a minimum of 10,000 cells were examined. 2.6. Mitochondrial ROS Analysis Mitochondrial ROS generation was determined using MitoSOX Red. In brief, HT1080 cells (300,000 cells/well) were seeded in a 6-well plate and incubated overnight. Afterward, cells were exposed to the test compounds according to the instructions of the experiment. After being washed with pre-warmed HBSS (Thermo Fisher Scientific, 14025076), cells were then incubated with fresh medium containing MitoSox Red for 15 min at 37 degC. Subsequently, cells were washed with HBSS and collected in PBS (Thermo Fisher Scientific, 10010023) containing SytoxBlue for measurement using BD FACSVerse (BD Biosciences). B586 (MitoSOX Red) and V448 (SytoxBlue) channels were used to measure fluorescence. Only non-permeable live cell fluorescence was evaluated. Per condition, a minimum of 10,000 cells were examined. 2.7. Determination of Cellular Labile Fe2+ Pool FeRhoNox-1 dye was used to measure iron levels as previously described . HT1080 cells (300,000 cells/well) were seeded in a 6-well plate and incubated overnight. Cells were harvested the next day and centrifuged at 300x g for 5 min. Then, cells were centrifuged at 300x g for 5 min after being washed with PBS buffer. The collected cells were stained with FeRhoNox-1 in PBS and kept in a CO2 incubator for 30 min. Following HBSS washing, cell culture was dissolved in 300 mL of HBSS containing SytoxBlue, and examined using BD LSRFortessa (BD Biosciences). Y585 (FeRhoNox-1) and V450 (SytoxBlue) channels were used to measure fluorescence. Only non-permeable live cell fluorescence was evaluated. Per condition, a minimum of 10,000 cells were examined. 2.8. Measurement of Mitochondrial Membrane Potential In a 6-well plate, HT1080 (300,000 cells/well) and IMR-32 (500,000 cells/well) cells were seeded. The following day, after cells had received the indicated treatment, TMRE (200 nM) was added, and the mixture was incubated for 30 min. The cells were washed with PBS to remove extra TMRE before being collected for analysis with the BD LSRFortessa (BD Biosciences). B575 (TMRE) and V450 (SytoxBlue) channels were used to measure fluorescence. Only non-permeable live cell fluorescence was evaluated. Per condition, a minimum of 10,000 cells were examined. 2.9. Measurement of GSH Levels As previously reported , glutathione levels were determined using QuantiChrom Glutathione Assay Kit (BioAssay Systems, Hayward, CA, USA, DIGT-250). Concisely, 1,000,000 cells per condition (HT1080 or IMR-32 cells) were seeded in a 6-well plate. The next day, cells were treated as indicated in each experiment. After that, cells were gathered, transferred to a new tube, and centrifuged at 425x g for 5 min at 4 degC. After being resuspended in 300 mL of PBS, each cell pellet was lysed using ultrasound. Each lysate was centrifuged at 14,000 rpm for 10 min at 4 degC. The cleared lysate was then used to calculate the amount of GSH present in each sample following the kit descriptions. 2.10. Measurement of Intracellular Glutamate Levels Intracellular glutamate levels were measured using Amplex(r) Red Glutamic Acid/Glutamate Oxidase Assay Kit (Thermo Fisher Scientific, A12221). HT1080 cells (400,000 cells/well) were seeded in a 6-well plate and incubated overnight. The following day, cells were treated according to the conditions described in each experiment and collected by centrifugation at 300x g for 5 min. After removing the supernatant, the pellet was resuspended in PBS buffer. Afterward, each sample was centrifuged again at 300x g for 5 min, and the pellet was resuspended in 100 mL of Tris HCl buffer (0.1 M, pH = 7.5). Then, cells were lysed by sonication, and each sample was diluted (2x) with Tris HCl buffer. Next, 50 mL of the diluted samples were transferred into separate wells of a microplate (OptiPlate 96-well plate), and the amount of intracellular glutamate was calculated following the kit descriptions. 2.11. Measurement of ATP Levels ATP levels were determined using CellTiter-Glo 2.0 Assay Kit (Promega, Madison, WI, USA, Cat# G9242/3) based on the firefly luciferin-luciferase assay system. Briefly, HT1080 cells (400,000 cells/well) were seeded in a 96-well plate in the absence (control) or presence of nemorosone, CCCP, or oligomycin, in line with the conditions described in the experiment legend. The measurement was performed in accordance with the instructions of the kit. 2.12. Measurement of Mitochondrial Respiration in Intact Cells Intact HT1080 or IMR-32 cells were added to a 2 mL chamber at a concentration of 1,000,000 cells/mL. Oxygen consumption was measured at 37 degC using a high-resolution respirometer (Oxygraph-2k Oroboros Instruments, Innsbruck, Austria). Oxygen flow per cell (pmol*s-1*mL-1) was recorded continuously using DatLab software 6 (Oroboros Instruments). After approximately 10 min of monitoring oxygen consumption, corresponding sequential injections of selected compounds and inhibitors were performed as indicated by the phosphorylation control protocol . 2.13. OCR and ECAR Measurement The Seahorse XFe96 Analyzer (Agilent) was used to measure the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). HT1080 cells (200,000 cells/well) were seeded into 96-well plates and incubated for 24 h. Before the assay, the culture medium was changed to a similar medium without phenol red and with 25 mM glucose, 1 mM sodium pyruvate, and 1 mM glutamine, and the cells were equilibrated for 30 min at 37 degC. During the assay, the compounds of interest were added, and the OCR and ECAR values were measured at intervals of approximately 6 min. 2.14. RNA Sequencing and Data Analysis An RNA 6000 nano chip (Agilent Technologies, Santa Clara, CA, USA) as well as an RNA labchip (Caliper GX-Perkin Elmer) were used to assess the total RNA quality of gall and control samples. Concentrations were determined using a Quant-it Ribogreen RNA assay (Life Technologies). Then, 265 ng of RNA were employed for the library prep through the QuantSeq 3' mRNA libr prep FWD kit (Lexogen). Library prep was carried out in accordance with the recommendations of the manufacturer. In brief, first-strand cDNA synthesis was performed, followed by an RNA removal step. Then, second-strand synthesis was performed with the use of UMIs, after which the cDNA was purified using beads (Lexogen). In addition to being purified with beads, the cDNA was used for 13 cycles of enrichment PCR. Using a high sensitivity DNA chip from Agilent Technologies, the quality was examined. To enable equimolar library pooling, a qPCR assay was used to quantify the libraries in accordance with the Illumina protocol. Finally, sequencing was carried out on a Nextseq500 using 20% Phix spike-in (single-end reads, 76 cycles). Through the use of FastQC (version 0.11.9), the quality of the reads was confirmed . The following parameters were used to trim reads with Trimmomatic (version 0.39): ILLUMINACLIP:<TruSeq3-SE adapter file>:3:30:10, SLIDINGWINDOW:5:20, MINLEN:20 . STAR (version 2.7.8a) was used for mapping with the subsequent parameters: readFilesCommand zcat, outFilterMultimapNmax 1 and outSAMtype BAM SortedByCoordinate using the GRCh38.106 genome build . These R packages were utilized to create a count table: GenomicFeatures (version 1.44.2), to convert the GRCh38.106 GTF file into a Granges object, and GenomicAlignments (version 1.28.0), for the summarizeOverlaps function to create the count table . The counting options were as follows: mode = 'Union', singleEnd = TRUE, and ignore.strand = FALSE. To find differentially expressed genes, DESeq2 (version 1.32.0) was used with a Benjamini-Hochberg FDR cutoff of 0.05 . Lists of differentially expressed genes were used for downstream analysis using Ingenuity pathway analysis (Qiagen). An R (v 4.1.3) environment was used for the analysis. 2.15. RNA Isolation and Analysis by RT-qPCR Total RNA from treated HT1080 cells was extracted according to the NucleoSpin(r) RNA Plus protocol (fifth revision, corresponding to January 2021) prepared by MACHEREY-NAGEL GmbH & Co. KG (Duren, Germany). For DNA synthesis, a C1000 Touch(r) thermocycler (Bio-Rad) was used. The qPCR analysis was performed under the following conditions: 95 degC for denaturation, 60 degC for hybridization, and 70 degC for elongation. qbase+ software (Biogazelle) was used to calculate the expression levels of mRNA (HMOX1: Bio-Rad, Hercules, CA, USA, qHsaCIP0033307) from the structural genes (housekeeping genes), HMBS (Bio-Rad, qHsaCID0038839) and RPL3 (Bio-Rad, qHsaCED0038656), which were used as internal references. 2.16. Protein Extraction and Western Blot Analysis At designated times, test compound-treated HT1080 cells were harvested and subjected to two washes with cold PBS solution. A cell lysis buffer (Cell Signaling Technology, Danvers, MA, USA) was used to extract the total cytosolic proteins, and their concentrations were determined by the Bradford method. In the wells of the 10% SDS-PAGE gel, 25 mg of protein were loaded along with the molecular weight marker. After performing the run (1 h, 100 V), the transfer of the proteins from the gel to nitrocellulose membranes was carried out. Subsequently, the membranes were blocked with 5% skim milk powder prepared in TBST saline (0.05% Tween 20). The membranes were incubated for 24 h at 4 degC with each primary antibody of interest (except in the case of b-tubulin, with which they were incubated for 1 h). Peroxidase-labeled secondary antibodies (PerkinElmer Life Sciences) were used to detect immunoreactive proteins. 2.17. Statistical Analysis Unpaired Student's t-test was carried out, using GraphPad Prism version 9.2.0 (GraphPad Software, San Diego, CA, USA), to calculate p values (* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001; see figure legends for more information), with the exception of Figure 3C, where a two-way ANOVA test was employed. Unless otherwise stated, data are displayed as the mean +- SD of three separate experiments. 3. Results 3.1. Nemorosone Is Highly Cytotoxic in Fibrosarcoma HT1080 Cells through Induction of Ferroptosis First, we analyzed the cytotoxic effect of nemorosone in a panel of cancer cell lines. Nemorosone was highly potent in killing HT1080 fibrosarcoma cell lines and high-risk MYCN-amplified IMR-32 neuroblastoma cells . The most potent effect was exerted on HT1080 cells, reaching 100% of cell death in 12 h , while in IMR-32 cells around 70% of cell death was reached in 24 h . However, nemorosone did not show any cytotoxic effect in glioblastoma (U87MG and U373MG) and the non-tumorigenic mouse neuronal cell lines (HT22) after 24h . The EC50 (half-maximal effective concentration) of nemorosone on HT1080 cells was determined to be 26.9 mM at 12 h and 16.7 mM at 24 h. To determine the type of cell death induced by nemorosone and prior to nemorosone exposure, HT1080 and IMR-32 cells were treated with a variety of apoptotic and non-apoptotic cell death inhibitors. The cell death induced by nemorosone was prevented by the tested ferroptosis inhibitors, the iron chelators deferoxamine (DFO) and ciclopirox olamine (CPX) and the lipophilic radical trap ferrostatin-1 (Fer1) , but it was not affected by the pan-caspase inhibitor Z-VAD-FMK and the RIPK1-kinase inhibitor necrostatin-1 (Nec-1s) . Moreover, analysis of caspase-3 activity with fluorescent caspase-activity probe (DEVD-AMC) did not show any caspase activity in HT1080 or IMR-32 cells. Considering that ferroptosis is characterized by high levels of lipid peroxidation compared to other cell death modalities , we examined this parameter after challenging HT1080 and IMR-32 cells with nemorosone using the fluorochrome C11-BODIPY. We observed that nemorosone triggers a time-dependent increase in lipid peroxidation in both fibrosarcoma and neuroblastoma cells . Moreover, we noticed that DFO and Fer1 completely prevented the production of lipid hydroperoxide . 3.2. Nemorosone Acts as a Natural Class I Ferroptosis-Inducing Compound Inactivation of GPX4 is one of the canonical ways of induction of ferroptosis and is exerted by class II ferroptosis inducers. Depletion of intracellular glutathione, which acts as a cofactor for GPX4 to reduce lipid hydroperoxides, is a second canonical way of ferroptosis induction, for example, by blocking the System xc cystine/glutamate antiporter by class I ferroptosis inducers . Similar to erastin, a class I FIN, we observed a substantial decrease in GSH levels in the fibrosarcoma and neuroblastoma cells after nemorosone treatment . We did not detect any GPX4 depletion at protein level after incubation with nemorosone or erastin, apart from the expected reduction in the signal due to the protein degradation exerted by the occurrence of cell death at the highest time points . Consistent with the GSH levels' decrease, we found that nemorosone, like erastin, increases the intracellular glutamate levels, suggesting the inhibition on the cystine/glutamate exchange mediated by the System xc cystine/glutamate antiporter . If the blockade of cystine import through the System xc antiporter can trigger ferroptosis, then providing this metabolite to cells through an alternative means should rescue the cells from death . Therefore, we pretreated cells with b-mercaptoethanol (b-ME), which reduces extracellular cystine to cysteine and bypasses the inhibition of the System xc antiporter, since cysteine can be imported via other pathways . As shown in Figure 2D, b-ME inhibited erastin-induced cell death in HT1080 cells, as previously reported . However, b-ME inhibited 100% of the cell death induced by erastin, whereas it inhibited the cell death induced by nemorosone by approximately 60% . The above results indicate not only that nemorosone partially acts as an erastin-like class I ferroptosis inducer but also that nemorosone additionally induces ferroptosis by another mechanism that circumvents the protection exerted by b-ME. Considering the central role of mitochondria in erastin-induced ferroptosis , we evaluated the involvement of the Electron Transport Chain (ETC) in nemorosone-induced ferroptosis using the mitochondrial complex I inhibitor (rotenone) and the mitochondrial complex III inhibitor (antimycin A) . We found that both inhibitors suppressed cell death and the lipid ROS accumulation triggered by nemorosone and erastin . These results show that functional ETC are required for nemorosone to induce ferroptosis. Altogether, these results suggest that nemorosone acts as a class I FIN and as an ETC-dependent ferroptosis inducer. 3.3. Mitochondrial Uncoupling of Nemorosone Is Indispensable for Ferroptosis Induction To examine whether the uncoupling effect of nemorosone is required to induce ferroptosis, we first verified its uncoupling potency compared to the classical protonophoric mitochondrial uncoupler CCCP by measuring the oxygen consumption rate (OCR) increase, the drop of mitochondrial membrane potential (MMP), ATP levels reduction, extracellular acidification rate (ECAR) increase (which can indicate higher rates of glycolysis), and mitochondrial ROS production (mitoROS). We found that nemorosone is at least an equally potent uncoupler compared to CCCP in both the neuroblastoma and fibrosarcoma contexts . Next, we prepared an analogue of nemorosone by a reaction of the vinylogous carboxylic acid moiety with trimethylsilydiazomethane, giving O-methylated nemorosone (hereafter named "methylnemorosone", isolated as a ~3/1 mixture of isomers resulting from both tautomeric forms of nemorosone), which lacks the uncoupling effect . We identified that, in the absence of its mitochondrial uncoupling effect, nemorosone shows no more cytotoxic effect nor lipid peroxidation increase in HT1080 cells . These results indicate, for the first time, the reactive moiety that is crucial for nemorosone-induced protonophoric mitochondrial uncoupling and ferroptosis induction. Furthermore, this association between nemorosone-induced ferroptosis and mitochondrial uncoupling is consistent with the previously stated requirement of nemorosone dependency on a functional ETC to trigger ferroptosis. Finally, we checked whether CCCP could also induce ferroptotic cell death. We found that both CCCP-induced cell death and lipid peroxidation were inhibited by canonical inhibitors of ferroptosis (Fer1 and DFO) and by ETC inhibitors (rotenone at complex I and antimycin A at complex III) . Moreover, we observed that CCCP decreases GSH levels, which is associated, similar to nemorosone, with an increased level of intracellular glutamate . These results show, for the first time, the capacity of not only nemorosone but also CCCP to induce ferroptosis, indicating that other protonophoric uncouplers could induce ferroptotic cell death. 3.4. Nemorosone-Induced Ferroptosis Involves Excessive Activation of Heme Oxygenase-1 To further characterize the mechanism of nemorosone-induced ferroptosis, we performed a genome-wide transcriptome analysis using RNA-Seq in HT1080 cells. We observed a significant transcriptional change after 2 and 8 h of nemorosone treatment . Remarkably, we found that heme oxygenase-1 (HMOX1) was the most upregulated gene by nemorosone, and one of the most upregulated by CCCP and erastin, which is in line with both the NRF2 upregulation and downregulation of the components of the KEAP1-CUL3-RBX1 E3 ubiquitin ligase protein complex . HMOX1 expression is controlled by the transcription factor NRF2, which is kept in check by KEAP1-dependent degradative ubiquitination . Correspondingly, one of the main signaling pathways induced by nemorosone, CCCP, and erastin, according to data analysis by Ingenuity Pathway Analysis (IPA), is the NRF2-mediated oxidative stress response . Nemorosone-induced upregulation of HMOX1 was confirmed at both the mRNA and protein levels. Consistently, we found that when HMOX1 is upregulated, KEAP1 levels are reduced, while NRF2 levels are elevated . The breakdown of heme molecules by HMOX1 is a major source of free Fe2+ . In line with this, we observed a time-dependent increase in the intracellular levels of the labile iron pool (LIP) upon nemorosone treatment, measured using an Fe2+-selective probe (FeRhoNox-1) . To check whether the increase in LIP is sufficient to induce ferroptosis in HT1080 cells, we treated cells with ferrous ammonium sulfate [Fe(NH4)2(SO4)2]. We revealed that the increase in LIP by the ferrous ammonium sulfate triggers ferroptotic cell death, which can be inhibited by Fer1 . Of note, pharmacological inhibition of HMOX1 with zinc protoporphyrin (ZnPP), a metalloporphyrin that competitively inhibits the HMOX1 activity , prevents both lipid peroxidation and ferroptotic cell death after exposure to nemorosone . Moreover, the combination of nemorosone with the HMOX1 substrate hemin increased labile Fe2+ levels, lipid peroxidation, and cell death . These findings propose that nemorosone targets the KEAP1-NRF2-HMOX1 axis to promote ferroptosis by increasing the LIP through excessive activation of heme oxygenase-1. Therefore, it can also act as a class IV FIN . To further confirm the role of HMOX1 upregulation in nemorosone-induced ferroptosis, we treated the cells with combinations of non-toxic concentrations of hemin and nemorosone. Interestingly, we observed that such a combination is sufficient to induce synergistically lipid peroxidation and cell death . 4. Discussion In the current work, nemorosone, a phytochemical isolated from the floral resin of the C. rosea plant, was identified to induce ferroptosis in fibrosarcoma and neuroblastoma cells. In 20 years of nemorosone anticancer-effect research, this is the first report that expands the potential of nemorosone by showing its capacity to induce another mechanism of cell death than apoptosis . Notably, while nemorosone was cytotoxic against the neuroblastoma and fibrosarcoma cell lines, it did not show any effect on glioblastoma U87MG and U373MG cells. In general, the sensitivity to ferroptosis depends on the different endogenous mechanisms that protect cells against the lipid peroxidation that drives ferroptosis . Recently, ferroptosis suppressor protein 1 (FSP1) was shown to play an essential role in the resistance of U373MG cells to erastin-induced System xc inhibition, while some unidentified mechanisms that support GPX4 function, independent of System xc activity, were also observed . In line with this, a higher methionine uptake has been reported in gliomas than in normal astrocytes, which positively correlated with tumor viability and aggressiveness and indicated a greater reliance on transsulfuration, a metabolic pathway that connects methionine with glutathione biosynthesis independent of the System xc antiporter . These reports allow us to explain a priori the resistance of glioblastoma cell lines to nemorosone-induced ferroptosis, although new experimental results are required to corroborate the aforementioned hypotheses. Conversely, based on the literature data, HT1080 and IMR-32 cells appear to be sensitive to the ferroptosis induced by decreased GSH levels through System xc inhibition and the increased labile iron pool (LIP) . In this investigation, it was found that nemorosone induces ferroptosis by modulating these two parameters (Section 3.2 and Section 3.4). On one hand, nemorosone-induced ferroptosis in HT1080 and IMR-32 cells involves the drop in the glutathione levels that can be associated with a blockade of the System xc cystine/glutamate antiporter or SLC7A11, which resembles the canonical ferroptosis-inducing pathway triggered by a class I FIN, such as erastin, also known as cysteine-deprivation-induced ferroptosis . Inhibition of cystine import, which is required for GSH synthesis, results in depletion of intracellular GSH levels , an important cofactor for selenium-dependent GPX4. Therefore, GSH depletion by nemorosone could indirectly inactivate GPX4, leading to production of lipid ROS, which in turn results in lipid peroxidation and ferroptotic cell death . It should be mentioned that more direct experimental approaches, such as the [14C]-cystine uptake assay , are required to confirm nemorosone-induced blockade of the System xc antiporter. Furthermore, inhibition of cystine entry is not necessarily the only pathway by which nemorosone could be lowering GSH levels. In fact, the decrease in the levels of NADPH, an electron-donor agent, relevant in the reduction of oxidized substrates, was reported as a common phenotypic effect for different structurally divergent uncoupling compounds . It has been suggested that the dissipation of the mitochondrial membrane potential renders nicotinamide nucleotide transhydrogenase (NNT) incapable of maintaining the reduced NADPH state, which in turn can affect GSH regeneration via glutathione reductase (GR) . In effect, the abundance of NADPH functions as a biomarker that is inversely correlated with the sensitivity of cells to the inducers of ferroptosis . This important experimental issue should also be studied in future research. On the other hand, nemorosone induces a non-canonical mechanism of ferroptosis by increasing the LIP, in response to the excessive activation of heme oxygenase-1 by targeting KEAP1 and NRF2, which is sufficient to trigger toxic lipid peroxidation. This result is comparable with the effect of withaferin A (WA), a natural FIN isolated from Withania somnifera roots, which at a medium dose induces ferroptosis through a massive upregulation of HMOX1 . Likewise, Tagitinin C, another natural compound, induces ferroptosis in colorectal cancer cells through the PERK-NRF2-HMOX1 signaling pathway, and again the significant overexpression of HMOX1 led to the increase in the LIP, which promoted lipid peroxidation and ferroptosis . As can be seen, these results with nemorosone add to a still small, but apparently growing, list of natural compounds that modulate the NRF2-HMOX1 axis to induce ferroptotic cell death, which could be related to some natural protection mechanism of plants (not yet reported) against pathogenic microorganisms. Similarly, HMOX1 was also shown as an essential enzyme that is involved in iron supplementation and lipid peroxidation in erastin-induced ferroptosis . By giving cancerous cells antioxidant and cytoprotective effects and by removing toxic intracellular heme, the inducible intracellular enzyme HMOX1 was also shown to play a role in cancer progression . This is in line with the fact that HMOX1 is elevated in various human malignancies such as, for example, fibrosarcoma tumors and HT1080 cells . In consequence, HMOX1 inhibition was explored to reduce tumor growth . Nevertheless, based on the current data, a massive activation of HMOX1 is important to kill HT1080 cells, strongly suggesting the efficacy of an opposite strategy: making tumor cells sensitive to the induction of ferroptosis via the therapeutic overactivation of HMOX1. At the same time, the active role of HMOX1 in tumor cells constitutes a significant difference compared to the healthy tissue and is, consequently, a way by which compounds such as nemorosone could induce a selective ferroptosis mechanism in cancer cells such as fibrosarcoma. However, nemorosone-induced activation of the NRF2-mediated oxidative stress response pathway , with the consequent modulation of NRF2 target genes (Table S1), shows that nemorosone activated the NRF2 pathway as an antioxidant and antiferroptotic response. It is the disproportionate upregulation of HMOX1 compared to other genes that results in a pro-ferroptotic effect. It is notable that HMOX1 is the gene most upregulated by nemorosone: more than 90 times compared to the control, while FTH1 is upregulated less than 3 times . That is, nemorosone generates an expression of HMOX1 30 times higher than the induced expression of FTH1, which, similar to what was reported for WA, suggests the induction of ferroptosis by raising the LIP in a context of insufficient ferritin buffering capacity . In other words, the effect of nemorosone reveals a hormetic response associated with the NRF2-HMOX1 axis: a protective effect after moderate activation (classical and most common reports) vs. a cytotoxic effect after excessive activation (reported for some naturally occurring ferroptosis-inducing compounds). It remains to be answered why nemorosone and other natural compounds generate such an overactivation of heme oxygenase-1. First of all, it must be taken into account that activation of HMOX1 by pathways other than NRF2 cannot be excluded. Several classes of stress-responsive transcription factors that activate HMOX1 gene have also been identified, such as members of the heat-shock factor (HSF), nuclear factor-kB (NF-kB), and activator protein-1 (AP-1) families . On the other hand, nemorosone was identified as a natural activator of the p300 histone acetyltransferase that enhanced histone acetylation in cells . At the same time, p300-mediated NRF2 acetylation was shown to be essential for the maximal binding of NRF2 to specific ARE (antioxidant response element)-containing promoters . Moreover, p300 was recently reported to compete with KEAP1 for the regulation of NRF2, enhancing the protein level of NRF2 and allowing NRF2 to translocate to the nucleus to upregulate the transcription of target genes . This possible nemorosone-induced epigenetic regulation of the KEAP1-NRF2-HMOX1 axis could also explain the capacity of nemorosone to induce non-canonical ferroptosis through excessive activation of HMOX1. Consistently, we observed that nemorosone also induces the downregulation of KEAP1, CUL3, and RBX1, while it upregulates SQSTM1 and EIF2AK3 (PERK) , all of which suggests the activation of the SQSTM1-KEAP1-NRF2-HMOX1 and PERK-NRF2-HMOX1 pathways as part of HMOX1 overactivation-mediated cytotoxicity. It is important to highlight that the regulation of the expression at gene level of the KEAP1-CUL3-RBX1-NRF2 complex does not exclude the possibility of regulation at the protein level by a direct binding between nemorosone and KEAP1, as was reported in the aforementioned case of withaferin A . All these factors need to be addressed in future experimental activities. The time relation existing between the two ferroptosis mechanisms triggered by nemorosone is also noteworthy: the drop of GSH, resulting in a lipid peroxidation increase, appears from 2 h (an early event), while HMOX1 overexpression, with its consequent increase in the intracellular labile Fe2+ levels, only begins at 6 to 8 h (a later event). Moreover, before the execution of the later event, there is already cell death induction in some cells. However, the cell death level is accelerated and enhanced at the time points in which HMOX1 expression can be associated with labile Fe2+ and an additional lipid peroxidation increase. It is unclear whether this difference in cell death by early lipid peroxidation due to blockage of cystine import and by the later event represent two distinct responding populations, in which cell resistance to cell death during the early lipid peroxidation wave receives a second ferroptotic hit due to HMOX1 upregulation, hemin degradation, and the increase in the labile Fe2+ pool. Importantly, high sensitization values were achieved by combining nemorosone and the substrate of HMOX1 hemin, which confirms the cytotoxic role of nemorosone-induced HMOX1 activation and points out a possible therapeutic approach to be experimentally tested in in vivo experiments. The aforementioned results allow for the conclusion that nemorosone exerts an erastin-like ferroptosis (intrinsic ferroptosis) in fibrosarcoma cells that is characterized by the concurrence of both canonical (decreasing GSH levels) and non-canonical (increasing LIP through HMOX1 upregulation) mechanisms. This may confer more therapeutic efficacy to nemorosone by circumventing the resistance mechanisms of the tumor cells that bypass the System xc blockade or the depletion of GSH levels, an effect suggested by the persistence of the induction of cell death, unlike erastin, in the presence of b-ME . On the other hand, erastin-induced cell death and, in general, cysteine-deprivation-induced (CDI) ferroptosis are exerted by transient mitochondrial membrane potential (MMP) hyperpolarization, in such a way that low concentrations (10 mM) of the mitochondrial uncoupler CCCP can prevent (by the drop of MMP) CDI lipid ROS accumulation and protect against ferroptosis . However, we confirmed that nemorosone acts as a mitochondrial uncoupler, dissipating (similar to CCCP) the transmembrane proton gradient prior to cell death execution. The possible involvement of mitochondrial uncoupling in ferroptosis induced by nemorosone was approached by using a high concentration of CCCP (50 mM) and methylnemorosone. While CCCP acted similarly to nemorosone regarding ferroptosis induction, methylnemorosone, which cannot exert mitochondrial uncoupling activity anymore, completely lost cytotoxicity. Altogether, this suggests that mitochondrial uncoupling is indeed required for nemorosone to trigger ferroptosis in fibrosarcoma cells. Furthermore, Figure S3 shows a possible link between HMOX1 over-activation and mitochondrial uncoupling: CCCP, a classic mitochondrial uncoupler, also increases Fe2+ levels upon HMOX1 upregulation. In addition, the obtained results at a high concentration of CCCP and the reported capacity to protect against erastin-induced ferroptosis at a low concentration show a dual role as uncoupler compounds to induce ferroptosis or protect against it by varying the concentration. The protective mechanism could be an important approach to treat several ferroptosis-associated diseases such as ischemic organ injury, brain damage, and kidney failure , expanding the potential application of mitochondrial uncouplers. To sum up, here, we connect, for the first time, mitochondrial uncoupling with ferroptotic cell death induction by the use of two closely related agents: proficient (nemorosone) and deficient (methylnemorosone). The cascade of cellular effects leading to ferroptosis induced by the mitochondrial uncoupler compounds in cancer cells is still an unexplored and emerging area of research and therapeutic opportunities. 5. Conclusions Here, we show, for the first time, that nemorosone can induce intrinsic ferroptosis in fibrosarcoma and neuroblastoma cells by a double-edged targeting mechanism consisting of the drop of GSH as an early event and the increase in labile Fe2+ levels through the overexpression of HMOX1 as a later event. The work also expands the current knowledge about the role of mitochondria in ferroptosis by showing that compounds with an uncoupling action can trigger an erastin-like ferroptosis mechanism linked to MMP dissipation. Acknowledgments We thank the VIB Flow Core for training, support, and access to the instrument park. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Nemorosone induces ferroptosis and mitochondrial uncoupling in neuroblastoma cells; Figure S2: Mitochondrial uncoupling triggered by nemorosone in fibrosarcoma cells; Figure S3: CCCP induces HMOX1 expression in HT1080 cells; Figure S4: RP-HPLC chromatogram of isolated (+)-nemorosone; Figure S5: 1H NMR spectrum of isolated (+)-nemorosone; Figure S6: 13C (APT) NMR spectrum of isolated (+)-nemorosone; Figure S7: 1H NMR spectrum of the crude mixture obtained after methylation of nemorosone; Figure S8: RP-HPLC chromatogram of obtained mixture of both O-methylated nemorosone isomers after chromatographic purification; Table S1: Selected ferroptosis-associated genes differentially expressed in HT1080 cells after exposition to nemorosone, CCCP and erastin in relation to the control (untreated cells); Table S2: p-values denoting the significance of enrichment of the differentially expressed pathways after treatment of HT1080 cells with nemorosone, CCCP and erastin. Click here for additional data file. Author Contributions Conceptualization, G.L.P.-A., R.F.-A., P.V., T.V.B. and B.H.; methodology, R.F.-A., G.L.P.-A. and B.H.; validation, R.F.-A. and B.H.; formal analysis, R.F.-A., G.L.P.-A. and B.H.; investigation, R.F.-A., B.H., J.C., B.W., D.A.-A., B.V., J.V.d.E. and G.L.P.-A.; data curation, R.F.-A. and B.H.; writing--original draft preparation, R.F.-A.; writing--review and editing, R.F.-A., B.H., J.C., T.V.B., P.V. and G.L.P.-A., visualization, R.F.-A., B.H. and G.L.P.-A.; supervision, G.L.P.-A., P.V. and T.V.B.; funding acquisition, G.L.P.-A. and P.V. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors have no relevant financial or non-financial interests to disclose. Figure 1 High cytotoxicity of nemorosone in human fibrosarcoma cell line HT1080 is due to ferroptosis induction. (A) Heatmap showing the sensitivity to cell death of different cancer and non-tumorigenic cell lines after exposure to various concentrations of nemorosone: HT22 (mouse hippocampal neuronal cell line), U87MG and U373MG (human glioblastoma cell lines), IMR-32 (human neuroblastoma cell line), and HT1080 (human fibrosarcoma cell line). Cell lines were incubated with nemorosone for 24 h. (B) Cytotoxic dose-response curve in HT1080 cells 12 h after nemorosone treatment. (C) Heatmap showing the sensitivity to cell death of HT1080 cells after being exposed to 100 mM of nemorosone, with or without the following inhibitors: the RIPK1-kinase inhibitor necrostatin-1 (Nec-1s, 10 mM), the pan-caspase inhibitor Z-VAD-FMK (10 mM), and the ferroptosis inhibitors ferrostatin-1 (Fer1, 1 mM), deferoxamine (DFO, 50 mM), and ciclopirox olamine (CPX, 5 mM). (D) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells) following nemorosone treatment (100 mM, 4 h). Ferroptosis inhibitors: DFO (50 mM) and Fer1 (1 mM). (E) Flow cytometry analysis (histogram) of the lipid peroxidation sensor (C11-BODIPY-581/591 dye) on live-gated HT1080 cells (DRAQ7-negative cells) after treatment with nemorosone (100 mM, 4 h) and its combination with the ferroptosis inhibitors DFO (50 mM) and Fer1 (1 mM). FI is the fluorescent intensity. Traces are representative of three independent experiments. All quantitative data are shown as mean +- SD from three separate experiments. *** p < 0.001 and **** p < 0.0001 determined by unpaired Student's t-test. Figure 2 Nemorosone acts as a class I ferroptosis-inducing compound. (A) GSH levels in HT1080 cells treated with nemorosone (100 mM) or erastin (20 mM). (B) Western blot analysis of the expression of GPX4 and b-tubulin in HT1080 cells after treatment with nemorosone (100 mM) or erastin (20 mM). (C) Intracellular glutamate levels in HT1080 cells treated with nemorosone (100 mM) or erastin (20 mM). (D) Percentage of cell death at different time points induced by nemorosone (100 mM) or erastin (20 mM) in HT1080 cells, assessed using SytoxGreen dye, in the absence or presence of b-mercaptoethanol (b-ME, 50 mM). (E) Schematic representation of some inhibitors of the mitochondrial oxidative phosphorylation. Electrons from substrates pass through complexes I to IV of the electron transport chain. Protons (H+) are pumped into the intermembrane space using the energy generated by this process. The resulting proton gradient is used to drive ATP synthesis. This figure was created with BioRender.com (accessed on 17 July 2022). (F) Percentage of cell death induced by nemorosone (100 mM) and erastin (20 mM) in HT1080 cells, assessed using SytoxGreen dye, in absence or presence of the subsequent electron transport chain inhibitors: rotenone (10 mM) and antimycin A (50 mM). (G) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells) following nemorosone treatment (100 mM, 4 h). Electron transport chain inhibitors: rotenone (10 mM) and antimycin A (50 mM). All quantitative data are shown as mean +- SD from three separate experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 determined by unpaired Student's t-test. Figure 3 Nemorosone-induced ferroptosis may be associated with mitochondrial uncoupling. (A) Phosphorylation control protocol performed by high-resolution respirometry in intact HT1080 cells (1,000,000 cells/mL). After the addition of oligomycin (1.5 mM), cells were titrated with nemorosone and methylnemorosone in steps of 5 mM additions, totalizing 30 mM of both compounds in the Oxygraph-2k chambers (2 mL). DMSO was added, similar to nemorosone. The O2 flow (pmol*s-1*mL-1) was inhibited to a constant level after the addition of rotenone-antimycin A mix (0.5 mM). Every addition is represented by vertical dot lines. (B) Oxygen consumption rate (OCR) fold increase was relative to LEAK state (reached after the inhibition of F1FO ATP synthase by oligomycin) in HT1080 cells exerted by the separated addition of DMSO (30 mM), nemorosone (30 mM), methylnemorosone (30 mM), and rotenone-antimycin A mix (Rot-Ant, 0.5 mM). (C) Percentage of cell death at different time points induced by nemorosone (100 mM) and methylnemorosone (100 mM) in HT1080 cells, assessed using SytoxGreen dye. (D) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells) following nemorosone (100 mM) or methylnemorosone (100 mM) treatment at different time points. MFI is the median fluorescence intensity of the fluorophore. (E) Percentage of cell death induced by CCCP (12 h, 50 mM) in HT1080 cells, assessed using SytoxBlue dye. Ferroptosis inhibitors: DFO (50 mM) and Fer1 (1 mM). Electron transport chain inhibitors: rotenone (10 mM) and antimycin A (50 mM). (F) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (SytoxBlue-negative cells) following CCCP treatment (12 h, 50 mM). Ferroptosis inhibitors: DFO (50 mM) and Fer1 (1 mM). Electron transport chain inhibitors: rotenone (10 mM) and antimycin A (50 mM). (G) GSH levels in HT1080 cells after treatment with CCCP (50 mM) during 2 h and 6 h. (H) Intracellular glutamate levels in HT1080 cells after treatment with CCCP (50 mM) during 2 h and 6 h. All quantitative data are shown as mean +- SD from three separate experiments. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001 determined by unpaired Student's t-test (B,D-H) and by two-way ANOVA test (C). Figure 4 Genes and signaling pathways differentially expressed after treatment with nemorosone, CCCP, and erastin in HT1080 cells. (A) Heatmap of the expression of genes that are differentially expressed after both nemorosone (100 mM) 2 h and nemorosone (100 mM) 8 h treatments, compared to the control. Each column represents a sample; each row represents a gene. The genes have been clustered, and their expression has been centered and scaled. (B) Venn diagram showing differentially expressed (DE) genes, compared to the control, regulated by one, two, or all three treatments at the same time point (nemorosone 100 mM, CCCP 50 mM, erastin 20 mM; 8 h). The direction of the arrows indicates upregulation or downregulation in the case of individual treatments. Each intersection shows the set of genes modulated by two or three treatments. The scatterplot below was made by plotting the LFC values (log2fold change), metric indicating how much the expression of a gene changes compared to the control condition of the corresponding genes indicated by the green intersection: positive values indicate higher expression than the control, and negative values indicate lower expression than the control. DE genes by erastin are colored according to their LFC value. Known ferroptosis-related genes are labeled. (C) Ridge plots showing the IPA (Ingenuity Pathway Analysis) pathways that were found to be significantly enriched in DE gene sets. Each density plot shows the distribution of the LFC values of the DE genes involved in the enriched pathway. Density plots are scaled per panel. The color indicates the z-score, which is an IPA metric that predicts activation (positive values) or inhibition (negative values) of the pathway. (D) Heatmap of the expression of selected ferroptosis-related genes. Each column represents a sample; each row represents a gene. The genes have been clustered, and their expression has been centered and scaled. Figure 5 Nemorosone-induced ferroptosis in HT1080 cells involves excessive activation of HMOX1. (A) Relative HMOX1 expression at mRNA level in HT1080 cells following nemorosone treatment (100 mM) at different time points. (B) Western blot showing KEAP1, NRF2, and HMOX1 modulation in HT1080 cells after treatment with nemorosone (100 mM). (C) Cellular levels of labile Fe2+, determined by flow cytometry using FeRhoNox-1 dye, at different time points, after nemorosone treatment (100 mM). Measurements were performed in live HT1080 cells (SytoxBlue-negative cells). Ferrous ammonium sulfate [Fe(NH4)2(SO4)2] was used as a control (2 h, 1 mM). MFI is the median fluorescence intensity of the fluorophore. (D) Heatmap showing the sensitivity to cell death of HT1080 cells treated with different concentrations of Fe(NH4)2(SO4)2 in the presence or absence of Fer1 (1 mM), assessed using SytoxGreen dye. (E) Percentage of cell death induced by nemorosone (100 mM) in the presence or absence of ZnPP (1 mM), assessed using SytoxGreen dye. (F) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells) after 8 h of treatment with nemorosone (100 mM) in the presence or absence of ZnPP (1 mM). (G) Cellular levels of labile Fe2+, determined by flow cytometry using FeRhoNox-1 dye, in response to nemorosone (100 mM), in the presence or absence of hemin (10 mM). Measurements were performed in live HT1080 cells (SytoxBlue-negative cells). Ferrous ammonium sulfate was used as a control (2 h, 1 mM). MFI is the median fluorescence intensity of the fluorophore. (H) Percentage of cell death induced by nemorosone (100 mM) in the presence or absence of hemin (10 mM) in HT1080 cells, assessed using SytoxBlue dye. (I) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells), following 8 h of treatment with nemorosone (100 mM), in the presence or absence of hemin (10 mM). (J,L) Percentage of cell death at different time points induced by nemorosone 15 and 10 mM, respectively, alone and in combination with hemin (5 mM). Cell death was assessed using SytoxGreen dye. (K,M) Analysis using flow cytometry of the C11-BODIPY lipid peroxidation sensor in live HT1080 cells (DRAQ7-negative cells) after treatment with nemorosone 15 and 10 mM, respectively, alone and in combination with hemin (5 mM) for 4 h. The combined results of 2 or 3 separate experiments are presented for (C-M). 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PMC10000522 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051114 foods-12-01114 Article Response Surface Methodology Approach for Predicting Convective/Infrared Drying, Quality, Bioactive and Vitamin C Characteristics of Pumpkin Slices Joudi-Sarighayeh Fatemeh 1 Abbaspour-Gilandeh Yousef Conceptualization Validation Resources Data curation Writing - review & editing Supervision 1* Kaveh Mohammad Conceptualization Methodology Software Formal analysis Writing - review & editing Visualization 2 Szymanek Mariusz Methodology Validation Writing - review & editing 3* Kulig Ryszard Writing - review & editing 4 Fratianni Alessandra Academic Editor 1 Department of Biosystems Engineering, College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran 2 Department of Petroleum Engineering, College of Engineering, Knowledge University, Erbil 44001, Iraq 3 Department of Agricultural, Forest and Transport Machinery, University of Life Sciences in Lublin, Gleboka 28, 20-612 Lublin, Poland 4 Department of Food Engineering and Machines, University of Life Sciences in Lublin, Gleboka 28, 20-612 Lublin, Poland * Correspondence: [email protected] (Y.A.-G.); [email protected] (M.S.) 06 3 2023 3 2023 12 5 111425 1 2023 27 2 2023 02 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). In this research, a convective/infrared (CV/IR) dryer was used to dry pumpkin slices. For optimization of the drying conditions, the influence of three levels of independent variables including air temperature (40, 55, and 70 degC), air velocity (0.5, 1, and 1.5 m/s), and IR power (250, 500, and 750 W) were assessed by response surface method (RSM) through a face-centered central composite design. Analysis of variance (non-fitting factor and R2 value) was employed to determine the desirability of the model. Response surfaces and diagrams were also utilized to show the interactive influence of the independent variables with the response variables (drying time, energy consumption, shrinkage, total color variation, rehydration ratio, total phenol, antioxidant, and vitamin C contents). According to the results, optimal drying conditions involved a temperature of 70 degC, air velocity of 0.69 m/s, and IR power of 750 W. At the mentioned conditions, response variables of drying time, energy consumption, shrinkage, color, rehydration ratio, total phenol, antioxidant, and vitamin C contents were 72.53 min, 24.52 MJ/kg, 23%, 14.74, 4.97, 617.97 mg GA/100 g dw, 81.57%, and 4.02 mg/g dw, with a confidence level of 0.948, respectively. drying pumpkin RSM total phenolic content shrinkage University of Mohaghegh Ardabili, IranMinistry of Education and Science (Republic of Poland)DNK/SP/546290/2022 This research was funded by the University of Mohaghegh Ardabili, Iran. Publication was co-financed by the state budget under the program of the Ministry of Education and Science (Republic of Poland) under the name Excellent Science--Support for Scientific Conferences entitled "XXIII Polish Nationwide Scientific Conference "PROGRESS IN PRODUCTION ENGINEERING" 2023" project number DNK/SP/546290/2022 amount of funding 162,650.00 PLN. pmc1. Introduction Pumpkin (cucurbita maxima) is one of the most important crops all around the world. This product contains highly bioactive compounds with health-boosting abilities such as polyphenols, antioxidant, carotenoids (mainly b-carotene), vitamins C and A, minerals, polysaccharides, and edible fibers . The presence of bioactive compounds in pumpkin shows it as a functional food or ingredient for the development of a variety of innovative food products with health-promoting properties . Additionally, due to its bioactive properties, carotenoids, and vitamins, pumpkin has beneficial effects on human health, including: reducing the risk of neurological, heart, and cancer diseases , the prevention of osteoporosis , and high blood pressure . The high moisture content of pumpkin (90.1 +- 0.3%), however, makes it prone to microbial decay. Hence, pumpkin fruits need to be kept either frozen or dried. Pumpkin is often distributed in the form of a raw vegetable, and a processed product (frozen, dried, pureed, or pre-cooked) to enhance its stability during storage . Drying can prolong the useful life of food products and play a decisive role in agricultural products by evaporating their moisture content, hence meddling with the growth of the microbial agents which grow in humid media . Despite its time-consuming and energy-demanding nature, drying approaches are necessary in the production of sustainable products with minimum water contents which can cause a dramatic decline in the weight and volume of the product, hence facilitating its storage and transport . The drying methods can be generally divided into traditional and industrial classes . The long drying time in the traditional methods can increase the possibility of microbial growth; on the other hand, the industrial methods can maintain the quality of the foods at a desirable level while drastically shortening the drying time . The quality of the final product is one of the main indicators of the drying process as the quality may vary during the mass and heat transfer or chemical reactions, affecting the consumer satisfaction in terms of the physical (shape, color, and texture) and nutritional (vitamins, antioxidants, and phenolic compounds) features . Regarding the high latent heat of water and relatively low energy efficiency of the industrial dryers, high input energy is required for the drying process, leading to high heating costs . Among the various dying methods, one capable of decreasing the energy consumption and drying time while enhancing the quality of the final product is highly welcome. A convective (hot air) dryer is a simple, conventional, and low-cost method for drying food products which suffers from a long drying time and low energy efficiency . Infrared drying, on the other hand, can provide fast and uniform heat distribution through electromagnetic waves within the product, decreasing the energy consumption and drying period while enhancing the quality of final product . A combinational use of convective and IR dryers can offer the advantages of both methods (i.e., maintaining the quality of the final product and shorter drying time) . Hybrid dryers have been used for drying various products including rice by fluidized bed-IR-microwave , apple by microwave/CV and CV/IR , chrysanthemum by CV/IR dryer , walnut kernel by the IR-vacuum and IR-fluidized bed with microwave pretreatment , tomato by CV/IR and microwave-CV , and okra by IR-freeze-drying and microwave vacuum . The response surface method (RSM) refers to a series of mathematical and statistical methods to model and analyze the problems in which the response variable is under the influence of several independent variables to optimize the response variables . RSM evaluates the mutual relationships between the input (independent) variables and their impact on the response (dependent) variable. The aim of the modeling is to achieve the best system performance and promote the cost-effectiveness of the drying process through rational predictions . This method has been extensively utilized in drying food products such as rough rice , echinacea root , lime , cumin seeds , and apple . Prashob et al. determined optimal drying conditions for drying shrimp by hot air-assisted continuous infrared drying at various IR powers, temperature, and IR lamp-product distance using RSM. Nanvakenari et al. also addressed the optimization of operation conditions to dry rice using a fluidized bed-assisted hybrid IR-microwave dryer through the RSM and verified the reliability of the model based on the experiments. Drying conditions of the microwave-assisted fluidized bed dryer were optimized for red bell pepper . The derived model was also experimentally verified. RSM can accurately predict SEC, color, and RR for drying ginger slices in a CV/IR dryer . Dhurve et al. examined the mutual effects of air temperature, air velocity, IR power, and vibration intensity on the TPC, flavonoid, and AA of pumpkin seeds dried by a hybrid IR-vibro fluidized bed dryer using RSM. They indicated the significant influence of the input parameters on the response values. A review of the literature showed that no study has addressed the performance and optimization of a hybrid CV/IR dryer for drying pumpkin slices considering the air temperature, air flow velocity, and IR power. In this context, a continuous CV/IR dryer was used in this study to dry pumpkin slices in which the heat was supplied by a heater (supplier of the air temperature) and four IR lamp. To this end, the operational features such as drying time, specific energy consumption (SEC), color, shrinkage, RR, and AA, TPC, and VC contents were assessed. Additionally, the optimal condition of the dryer was determined by selecting the proper air temperature, air velocity, and IR power using the RSM method. 2. Materials and Methods 2.1. Sample Preparation Pumpkins were purchased form a local market in Sardasht (west Azarbyjan, Iran). The samples were then kept in plastic bags in a refrigerator (3-5 degC) to prevent the decline in initial moisture content (MC); for the tests, the samples were put at room temperature for 2 h to reach the ambient temperature . Pumpkins were cut into 4-mm slices using a cutter. The initial moisture content of the samples was measured by putting the slices at 70 degC for 24 h using an oven (Memmert, UFB 500, Schwabach, Germany). The initial moisture content was obtained 6.38 +- 0.1 on dry basis (% d.b). 2.2. Drying In this research, the pumpkin samples were dried in a convective/infrared (CV/IR) dryer designed by the biosystem engineering department of Mohaghegh Ardabili University, Ardabil, Iran . The utilized dryer included a drying chamber (120 x 100 x 130 cm3), a centrifugal fan, thermal elements (3 heating elements and IR lamps), and a control unit (encompassing blowing speed controller, thermometer of the input air, and controller of the number of on/off IR lamps). Four IR lamps, (each with the power of 250 W) were placed within and above the drying chamber. The lamps were 15 cm above the samples. Regarding the test conditions, 3 levels of IR power (maximum 3 IR lamps with power of 750 w) were used. A centrifugal lamp (1 hp/3000 rpm) was utilized to supply the input air at the beginning of dryer while a gate was installed at the top of the dryer for exhaust of air and humidity. The speed of the input air was adjusted by an invertor (LS, Seoul, Republic of Korea). The temperature of the input air was also regulated by a thermostat (Atbin, Tehran, Iran) equipped with K-type thermocouples. The weight of the samples was also measured every 5 min using a digital balance (AND GF-6000) at the resolution of 0.001. The tests were continued until the MC of the pumpkin slices reached from 6.38 (d.b) of the initial MC to 0.12 (d.b). The drying tests were carried out at three air temperatures of 40, 55, and 70 degC, three IR powers of 250, 500, and 750 W, and three airflow of 0.5, 1, and 1.5 m/s in a central composite design. 2.3. Moisture Content The MC of the samples was determined by Equation (1) :(1) MCd.b=Wi-WfWf 2.4. Specific Energy Consumption The specific energy consumption refers to the ratio of the total energy consumption for drying pumpkin slices to the water loss during the drying process. The equations used to determine the SEC of a CV/IR dryer can be found in Table 1. 2.5. Quality Features 2.5.1. Color The color of the dried samples was evaluated based on L*, a*, and b* parameters using a color-meter (HP-200, Guangdong, China). The color change (E) in the pumpkin samples after drying can be determined by Equation (8) : (8) DE=(DL*)2+(Da*)2+(Db*)2 2.5.2. Shrinkage The shrinkage of the pumpkin samples was measured by fluid displacement (toluene) . The volume variations of the samples before and after drying was measured. Then, the shrinkage was determined by Equation (9) :(9) Sa=(1-VtV0)x100 2.5.3. Rehydration Ratio Water resorption can indicate the physiochemical variations during the drying process. It could also be a measure of damage made to the sample texture. To assess rehydration ratio, 5 g of the dried sample was floated in distilled water for 1 h (100 mL, 20 degC). After removing the sample from water and drying the excessive water, the rehydration ratio was determined by Equation (10) :(10) RR=WrWd 2.6. Bioactive Properties 2.6.1. Antioxidant Activities Antioxidant activities of the samples was quantified by measuring the inhibitory ability against DPPH free radicals. In this method, 2 mL of the extract was mixed with 2 mL of methanolic DPPH solution and shaken in darkness for 30 min. The absorbance of the sample was measured at 520 nm. Equation (11) shows the free radicals' inhibition percentage :(11) AA=(1-AsAc)x100 2.6.2. Total Phenol Content (TPC) Total phenol content was measured using Folin-Ciocalteu reagent in the form of gallic acid and expressed . In this method, 0.4 mL of the extract was mixed with 3 mL of water-diluted Folin-Ciocalteu reagent solution (1:10). After resting at room temperature for 5 min, 3 mL of sodium bicarbonate (7%) was added. The solution was kept at room temperature (22 degC) for 90 min and the absorbance of the samples was spectroscopically read at 752 nm. 2.7. Vitamin C Vitamin C was measured using an HPLC device (made in Iran; Danchrom hplc model). The extract preparation involved combining 300 mg of powdered sample and 30 mL of 4.5% metaphosphoric acid solution followed by 5 min of stirring. The resulting solution was then centrifuged at 4000 rpm for 15 min and the centrifuged solution was kept in a refrigerator at 4 degC for 1 h. The injection volume was 20 mL and the column temperature was 25 degC with separation using a Eurosphere column (Eurosphere, C18, 5 x 4/6 x 250). The absorption of the sample was read at a wavelength of 245 nm, the mobile phase was in 0.01% sulfuric acid, and the flow rate was 1 mL/min. 2.8. Response Surface Method (RSM) The best conditions for the production of dried pumpkin samples with a CV/IR dryer were determined using a response surface method as implemented in Design Expert 10 software. In this research, the central composite design (CCD) with three independent variables (air temperature, air velocity, and infrared power) at three levels (Table 2) was employed, and their effects were assessed on the dependent variables. In the RSM, the goal is to optimize the response variable, which is influenced by many variables. The optimal value (y) can be obtained by solving the regression Equation (12) :(12) y=b0+i=1kbixi+ijbijxixj+i=1kbiixi2+e In the above relationship, b0, bi, bii, and bij are parameters related to regression coefficients, while xi and xj denote independent variables. k represents the number of variables, and e shows the error. The coded levels of independent variables and experimental design along with the response of drying time, SEC, shrinkage, RR, color, and TPC, AA, and VC contents are presented in Table 2 and Table 3 at different levels of independent variables, respectively. The test data performed at air temperature 55 degC temperature, air velocity of 1 m/s, and IR power 500 W, were repeated 6 times (Table 3). To achieve optimal conditions in terms of the objectives of this study, the maximum value of RR, TPC, AA, and VC, as well as minimum drying time, SEC, shrinkage, and color variations, were considered. 3. Results and Discussion Table 4 shows the fitted statistical values for dependent variables (drying time, SEC, shrinkage, color, RR, and TPC, AA, and VC). According to Table 4 and the statistical values of all the responses, the value of the coefficient of determination (R2) was above 0.91 while the coefficient of variation (C.V.) was less than (7) for all models, suggesting good reproducibility of models. Moreover, with the non-significance of the misfit factor indicated that all the presented models accurately predicted the changes in the dependent variables. 3.1. Drying Time Table 5 lists the analysis of variance for the response of drying time. Accordingly, the linear expression of air temperature, air velocity, and IR power are significant with the response of drying time (p < 0.0001). In addition, the second-order expression of air velocity and the interactive effect of air temperature and infrared power are also significant at the probability level of p < 0.0005. The second order and the interactive effect of other parameters were not significant. The longest drying time (250 min) was obtained at air temperature of 40 degC, air velocity of 0.5 m/s, and IR power of 250 W whereas the shortest drying time (60 min) was recorded at air temperature of 70 degC, air velocity of 1.5 m/s, and IR power of 750 W. Figure 1 shows the interactive effect of air temperature-air velocity and IR power-air temperature with the dependent variable of drying time. Accordingly, the drying time decreases with the elevating air temperature and IR power, due to the increase in the movement of water molecules in the product which enhanced the water evaporation rate of the samples, elevating the heat transfer flow in the samples and accelerating the evaporation. In addition, a rise in the IR power led to the rapid heating of the product, better water evaporation, and ultimately a reduced drying time . Similar results were reported in drying slices of pear , lemon , and strawberry . According to Figure 1, the increase in all three factors shortened the drying time. It can be said that air temperature, IR power, and air velocity show the greatest effect on reducing drying time, respectively. Simultaneous use of IR power and temperature will increase the temperature of the dryer which can increase the moisture absorption capacity due to the increase in the product-air temperature difference. On the other hand, this reduces the drying time by a faster increase in the product temperature and water evaporation . 3.2. Specific Energy Consumption Table 6 shows the analysis of variance for SEC response. Accordingly, the linear relationship between air temperature, air velocity, and IR power with the SEC variable is significant (p < 0.0001). The interactive air temperature-air velocity relationship with the SEC response is also significant (p < 0.01). Figure 2 shows the interactive effect of air temperature-air velocity on the SEC response. As seen, air temperature enhancement from 40 to 70 degC at the high air velocity (1.5 m/s) reduced the SEC with a greater slope compared to the low air velocity (0.5 m/s). However, increasing the air velocity incremented the SEC. According to Figure 2, SEC decreased with increasing IR power and air temperature. The reason could be the accelerated water evaporation at high temperature and low air velocity, which significantly reduced the drying time, hence, causing a decline in the SEC. Moreover, all energy of IR lamps is directly radiated to the sample and heats it, which decremented the energy loss . Based on Figure 2, however, air velocity has a direct relationship with SEC, in other words, the increase in air velocity enhanced the SEC. At low air speeds, the SEC decreased due to the rise in the effective contact between air and pumpkin samples and increased moisture evaporation rate as a result of IR heating. The increase in the SEC with the elevation of air velocity can be attributed to the cooling of the sample surface that reduces the moisture evaporation, prolonging the drying time . To improve the processing and the quality of poria cocos with vacuum and CV/IR dryers, Zhang et al. concluded that the vacuum process has the highest level of SEC (6.21 MJ/kg) while CV/IR led to the lowest SEC (1.38 MJ/kg). Based on the work of Chen et al. , infrared heating along with hot air reduced SEC in drying carrots. 3.3. Quality Features 3.3.1. Color According to Table 7, listing the analysis of variance for the color index, the linear relationship of air temperature, and IR power with the color response is significant (p < 0.0001). Based on Figure 3, the color changes showed a downward trend with the rising air temperature while the air velocity had no significant effect on the color, and it is not mentioned in Table 7. The greatest color change occurred at an air temperature of 40 degC and an IR power of 250 W. By raising the air temperature and infrared power, the intensity of the color decreased. The lowest color changes were recorded at 70 degC and an IR power of 750 W. One of the reasons could be the influences on the nutrients in long drying times at low temperatures. Additionally, more heat will penetrate into the samples at higher IR powers, elevating its temperature. In this way, enzymatic and non-enzymatic browning reactions, burning, and darkening of the surface of the samples were reduced. In a study on terebinth, the milder color change in the samples dried in the CV/IR method (compared to the IR dryer) is the faster drying and shorter drying time, which prevented the pigment degradation, leading to better color preservation . 3.3.2. Shrinkage Table 8 lists the analysis of variance results for shrinkage response. As seen, the linear relationship of air temperature and IR power with shrinkage is significant at (p < 0.0001) level. As can be observed, the air velocity had no significant influence on the shrinkage response; while the interactive air velocity-air temperature and air temperature-IR power effects were significant on the shrinkage. Figure 4 also demonstrates the interactive effects of the independent variables with the shrinkage (dependent response). As with IR power, changes in the air speed had no meaningful impact on the shrinkage; while the shrinkage showed a decline by raising the air temperature. Furthermore, temperature elevation at the low infrared power significantly decreased shrinkage compared to the high IR power. The highest shrinkage (49.95%) occurred at 40 degC and IR power of 250 W. Long-term heating leads to high moisture escape during the drying process as well as thermal stresses in the samples, hence, increasing the shrinkage . El-Mesery et al. dried tomato slices by a CV/IR dryer and reported a decrement in the shrinkage by increasing the IR power. 3.3.3. Rehydration Ratio (RR) RR is one of the major quality indicators of dry products. It can be said that better products have a higher RR. The highest RR (4.98) was obtained at an air temperature of 70 degC, air velocity of 0.5 m/s, and IR power of 750 W while the air temperature of 40 degC, air velocity of 0.5 m/s, and IR power of 250 W led to the lowest RR (1.75). Table 9 shows the results of the analysis of variance for RR response. Accordingly, the linear relationship between air temperature and IR power with RR response is significant (p < 0.0001). The interactive effect of air temperature-IR power is also significant (p < 0.0005). Other parameters had no significant influence on the resorption ratio. Figure 5 shows the mutual influence of independent variables on RR response. As seen, a rise in the air temperature enhanced the RR, while air velocity showed no effect. Moreover, RR increased with the enhancement in air temperature and IR power. The highest RR was observed at an air temperature of 70 degC and IR power of 750 W, as the increase in air temperature and IR power prevented tissue destruction and reduced product shrinkage due to the shorter drying time . Similar results were observed during pomegranate drying using a hybrid CV/IR dryer by Briki et al. . El-Mesery et al. investigated the effect of a hybrid dryer (CV/IR) on the qualitative characteristics of garlic slices and found an increment in the RR with the increase in temperature and IR power which is consistent with the present research. 3.4. Bioactive Properties 3.4.1. Total Phenol Content (TPC) According to Table 10, the analysis of variance for TPC shows a significant linear relationship between air temperature and IR power with TPC (p < 0.0001). The second-order expression of air temperature was also significant (p < 0.001). Figure 6 shows the effect of independent variables on TPC response. According to Figure 6, TPC increases with raising the air temperature, while the air velocity had no significant effect. Moreover, TPC exhibited a descending trend with declining IR power and air temperature. The reduction in TPC during the drying process can be assigned to the irreversible oxidative reactions and thermal decomposition during long-term heating . Examining TPC in samples dried by the CV/IR method compared to those dried by the hot air and IR method suggested higher levels of TPC. In the CV/IR method, bioactive compounds are released due to changes in the structure. These changes can have adverse effects in terms of preserving bioactive compounds, but in this study, it showed a positive effect (increase) in TPC . These findings agree with the reports of Vega-Galvez et al. for drying papaya. 3.4.2. Antioxidant Activity (AA) The highest and lowest AA contents in pumpkin samples were 83.24% (at 70 degC, 0.5 m/s, and 750 W) and 49.92% (at 40 degC, 0.5 m/s, and 250 W), respectively. Table 11 presents the analysis of variance for AA response. As seen, air temperature and IR power have a significant linear relationship (p < 0.0001) with AA. Figure 7 shows the effect of air temperature and air velocity on the AA in which the AA rose with the elevation in the air temperature. The air velocity, however, is not significant as it follows a constant trend. Concerning the effect of air temperature and IR power on AA response, the increase in both factors incremented the AA as the maximum AA was observed at 70 degC and 750 W, which could be due to the formation of a Maillard reaction . Disturbance in the cell wall can result in the release of oxidizing and hydrolytic enzymes which can lead to the destruction of antioxidants in fruits and vegetables. The thermal process at low-temperatures, however, activates these enzymes and causes the loss of phenolic acid due to long-term exposure to heat. The increase in temperature, though, prevents the loss of phenolic acid due to less disturbance in the cell wall, and as a result, the antioxidant capacity increases . Many other researchers also reported a rise in the AA with the enhancement in the temperature and IR power . 3.5. Vitamin C (VC) Vitamin C is a vital nutrient for human health. Thermal instability explains the selection of VC as an indicator of the heat treatment process. In general, preservation of VC could indicate that other nutrients are also preserved . The VC content of pumpkin samples was in the range of 1.57 mg/g dw (temperature of 40 degC, air velocity of 1.5 m/s, and IR power of 250 W) which rose to 4.11 mg/g dw (at 70 degC, air velocity of 0.5 m/s, and IR power of 750 W). Vitamin C is highly sensitive to heat and will be rapidly oxidized. It will be decomposed by enhancing the drying time and temperature of the drying process, therefore, high-temperature and short-period drying approaches are recommended to prevent the loss of VC while achieving high drying efficiencies. In this way, moisture will be declined to a desirable level while avoiding VC loss. According to Table 12 for the ANOVA results of the VC response, there is a linear relationship between air temperature and IR power with VC (p < 0.0001); meanwhile, the air velocity showed no significant relationship. Figure 8 demonstrates the influence of the independent variables of the VC content; as seen, a rise in the air temperature and IR power enhanced the VC content. The minimum VC was observed at the lowest air temperature and IR power. Decline in VC can be assigned to the longer exposure of the samples in the drying chamber and increased IR intensity, which finally altered the nature of the product and resulted in its thermal damage. Previous results also mentioned the usefulness of the shorter drying times in preservation of VC . 3.6. Optimization Optimal operation conditions were explored by numerical optimization techniques for the optimal drying of pumpkin slices using a CV/IR dryer. Here, the aim of optimization (see Table 13) is to minimize the drying time, SEC, shrinkage, and color variation in the pumpkin samples while maximizing their RR and TPC, VC, and AA. Table 13 presents the optimized independent and dependent variables for drying pumpkin slices by a CV/IR dryer. Accordingly, the optimal drying time involved the air temperature, air velocity, and IR power of 70 degC, 0.69 m/s, and 750 W, respectively. The mentioned optimal condition led to drying time, SEC, shrinkage, color variation, RR, TPC, AA, and VC of 72.53 min, 24.52 MJ/kg, 23%, 14.74, 4.97, 617.67 mg GA/100 g dw, 81.57%, and 4.02 mg/g dw, respectively, with a confidence level of 0.948. Table 14 lists the fitted model coefficients of the regression equation for the response variables (IR power, air velocity, and air temperature). 4. Conclusions In the present research, effective parameters of the drying time, SEC, and physiochemical properties of pumpkin slices were assessed during drying by a thin film dryer using a RSM software and an axial central cubic design (CCD) considering three independent variables of IR power (250, 500, and 750 W) air temperature (40, 55, and 70 degC), and air velocity (0.5, 1 and 1.5 m/s) in a hybrid CV/IR dryer. The process time and specific energy consumption were decreased with increasing temperature and infrared power. Specific energy consumption for pumpkin drying is the lowest (24.52 MJ/kg) at drying temperature (70 degC) and IR power (750 W) and air velocity (0.5 m/s). The pumpkin slices dried at 70 degC and 750 W had the highest retention of VC, and antioxidant activity and total phenol contents. The results can be included in the design of an optimal dryer. The results indicated that the presented models had proper efficiency in predicting, optimizing, and modifying the evaluated parameters during the drying process. The IR power and air temperature and speed were 750 W, 70 degC, and 0.69 m/s, respectively, which resulted in the desirability factor of 0.948. Application of the mentioned conditions can usefully decrease the waste and number of experiments for drying pumpkin slices using a hybrid CV/IR dryer. Author Contributions Conceptualization, Y.A.-G. and M.K.; methodology, F.J.-S., M.K. and M.S.; software, F.J.-S. and M.K.; validation, Y.A.-G. and M.S.; formal analysis, F.J.-S. and M.K.; investigation, Y.A.-G., M.K. and M.S.; resources, F.J.-S. and M.K.; data curation, Y.A.-G. and M.K.; writing--original draft preparation, F.J.-S. and M.K.; writing--review and editing, Y.A.-G., M.S. and R.K.; visualization, M.S. and M.K.; supervision, Y.A.-G. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Nomenclature AA % Antioxidant activity A m2 Tray area AS - Absorbance values of the blank At - Absorbance values of the sample Cp kJ/kg degC Specific heat Et kJ Energy consumption EUmec kJ Mechanical energy EUIR kJ Energy consumption in infrared dryer EUCV kJ Energy consumption in convective dryer EUter kJ Thermal energy consumption K W IR power (W) MCd.b % d.b Moisture content dry basis MW kg Weight loss Sa % Shrinkage SECCV/IR kJ/kg Energy consumption in CV/IR dryer V0 cm3 Initial volume Vt cm3 Final volume u m/s Inlet air velocity t s Drying time Wr kg Weight of the sample before rehydration Wd kg Weight of the sample after rehydration Wi kg Initial weight of the samples Wd kg Dry matter ra kg/m3 Air density DT degC Temperature difference DP mbar Pressure difference DL*, Db*, Da* The difference between the color of fresh and dried samples Figure 1 Interaction of air temperature/air velocity, air temperature/IR power, and IR power/air velocity on drying time of pumpkin. Figure 2 Interaction of air temperature/air velocity, air temperature/IR power, and IR power/air velocity on energy consumption of pumpkin. Figure 3 Interaction of air temperature/air velocity and air temperature/IR power on color of pumpkin. Figure 4 Interaction of air temperature/air velocity, air temperature/IR power, and IR power/air velocity on shrinkage of pumpkin. Figure 5 Interaction of air temperature/air velocity, air temperature/IR power, and IR power/air velocity on rehydration ratio of pumpkin. Figure 6 Interaction of air temperature/air velocity, air temperature/IR power, and IR power/air velocity on TPC of pumpkin. Figure 7 Interaction of air temperature/air velocity and air temperature/IR power on AA of pumpkin. Figure 8 Interaction of air temperature/air velocity and air temperature/IR power on VC of pumpkin. foods-12-01114-t001_Table 1 Table 1 Formulas used for determining the energy consumption of CV/IR. Equation Equation Number References EUter=AnraCpDT*t (2) EUmec=DPMairt (3) EUCV=EUter+EUmec (4) EUIR=Kt3600 (5) Et(CV/IR)=Equation (4)+Equation (5) (6) SEC=Et(CV/IR)MW (7) foods-12-01114-t002_Table 2 Table 2 Independent variables and their levels. Independent Variables Coded Variables Levels -1 0 +1 Air temperature (degC) X1 40 55 70 Air velocity (m/s) X2 0.5 1 1.5 IR power X3 250 500 750 foods-12-01114-t003_Table 3 Table 3 Experiment design and value of dependent variables at different levels of independent variables. Number Air Temperature (degC) Air Velocity (m/s) IR Power (W) SEC (MJ/kg) Drying Time (Min) Shrinkage (%) RR Color TPC (mg GA/100 g dw) AA (%) VC (mg/g dw) 1 40 1.5 750 64.74 130 31.29 2.79 20.29 540.35 63.69 3.11 2 55 1 500 45.54 130 33.34 3.24 22.11 488.88 66.89 2.89 3 55 1 250 51.71 170 40.40 2.22 26.65 420.24 54.56 2.35 4 55 1 500 44.32 120 31.25 3.2 20.25 468.65 70.11 2.64 5 40 0.5 750 29.92 170 34.49 2.66 22.22 539.19 60.68 2.96 6 55 1.5 500 58.8 120 35.59 3.26 23.35 466.69 62.69 2.45 7 55 1 500 42.11 125 32.23 3.44 21.29 501.21 67.25 2.83 8 70 0.5 750 24.52 75 22.54 4.98 14.25 611.29 83.24 4.11 9 55 0.5 500 29.26 140 34.57 3.11 24.23 486.34 64.57 2.65 10 40 1 500 54.04 180 42.24 2.29 25.22 444.35 55.11 2.08 11 55 1 750 41.91 95 29.29 4.22 18.23 545.55 73.80 3.19 12 55 1 500 46.54 130 35.56 2.95 23.05 455.88 66.52 2.94 13 70 0.5 250 32.31 120 29.45 2.56 25.2 485.65 60.61 2.67 14 55 1 500 48.25 135 38.87 3.15 22.04 482.50 62.50 3.01 15 55 1 500 50.50 140 33.14 3.33 21.9 497.25 60.99 3.11 16 70 1.5 250 57.83 100 34.59 2.77 26.01 480.57 64.59 2.44 17 70 1 500 39.53 80 28.87 3.76 20.21 570.30 75.25 3.42 18 70 1.5 750 39.32 60 25.11 4.66 15.01 605.59 82.25 4.08 19 40 0.5 250 49.19 250 49.95 1.75 32.07 388.96 49.92 1.64 20 40 1.5 250 80.36 230 47.89 1.82 30.22 393.34 51.59 1.57 foods-12-01114-t004_Table 4 Table 4 Statistical values fitted for dependent variables by response surface method. Source Drying Time SEC Shrinkage Color RR TPC AA VC Model (p-value) 0.0001 a 0.0001 a 0.0001 a 0.0001 a 0.0001 a 0.0001 a 0.0001 a 0.0001 a Lack of Fit (p-value) 0.6159 ns 0.5868 ns 0.9985 ns 0.3221 ns 0.4103 ns 0.8821 ns 0.8137 ns 0.3368 ns R2 0.9853 0.9628 0.9476 0.9415 0.9603 0.9585 0.9147 0.9248 Adj. R2 0.9801 0.9528 0.9337 0.9346 0.9528 0.9507 0.9047 0.916 Predicted R2 0.964 0.9183 0.9315 0.9208 0.9327 0.9399 0.8796 0.9031 C.V. 4.96 6.12 5.07 4.9 5.89 2.76 4.27 6.73 Std. Dev. 6.69 2.85 1.75 1.11 0.18 13.61 2.77 0.19 a = significant at 0.1%. ns = Not significant. foods-12-01114-t005_Table 5 Table 5 Analysis of variance for drying time response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 42,073.13 5 8414.63 187.92 <0.0001 significant A-Air temperature 27,562.50 1 27,562.50 615.55 <0.0001 B-Velocity 1322.50 1 1322.50 29.54 <0.0001 C-IR power 11,560.00 1 11,560.00 258.17 <0.0001 AC 1128.13 1 1128.13 25.19 0.0002 C2 500.00 1 500.00 11.17 0.0048 Residual 626.87 14 44.78 Lack of Fit 376.87 9 41.87 0.84 0.6159 not significant Pure Error 250.00 5 50.00 Cor Total 42,700.00 19 foods-12-01114-t006_Table 6 Table 6 Analysis of variance for SEC response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 3150.12 4 787.53 96.97 <0.0001 significant A-Air Temperature 717.82 1 717.82 88.38 <0.0001 B-Velocity 1845.92 1 1845.92 227.29 <0.0001 C-IR power 503.96 1 503.96 62.05 <0.0001 AB 82.43 1 82.43 10.15 0.0061 Residual 121.82 15 8.12 Lack of Fit 78.32 10 7.83 0.90 0.5868 not significant Pure Error 43.50 5 8.70 Cor Total 3271.95 19 F-value: The F-value in the ANOVA also deteremins the p-value. foods-12-01114-t007_Table 7 Table 7 Analysis of variance for color response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 337.59 2 168.79 136.79 <0.0001 significant A-Air Temperature 86.08 1 86.08 69.76 <0.0001 C-IR power 251.50 1 251.50 203.82 <0.0001 Residual 20.98 17 1.23 Lack of Fit 16.59 12 1.38 1.58 0.3221 not significant Pure Error 4.38 5 0.88 Cor Total 358.56 19 foods-12-01114-t008_Table 8 Table 8 Analysis of variance for shrinkage response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 832.87 4 208.22 67.88 <0.0001 significant A-Air Temperature 426.41 1 426.41 139.00 <0.0001 C-IR power 354.74 1 354.74 115.64 <0.0001 AB 21.03 1 21.03 6.85 0.0194 AC 30.69 1 30.69 10.01 0.0064 Residual 46.01 15 3.07 Lack of Fit 8.02 10 0.80 0.11 0.9985 not significant Pure Error 38.00 5 7.60 Cor Total 878.88 19 foods-12-01114-t009_Table 9 Table 9 Analysis of variance for RR response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 12.95 3 4.32 128.93 <0.0001 significant A-Air temperature 5.51 1 5.51 164.42 <0.0001 C-IR power 6.71 1 6.71 200.32 <0.0001 AC 0.74 1 0.74 22.04 0.0002 Residual 0.54 16 0.033 Lack of Fit 0.40 11 0.036 1.30 0.4103 not significant Pure Error 0.14 5 0.028 Cor Total 13.49 19 foods-12-01114-t010_Table 10 Table 10 Analysis of variance for TPC response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 68,356.50 3 22,785.50 123.06 <0.0001 significant A-Air temperature 19,999.68 1 19,999.68 108.01 <0.0001 C-IR power 45,321.17 1 45,321.17 244.77 <0.0001 A2 3035.65 1 3035.65 16.39 0.0009 Residual 2962.58 16 185.16 Lack of Fit 1453.87 11 132.17 0.44 0.8821 not significant Pure Error 1508.71 5 301.74 Cor Total 71,319.08 19 foods-12-01114-t011_Table 11 Table 11 Analysis of variance for AA response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 1400.46 2 700.23 91.18 <0.0001 significant A-Air temperature 721.65 1 721.65 93.97 <0.0001 C-IR power 678.81 1 678.81 88.39 <0.0001 Residual 130.56 17 7.68 Lack of Fit 74.20 12 6.18 0.55 0.8173 not significant Pure Error 56.36 5 11.27 Cor Total 1531.02 19 foods-12-01114-t012_Table 12 Table 12 Analysis of variance for TPC response using RSM. Source Sum of Squares df Mean Square F Value p-Value Prob > F Model 7.47 2 3.73 104.56 <0.0001 significant A-Air Temperature 2.87 1 2.87 80.43 <0.0001 C-IR power 4.60 1 4.60 128.70 <0.0001 Residual 0.61 17 0.036 Lack of Fit 0.48 12 0.040 1.52 0.3368 not significant Pure Error 0.13 5 0.026 Cor Total 8.08 19 foods-12-01114-t013_Table 13 Table 13 The results of optimizing the process of drying pumpkin samples with CV/IR. IR Power (W) Air Velocity (m/s) Air Temperature (degC) Drying Time (Min) SEC (MJ/kg) Color Shrinkage (%) RR TPC (mg GA/100 g dw) AA (%) VC (mg/g dw) 750 0.69 70 72.53 24.52 14.74 23 4.97 617.97 81.57 4.02 foods-12-01114-t014_Table 14 Table 14 Coefficients of the model fitted to the regression equation of response variables (A, air temperature, B, air velocity, and C, IR power). Response Intercept A B C AB AC BC A2 C2 SEC 46.53 -8.472 a 13.586 a -7.099 a -3.209 a Drying time 130 -52.5 a -11.5 a -34 a 11.875 a 10 a Shrinkage 34.53 -6.53 a -5.956 a 1.621 b 1.958 a Rehydration ratio 3.108 0.742 a 0.819 a 0.303 a Color 22.69 -2.934 a -5.015 a TPC 481.319 44.721 a 67.321 a 24.64 a Antioxidant capacity 64.840 8.495 a 8.239 a Vitamin C 2.807 0.536 a 0.678 a a = significant at 0.01%; b = significant at 0.05%. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Monteiro R.L. Link J.V. Tribuzi G. Carciofi B.A. Laurindo J.B. Microwave vacuum drying and multi-flash drying of pumpkin slices J. 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PMC10000523 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051027 foods-12-01027 Article Novel Method of Increased Efficiency Corn Drying on a Fixed Bed by Condensation Fu Daping 12 Wu Wenfu 13 Wang Guiying 14* Xu Hong 4 Han Feng 1 Liu Zhe 1 Morais Alcina M.M.B. Academic Editor 1 College of Biological and Agricultural Engineering, Jilin University, 5988 Renmin Road, Changchun 130025, China 2 College of Engineering and Technology, Jilin Agricultural University, 2888 Xincheng Street, Changchun 130118, China 3 Jilin Business and Technology College, 1666 Cullen Lake Road, Changchun 130507, China 4 College of Materials Science and Engineering, Jilin University, 5988 Renmin Road, Changchun 130025, China * Correspondence: [email protected]; Tel.: +86-13-844-178-220 28 2 2023 3 2023 12 5 102709 1 2023 22 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Exhaust air recycling is a simple and commonly used technique to save energy when using a dryer. The fixed-bed drying test device with increased efficiency by condensation is a clean and energy-saving drying test device developed by combining exhaust air recycling and condensation dehumidification technology. In this paper, through comparisons with or without exhaust air circulation using the single factor test of drying process parameters and the response surface test of corn drying on this test device to investigate the energy-saving effect and drying characteristics resulting from the novel drying method of increased efficiency by condensation. We drew the following main conclusions: (1) increased efficiency drying by condensation resulted in an energy savings of 32-56% compared with the conventional open hot air drying; and (2) during the increased efficiency corn drying by condensation, the mean energy and exergy efficiencies were within 31.65-51.26% and 41.69-63.52%, respectively, when the air temperature was in the 30-55 degC range, and they were 24.96-65.28% and 30.40-84.90%, respectively, when the air passed through the grain layer at 0.2-0.6 m/s; both of these increased with increasing air temperature, and decreased with increasing air velocity. These conclusions may constitute an important reference for investigating the energy-saving drying process of increased efficiency by condensation and developing relevant energy-saving drying equipment. increased efficiency by condensation energy-saving drying energy efficiency exergy efficiency improvement potential rate sustainability index The National Natural Science Foundation of China Youth Foundation32102034 Environmental Protection Research Project of the Ecological Environment Department of Jilin Province2019-02 This research was funded by The National Natural Science Foundation of China Youth Foundation (Grant No. 32102034) and Environmental Protection Research Project of the Ecological Environment Department of Jilin Province (2019-02). pmc1. Introduction Corn is a staple food crop in China, with this country ranking second globally in corn production and consumption . Drying the harvested corn in a timely manner significantly contributes to the process of corn storage and processing. Since drying is energy-intensive and highly polluting, clean and energy-saving drying to extend the shelf life of corn is an important research objective. Corn is primarily dried via continuous hot air drying, and a massive amount of heat is liberated by exhaust air emissions. Since coal-fired furnaces are the main drying heat sources, an enormous amount of polluting gases and fumes are emitted during this process . Therefore, recovering the exhaust air and employing a clean drying heat source can help conserve energy and reduce the emissions in the drying process. Exhaust air recovery or recycling is one of the main approaches to conserve energy and reduce emissions when operating dryers . A study suggested that when the winter temperature was -10 degC, the temperature required for recovering the exhaust gas emitted by a continuous flow grain dryer during corn drying was in the 34-40 degC range, representing a temperature rise of 44-50 degC, which corresponds to 500,000 kcal/h of heat or 100 kg/h of coal. By substituting the open hot air drying with a fully enclosed structure-based exhaust air recovery process, the recovery of vegetable matter and dust can reach 90%, and the energy consumption can be reduced by more than 3%. A pilot-scale wood drying test conducted using a convection dryer showed that exhaust air recycling could markedly improve the exergy efficiency of the dryer by more than two times. This indicates that exhaust air recovery in dryers can noticeably promote energy conservation and emission reduction. Furthermore, the exergy efficiency of a dryer with an exhaust air circulation system increases as the air circulation ratio increases . As China remains committed to pursuing clean, low-carbon, and green development and reaching the goals of peaking carbon dioxide emissions before 2030 and achieving carbon neutrality before 2060, energy efficient and eco-friendly farm machines will be vigorously developed. In a dryer, the dryer heat source is one of the main factors affecting energy conservation and emission reduction. Due to the rising demand for a clean dryer heat source, oil-, gas-, and biomass-fired hot-blast stoves and heat pumps have emerged. Studies in China and abroad have indicated that biomass-fired hot-blast stoves and heat pumps are the preferred heat sources for reducing pollution and the drying costs . The alcohol-based mixed fuel hot-blast stove and the electrothermal energy storage hot-blast stove are emerging as clean, low-carbon, energy-saving, and eco-friendly heat sources for grain dryers in China; however, they are still in the market development stage. Electricity, which can be generated from a clean energy source, possesses the inherent advantage of a low initial investment when employed as the heat source for grain dryers , however, it cannot be widely used due to its large power configuration. Increased efficiency drying by condensation, a new type of hot air drying, is a process in which the exhaust air is recovered, condensed, dehumidified, and recycled. More specifically, the drying medium flows in a closed loop in the drying system. This method possesses the prominent advantages of cleanliness, energy conservation, and intelligent control during the drying process . Its novelty lies in the utilization of both the residual heat of exhaust air and the latent heat of condensation through moderate condensation of recycled exhaust air and exergic analysis of the drying process directing the selection of drying process parameters, with the purpose of clean and energy-saving drying. Fixed-bed drying is traditionally employed to dry corn . In recent years, there were many studies on drying process simulations of corn fixed-bed drying based on the MSU (Michigan State University) model and partial differential equations drying model , and some effective drying simulation research methods were established. For the purpose of energy saving drying, based on the increased efficiency by condensation hot air drying combined with fixed-bed drying, a fixed-bed drying test device of increased efficiency by condensation was designed to investigate and optimise the fixed-bed drying process of increased efficiency by condensation. Here, we compared conventional open hot air drying and increased efficiency drying by condensation using corn drying test under the same drying conditions, using the response surface method test and the corn drying test of increased efficiency by condensation under different drying conditions to verify the energy-saving advantage of the novel drying method, and the influence of drying process parameters on the drying characteristics and exergy characteristics of the corn drying process. 2. Materials and Methods 2.1. Materials and Test and Analytical Methods The corn used for the test was Ketai 881 corn freshly harvested from Quanyan Town, Erdao District, Changchun, Jilin, China. The corn was harvested and threshed in the field, washed to remove the impurities, and placed in sealed bags, followed by freezing in a freezer and stored at -15 degC. During the test, an appropriate amount of the sample was removed and placed in an environment at 23 degC for approximately 1 h to remove the frost on the surface. Then, an additional 500 g of sample was weighed with a high precision electronic scale of the Yingheng brand to conduct the drying test. The sample weight before and after the test was measured by the electronic scale and moisture was measured using a PM-8188 grain moisture meter produced by KETT Japan. In the drying process, the total weight method was used to detect corn moisture in real time . The test data of the comparative test with or without exhaust air circulation and the single factor test were statistically analysed using Excel 2013, and the response surface method test data were statistically analysed using Design-Expert v8.0.6.1. The comparative test with or without exhaust air circulation was performed with an air velocity across the grain layer of 0.4 m/s, condensation ratio of 0.8, and hot air temperature of 30, 35, 40, 45, 50, and 55 degC. The single factor experiment was performed at six temperatures (30, 35, 40, 45, 50, and 55 degC), five air velocities across the grain layer levels (0.2, 0.3, 0.4, 0.5, and 0.6 m/s), and five condensation ratios (0.4, 0.6, 0.8, 1.0, and 1.2). The single factor air temperature test data were the same as the comparative test data with or without exhaust air circulation. In the single factor air velocity test, the air temperature was 40 degC and condensation ratio was 0.8. In the single factor condensation ratio test, the air temperature was 40 degC and the air velocity across the grain layer was 0.3 m/s. A rotary combination design was used for response surface test. 2.2. Test Device The fixed-bed drying test device of increased efficiency by condensation was designed based on the principle of energy-saving drying of increased efficiency by condensation . The drying medium is heated by the electric heater and sent to the drying chamber by the fan, where it exchanges moisture and heat with drying materials in the drying chamber; the drying medium that has absorbed the water from the grain enters the water cooling condensers for moderate condensation and dehumidification, and then enters the electric heater for supplementary heating to the required hot air temperature before proceeding to the next drying cycle. The drying medium flows in a closed loop inside the device. Figure 1 shows the fixed-bed drying test device of increased efficiency by condensation, which primarily consists of the test chamber, an electronic balance, a holder, and a water tank. Figure 2 shows the internal working components of the test device consisting of a drying chamber, a water-cooled condenser, an electric heater, a fan, detection sensors , and a control host, which are located inside the outer case. The inner wall of the outer case is insulated with 1 cm thick rubber plastic insulation cotton. The wet grains to be dried are dried in the drying chamber. The moisture in the grains evaporates and is exposed to the drying medium which is then discharged from the drying chamber in the form of humid exhaust gas. The humid exhaust gas is condensed and dehumidified when flowing through the condenser, and then flows in a closed loop in the system with the aid of the power provided by the fan. The heat source is an electric heater, which provides heat in a clean and eco-friendly manner. We can adjust the air velocity of the fan by controlling the main voltage, and the fan has a pulse speed measurement function. The detection sensors include the hot air temperature sensors, the water temperature sensors at the condenser inlet and outlet, and the temperature and humidity sensors before and after the condensation of the exhaust gas. The control host controls the "on" and "off" function of all system components, performs real-time monitoring, and stores the data. The control system, which was developed by LabVIEW, enables the window display of the control interface and the drying process parameter settings, as well as the display of the real-time interface. The models and parameters of the main components of the test device are shown in Table 1. 2.3. Test Principle The energy consumption of the drying process, which is evaluated based on the specific heat consumption (SHC), is the main index to evaluate the energy saving of drying device and process. The SHC (measured in kJ/kg) is the amount of heat consumed per kilogram of water evaporated from the materials in the drying process . Since the heat source of the test device is an electric heater, all the heat consumed for drying is provided by electricity, and the SHC computational equation is the following:(1) SHC=3600WsrWs where Wsr and Ws are the electricity input consumed during electric heating (kWh) and the water loss (kg) observed during the drying process over the same time period, respectively. The drying rate (m), which is used to evaluate whether the drying is performed rapidly or slowly, is expressed by the variations in the moisture content (wet basis) of the materials per unit of time, and is calculated using the following equation :(2) m=M1-M2t where M1 and M2 are the moisture contents (%, wet basis) of the materials before and after drying, respectively, and t is the drying time (h). Exergy is the amount of work a gas, liquid, or substance can perform when it is in a state that is not in equilibrium with a reference state , and is the unity of energy, environment, and sustainability. As the exergy efficiency increases in a process, the associated environmental effect decreases, whereas the sustainability increases . The exergy efficiency in the drying process is the ratio of the exergy used to dry materials to the exergy of the drying medium in the inlet of drying chamber, and is calculated using the following equation :(3) ps=E kheE kha1 where E khe is the exergy rate for the water evaporating from the grain, which was calculated as follows :(4) E khe=1-t0tgQ e where tg is the grain temperature and t0 is the reference state temperature of the exergy analyses. The exergy reference state of the corn drying system in this study was considered as the condition of the drying chamber inside the case. Q e is the heat required for the evaporation of grain water, which belongs to the useful energy of the system and was calculated as follows :(5) Q e=n*2500+1.842ta2-Cwthg1 where n is a constant and it denotes water removal per unit time during the drying process, ta2 is the exhaust gas temperature, Cw is the specific heat by weight at a constant pressure of water, and thg1 is the temperature of the corn before drying. E kha is the exergy rate of the drying medium, and the subscript 1 and 2 refer to the state of the drying medium input to the drying chamber and exhaust gas discharged from it, respectively, which was calculated as follows :(6) E kha=m aCa+phCvt-t0-t0Ca+phCvlntt0-Ra+phRvlnPP0+t0Ra+phRvln1+1.6078ph01+1.6078ph+1.6078phRalnphph0 where m a is the mass flow rate of the drying medium during the experimental process; Ca and Cv are the specific heat of air and the mean specific heat of vapour, respectively; Ra and Rv are the gas constant and vapour gas constant equal to 0.287 kJ/kg*K and 0.462 kJ/kg*K, respectively; and t, P, and ph are the temperature, pressure, and humidity ratios of the drying medium, respectively. The exergetic improvement potential rate and sustainability index are two useful parameters for analysing the exergy of a process. When the internal exergy loss in a system is reduced, the exergetic improvement potential is high; when the sustainability index in a process is high, the environmental effect is low . The improvement potential rate and sustainability index are calculated using the following equations. The improvement potential rate in the drying process is expressed as :(7) IP =1-psE khin-E khout (8) E khin=E khg1+E kha1 (9) E khout=E khg2+E kha2 where E khin and E khout are the exergy rate of the input and output drying chamber, respectively, and E khg is the exergy rate of the grain, and the subscript 1 and 2 refer to the state of grain before and after drying, which was calculated as follows :(10) E khg=m gCgt-t0-t0lntt0 where m g and Cg are the mass flow rate and the specific heat of the dried grain during the experimental process, respectively. The sustainability index in the drying process is expressed as :(11) SI=11-ps 2.4. Test Uncertainty Analysis The reproducibility and validity of the data obtained during the corn drying test were verified by uncertainty analysis. The uncertainty or error of the temperature sensors and the temperature and humidity sensors mainly arises from the measurement accuracy of the sensor itself and the effect of the higher humidity where sensors were installed on its performance. The uncertainty of the load cell was affected by the air flow ambient environment. To check the accuracy of the thermocouple, grain moisture meter, and load cell, twenty repetitions of the test were performed. Temperature and humidity data of the exhaust air, corn temperature data, corn moisture data, and machine and grain weight data were collected over a time period. The mean value and standard deviation of all observed data were obtained. The variable Xi is uncertain and can be expressed as follows :(12) Xi=Xmean+-dXi where Xi is the actual value of the variable, Xmean is the mean of the measurements, and dXi is the uncertainty in the measurement. The percentage of uncertainty is express as follows:(13) %Uncertainty=dXiXmeanx100 The percent uncertainties of all instruments were calculated and are shown in Table 2. The percent uncertainty was in the range of 4.8%. According to Yamamura et al., for the reproducibility of an experiment, uncertainty values below 5% are considered acceptable . 3. Results and Discussion 3.1. Comparison between Drying of Increased efficiency by condensation and Conventional Hot Air Drying Hot air drying is commonly employed to dry grains, and hot air dryers occupy a market share of approximately 99%, having a thermal efficiency of approximately 70%. Plenty of heat is consumed during exhaust air emissions, and dehumidification plays a pivotal role in exhaust air recycling. Here, the water-cooled condenser of the device employed the waste heat of the exhaust air and the latent heat of condensation to condense and dehumidify the exhaust air discharged from the drying chamber for recycling, resulting in remarkable energy-saving effects. The drying characteristics during increased condensation efficiency drying and conventional hot air drying are compared in Figure 4. When drying was performed at 30-55 degC, the SHC during the drying of increased efficiency by condensation was lower than that during a conventional open hot air drying process in the same temperature range. Specifically, the former was 0.68-0.44 of the latter, that is to say increased condensation efficiency drying resulted in an energy savings of 32-56% compared with the conventional open hot air drying; the energy-saving effect increased with increasing drying temperature. In Figure 4a, the SHC ratio refers to the ratio of the SHC between the drying of increased efficiency by condensation and conventional open hot air drying. Moreover, it can be seen from the trend line in Figure 4b that the mean drying rate during the drying process of increased efficiency by condensation was greater than that of conventional open hot air drying. This is mainly subject to the humidity and enthalpy of the drying medium, and the enthalpy of drying medium can be calculated by temperature and humidity parameters . As the exhaust air is recovered during increased condensation efficiency drying, the moisture absorbed by the drying medium from the grains is not fully condensed in the condensation process. In other words, the moisture content and enthalpy of the drying medium during the drying of increased efficiency by condensation are higher than those during conventional open hot air drying at the same temperature. Therefore, although the drying medium of the drying process of increased efficiency by condensation has a high moisture content and is less capable of absorbing moisture than that of a conventional open hot air drying process under specific temperature conditions, it rapidly exchanges heat with the grains because of its high enthalpy, promoting moisture evaporation. This indicates that the high enthalpy of the drying medium is favourable to drying within a specific humidity range. It can be seen that exhaust air recycling can improve energy efficiency and reduce energy consumption, which is the same as the conclusion that exhaust air recycling can improve the exergy efficiency of the system concluded by Amantea et al. . It is also consistent with the research conclusions of Chen et al. who showed that corn dried at gradually increasing air temperature and humidity can obtain an optimal comprehensive drying goal, which includes energy savings and corn quality indices . This is also the novelty of this experiment study. 3.2. Single Factor Experiment of Increased efficiency by condensation 3.2.1. Effects of Hot Air Temperature on the Drying Characteristics As the drying medium temperature in the inlet of drying chamber rose, the drying rate increased, whereas the SHC decreased, as shown in Figure 5. This is because when the air velocity, condensation ratio, and water temperature of the cooling medium are identical, the exhaust air temperature and dew point increase as the air temperature of the drying medium increases, and the condensation conditions can be reached, which means that condensation can occur earlier in the condensation process. This way, the relative humidity of the recovered exhaust air decreases earlier and remains at a low level. As a result, the drying medium is highly capable of absorbing moisture, resulting in a higher drying rate and a lower energy consumption. This is inconsistent with Ononogbo et al.'s research results from corn drying in a hot air dryer in the range of 50-60 degC, where the specific energy consumption increased with increasing air temperature . This is also inconsistent with Zhang et al.'s simulation analyses of energy consumption in hot air drying of corn kernels in which energy consumption increased with increasing air temperature . It is because the exhaust air recycling is used in this test device to make the drying system more energy-saving. 3.2.2. Effects of the Air Velocity on the Drying Characteristics With the increase of the air velocity passed through the grain layer measured by the testo 512-1 differential pressure meter above the grain layer in the drying chamber, the SHC increased, whereas the drying rate first increased and then decreased and remained unchanged as the air velocity increased after a stable value was reached, as shown in Figure 6. This is due to the fact that the amount of air passing through the grain layer increased with an increasing air velocity; thus, the heat consumption required for reaching the pre-set air temperature was higher; the SHC of the drying process increased because the moisture absorbed from the grains did not change significantly. Furthermore, when the condensation ratio is constant, the cold fluid water flow, the amount of exchanged heat between the hot and cold fluids, and the heat loss increase with increasing air velocity. An air velocity value that is too high will cause heat waste; therefore, the air velocity value of the drying process should meet the drying needs. The influence of air velocity on specific heat consumption in the drying process is consistent with the research conclusions of Ononogbo et al. and Zhang et al. who showed that energy consumption increased with an increase in air velocity . 3.2.3. Effects of the Condensation Ratio on the Drying Characteristics In the case of a low SHC and a high drying rate, an optimal condensation ratio was observed. Here, the condensation ratio is defined as the mass flow ratio between cold and hot fluids in the condenser. Under the test conditions, the SHC was the lowest and the drying rate was the highest when the condensation ratio was 1.0, as shown in Figure 7. Briefly, an optimal condensation ratio should be determined under specific operating conditions so that the exhaust air is condensed at an appropriate humidity to facilitate the drying process, and so that it is not excessively condensed to the point where it leads to an unnecessary energy waste. The process of controlling the humidity of the drying medium through the condensation ratio must meet the requirements of the drying index. 3.3. Rotation Combination Experiment Based on Response Surface Methodology Grain drying is a non-linear, multi-coupled, and complex heat and mass transfer process, and the relationship between the drying process parameters and the drying characteristics is non-linear. Here, an orthogonal polynomial regression based on the SHC and drying rate values during the drying of increased efficiency by condensation was performed using response surface methodology, and the following regression equations were obtained:(14) Y1=3456.11994+126.66476X1+30161.23338X2-429.59375X1X3 (15) Y2=1.49889+0.072053X1+3.35118X2-6.17892X3-0.13750X1X2+0.13125X1X3 where Y1 and Y2 are the SHC and drying rate, respectively, and X1, X2, and X3 are the hot air temperature, air velocity, and condensation ratio, respectively. ANOVA of the SHC and drying rate are shown in Table 3 and Table 4, respectively. According to the above regression equations, the SHC in the drying process of increased efficiency by condensation is mainly dependent on the hot air temperature, air velocity, and the interaction between the hot air temperature and the condensation ratio, and the drying rate is primarily dependent on the hot air temperature, air velocity, condensation ratio, the interaction between the air temperature and air velocity, and the interaction between the air temperature and condensation ratio. 3.4. Study of the Exergy Characteristics of the Drying Process 3.4.1. Effect of Drying Medium Temperature on the Mean Energy and Exergy Efficiencies of the Drying Process As shown in Figure 8, in the test temperature range, the mean energy and exergy efficiencies of the drying process were within the 31.65-51.26% and 41.69-63.52% ranges, respectively, and the mean exergy efficiency was greater than the mean energy efficiency. The mean energy and exergy efficiencies increased as the hot air temperature increased. This is mainly because the energy consumption required to evaporate 1 kg of water from the grains does not change significantly as the hot air temperature increases; however, the energy consumed in the drying chamber inlet increases as the hot air temperature increases. The change law of mean exergy efficiency with hot air temperature is consistent with the research conclusions of Khanali's study on the plug flow fluidised bed drying process of rough rice and Mondal's study on mixed flow drying of maize, in which exergy efficiency increased with an increase in drying air temperature . However, our results are in contrast to Zohrabi's study on convective drying of wood chips with exhaust air recirculation and Afzali's study on infrared hot air drying of mushroom slices with air recycling system . Thus, the change law of exergy efficiency with hot air temperature is related to drying mode. 3.4.2. Effect of Air Velocity on the Mean Energy and Exergy Efficiencies of the Drying Process As shown in Figure 9, when air passes through the grain layer at 0.2-0.6 m/s, the mean energy and exergy efficiencies of the drying process of the increased efficiency by condensation of corn are in the 24.96-65.28% and 30.40-84.90% ranges, respectively, and both decreased with an increasing air velocity. This is primarily because the energy required to heat the drying medium increases with an increase in air velocity, since the thermal energy required to evaporate 1 kg of moisture from corn is essentially constant, the energy and exergy efficiencies of the drying process decrease with an increase in air velocity. Furthermore, an increase in air velocity leads to accelerated heat exchanges between the air duct and the inside of the box, between the inside and the wall of the box, and between the box and the external environment, leading to the dissipation of a higher amount of heat from the system and, as a result, the energy and exergy efficiencies decrease. This is the same as Tohidi et al.'s research results that energy efficiency increased with decreasing flow rate of the drying air . 3.4.3. Effects of the Drying Medium Temperature on the Improvement Potential Rate and Sustainability Index of the Drying Process When the drying temperature was below 55 degC, the improvement potential rate decreased in the early drying process and, subsequently, tended to flatten out, as shown in Figure 10. This is mainly because the early drying process corresponds to the pre-heating stage of the drying system, and the exergy efficiency of the drying medium increases with an increasing in drying medium temperature. As the exergy efficiency of the grain drying system showed marginal changes with the changes in grain temperature, the exergy efficiency decreased in the early drying process. Moreover, since marginal changes in the differences between the initial and final grain temperatures and between the drying medium temperature and the exhaust air temperature occurred, the improvement potential rate of the drying process decreased. When the drying temperature was 55 degC, the improvement potential rate of the drying process gradually increased during the drying process. In the range of 30-55 degC, the improvement potential rate of the drying process had no obvious correlation with the change in drying air temperature. This is inconsistent with Khanali et al.'s study on the drying process of rough rice in a plug flow fluidised bed and Mondal's study on mixed flow drying of maize, in which the improvement potential rate of the drying process increased with the increase in drying air temperature , which was mainly due to the effect of the condensation process on the drying process. As shown in Figure 11, in the drying temperature range of 30-55 degC, the sustainability index of the drying process of increased efficiency by condensation fluctuated in the 1.56-3.10 range and showed no obvious pattern of change as the hot air temperature increased. This reveals that when drying is performed at 30-55 degC, the drying system does not exchange much energy with the external environment, and the heat dissipated by the system to the environment is maintained at a constant level and the sustainability index is marginally affected by the drying air temperature. This is inconsistent with Khanali et al.'s study about the drying process of rough rice in a plug flow fluidised bed and Mondal's study on mixed-flow drying of maize, in which the sustainability index of the drying process increased with the increase in drying air temperature , which was mainly because the exhaust air of the test device is recycled and the drying medium flows in the closed loop of the system. 3.4.4. Effects of the Drying Medium Flow Rate on the Improvement Potential Rate and Sustainability Index of the Drying Process The corn drying process and the condensation process of the drying medium influenced each other in the early drying process. As shown in Figure 12, as the drying process proceeded, the improvement potential rate showed no marked changes. When the drying was performed for nearly 1 h, the drying and condensation processes remained relatively stable, and the improvement potential rate of the drying process decreased as the drying process proceeded. In other words, the improvement potential rate determines when the system enters the equilibrium state of drying and condensation, representing the characteristic parameter of the system in the equilibrium state. When air passed through the grain layer at 0.2-0.6 m/s, the improvement potential rate of the fixed-bed drying process of increased efficiency by condensation of corn was in the 0.24-15.33 J/s range, and it increased as the air velocity increased. This is consistent with Beigi's research on deep bed drying of rough rice in a convective dryer in which the improvement potential rate increased with the increase in flow rate . When air passed through the grain layer at 0.4-0.6 m/s, the range of the sustainability index of the drying process was relatively narrow (1.3-1.9) and marginally fluctuated with an increase in drying time, as shown in Figure 13. When air passed through the grain layer at 0.3 m/s, the sustainability index of the drying process was within the 2.5-3.2 range. When air passed through the grain layer at 0.2 m/s, the sustainability index first decreased and then increased, and fluctuated in the 4.2-10.0 range during the drying process. Generally, as the air velocity increased, the sustainability index of the drying process decreased, and the effects of the drying process on the environment increased. This is consistent with Beigi's research on deep bed drying of rough rice in a convective dryer in which the sustainability index decreased with the increase in flow rate . 4. Conclusions In this study, we conducted a fixed-bed drying test of increased efficiency by condensation on corn to study the drying characteristics of this drying method and analyse the energy saving advantage and exergy characteristics of the drying process. The following conclusions were obtained:(1) In the range of 30-55 degC, the SHC of corn drying using the drying of increased efficiency by condensation was 0.68-0.44 of that observed during conventional open hot air drying. Therefore, drying of increased efficiency by condensation resulted in an energy savings of 32-56% compared to conventional open hot air drying. Additionally, the energy-saving effects increased as the drying temperature increased, and the drying rate during increased efficiency drying by condensation was higher than that during conventional open hot air drying. (2) When corn drying of increased efficiency by condensation was performed at 30-55 degC, the drying rate increased and the SHC decreased as the drying medium temperature increased. When air passed through the grain layer at 0.2-0.6 m/s, the SHC increased and the drying rate first increased, and then decreased before reaching a stable value as the air velocity increased. (3) On corn drying of increased efficiency by condensation on a fixed-bed, when the drying air temperature was within the 30-55 degC range, the mean energy and exergy efficiencies were within the 31.65-51.26% and 41.69-63.52% ranges, respectively, and both increased with an increase in hot air temperature. When air passed through the grain layer at 0.2-0.6 m/s, they were within the 24.96-65.28% and 30.40-84.90% ranges, respectively, and both decreased with an increase in air velocity. (4) The improvement potential rate and sustainability index of the drying process showed no obvious correlation with increasing drying air temperature, and the former increased and the latter decreased with increasing air velocity. In future studies, the corn drying of increased efficiency by condensation should be performed at higher temperatures, and the drying characteristics and exergy characteristics should be analysed for the development of energy-saving drying processes, models, and control systems. 5. Patents The measurement and control system V1.0 of the grain hot air drying and condensation enhancement experiment bench is based on the Labview platform; Chinese patent: 2022SR1534482. Condensation heating grain drying basic test device, Chinese patent: 212030056U, 2019. Acknowledgments The authors acknowledge the technical support provided by the National Engineering Laboratory for Grain Storage and Transportation, College of Biological and Agricultural Engineering, Jilin University. The authors thank the College of Engineering and Technology, Jilin Agricultural University, for providing the testing platform support for this study. The authors thank the College of Material science and Engineering, Jilin University and Jilin Business and Technology College for providing the staff help and support. Author Contributions Conceptualization, methodology, writing--original draft preparation, D.F.; validation, writing--review and editing, W.W.; formal analysis, investigation, resources, G.W.; data curation, H.X.; software, visualization, F.H.; supervision, project administration, funding acquisition, Z.L. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The datasets generated for this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Fixed-bed drying test device of increased efficiency by condensation. Figure 2 Internal structure diagram of test system. (a) Main section view and (b) top view. 1. Drying outer cylinder, 2. Drying inner cylinder support plate, 3. Drying outer cylinder lower duct, 4. Drying inner cylinder, 5. Drying inner cylinder bottom screen plate, 6. Upper duct, 7. Condenser, 8. Condenser upper cover, 9. Water cooler, 10. Condenser outlet duct, 11. Condenser inlet duct, 12. Heating duct, 13. Fan outlet duct, 14. Fan, 15. Fan inlet duct 16. Drying outer cylinder interface, 17. Drying outer cylinder bottom cover. Figure 3 Sensor layout of test system. TF1: Hot air temperature; TJ1, TJ2: Condensing medium inlet and outlet temperature; TH1, TH2: Drying medium before and after condensation temperature and humidity; TH3: Drying chamber temperature and humidity. Figure 4 (a) Specific heat consumption (SHC) ratio and (b) drying rate of the two drying methods. Figure 5 Effects of the hot air temperature on the (a) specific heat consumption (SHC) and (b) drying rate. Figure 6 Effects of the air velocity on the (a) specific heat consumption (SHC) and (b) drying rate. Figure 7 Effects of the condensation ratio on the (a) specific heat consumption (SHC) and (b) drying rate. Figure 8 Changes in the mean energy (exergy) efficiency of the drying process with hot air temperature. Figure 9 Changes in the mean energy (exergy) efficiency of the drying process with air velocity. Figure 10 Changes in the improvement potential rate of the drying process at different hot air temperatures. Figure 11 Changes in the sustainability index of the drying process at different hot air temperatures. Figure 12 Changes in the improvement potential rate of the drying process at different air velocities. Figure 13 Changes in the sustainability index of the drying process at different air velocities. foods-12-01027-t001_Table 1 Table 1 Models and parameters of the main components. Name Model Parameters Specification Control of the host PPC-DL104D 10.4-inch industrial all-in-one machine Aluminium water cooler 40 x 240 mm Thickness 12 mm Fan BFB1012H Air flow 0.712 m3/min, air pressure 249.082 Pa, motor speed 3600 rpm Electric heating wire 24 v 25 W Total power 100 W Temperature sensor PT100 Range -100-280 degC, precision 0.1 degC Temperature and humidity sensor HC2A-S Humidity range 0~100% RH, temperature range -50~100 degC, precision +- 0.8% RH/0.01 degC Power meter DDSU666 0.001 kWh foods-12-01027-t002_Table 2 Table 2 List of measuring instruments with their specification, accuracies, and uncertainties of the measured quantities. Name of Instrument Model Accuracy Standard Deviation Uncertainty (%) Temperature and humidity transmitter HC2A-S +-0.005 degC +-0.8%RH 0.89 1.67 2.32 4.80 Temperature and humidity transmitter TH10S-B-H +-0.2 degC +-2%RH 0.39 1.41 2.96 4.61 Temperature probe PT100 +-0.005 0.28 0.69 Electronic platform scale -- +-0.5 g 16.61 0.06 Grain moisture meter PM-8188-A +-0.5% 0.18 1.31 foods-12-01027-t003_Table 3 Table 3 ANOVA of the model specific heat consumption. Source Sum of Squares (107) d f Mean Square (107) F Value p Value Significance Model 23.47 6 3.912 6.42 0.0025 Significant X1 8.551 1 8.551 14.02 0.0025 X2 10.37 1 10.37 17.01 0.0012 X3 0.735 1 0.735 1.21 0.2922 X1 X2 0.01412 1 0.01412 0.023 0.8814 X1 X3 2.362 1 2.362 3.87 0.0707 X2 X3 1.435 1 1.435 2.35 0.149 Residual 7.927 13 0.6098 Lack of Fit 4.063 8 0.5079 0.66 0.7156 Not significant Pure Error 3.864 5 0.7727 COR total 31.4 19 foods-12-01027-t004_Table 4 Table 4 ANOVA of the model drying rate. 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PMC10000524 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050928 diagnostics-13-00928 Article Diagnostics Using the Change-of-Direction and Acceleration Test (CODAT) of the Biomechanical Patterns Associated with Knee Injury in Female Futsal Players: A Cross-Sectional Analytical Study Ferrandez-Laliena Loreto 1 Vicente-Pina Lucia 1 Sanchez-Rodriguez Rocio 1 Orantes-Gonzalez Eva 2 Heredia-Jimenez Jose 3 Lucha-Lopez Maria Orosia 1* Hidalgo-Garcia Cesar 1* Tricas-Moreno Jose Miguel 1 Strzelecki Michal Academic Editor Obuchowicz Rafal Academic Editor Urbanik Andrzej Academic Editor Piorkowski Adam Academic Editor 1 Unidad de Investigacion en Fisioterapia, Spin off Centro Clinico OMT-E Fisioterapia SLP, Universidad de Zaragoza, Domingo Miral s/n, 50009 Zaragoza, Spain 2 Department of Sports and Computer Science, Faculty of Physical Education and Sports, University of Pablo de Olavide, 41013 Sevilla, Spain 3 Department of Physical Education and Sports, Faculty of Education, Economy & Technology, University of Granada, 51001 Ceuta, Spain * Correspondence: [email protected] (M.O.L.-L.); [email protected] (C.H.-G.); Tel.: +34-626-480-131 (M.O.L.-L.) 01 3 2023 3 2023 13 5 92805 1 2023 17 2 2023 25 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The primary aim of this study was to identify kinematic differences at initial contact between female futsal players with and without previous knee injury, using a functional motor pattern test. The secondary aim was to determine kinematic differences between the dominant and non-dominant limb in the whole group, using the same test. A cross-sectional study was performed in 16 female futsal players allocated into two groups: eight females with a previous knee injury, i.e., affected by the valgus collapse mechanism without surgical intervention, and eight with no previous injury. The evaluation protocol included the change-of-direction and acceleration test (CODAT). One registration was made for each lower limb, i.e., the dominant (the preferred kicking limb) and non-dominant limb. A 3D motion capture system (Qualisys AB, Goteborg, Sweden) was used to analyze the kinematics. The Cohen's d effect sizes between the groups demonstrated a strong effect size towards more physiological positions in the non-injured group in the following kinematics in the dominant limb: hip adduction (Cohen's d = 0.82), hip internal rotation (Cohen's d = 0.88), and ipsilateral pelvis rotation (Cohen's d = 1.06). The t-test for the dominant and non-dominant limb in the whole group showed the following differences in knee valgus: dominant limb (9.02 +- 7.31 degrees) and non-dominant limb (1.27 +- 9.05 degrees) (p = 0.049). Conclusions: The players with no previous history of knee injury had a more physiological position for avoiding the valgus collapse mechanism in the hip adduction and internal rotation, and in the pelvis rotation in the dominant limb. All the players showed more knee valgus in the dominant limb, which is the limb at greater risk of injury. knee injury kinematics soccer sports anterior cruciate ligament prevention physiotherapy CODAT This research received no external funding. pmc1. Introduction Knee injury incidence is one of the most frequent in soccer, reaching values of 0.7 injuries per 1000 h of exposure . With respect to knee ligament injuries, the anterior cruciate ligament (ACL) is the most common injury, reaching an incidence of 0.45 per 1000 h of exposure, and is also the most common reason for players requiring medical leave of more than 120 days . Previous studies have reported that female soccer players have a risk of sustaining ACL injuries that is two or three times higher than the equivalent risk in males , and is usually caused by a non-contact mechanism , while in men the cause is a direct impact of external force . Non-contact mechanisms causing ACL injury are due to a failure in biomechanical patterns, which include a lack of control in proprioceptive and neuromuscular activation . Moreover, it is conditioned by non-modifiable risk factors, such as anatomical and hormonal factors . Prospective studies have found that most ACL injuries were caused during dynamic high-intensity stabilization situations such as landings and changes of direction or decelerations, activities that are very common in the defensive roles of pressing/tracking actions in sports . In addition, the pressing pattern is one of the most frequent, due to the unexpected stimulus of the opponent and the match context situations . A recent study by DiPaolo et al. showed a compilation of the main biomechanical risk factor thresholds from prospective video analysis studies, which explain the "perfect loading storm" that defines ACL injury mechanisms , valgus collapse being the main biomechanical risk factor related to ACL injury. Arundale et al. explained "valgus collapse" as the combination of hip adduction and internal rotation, and knee abduction. Valgus collapse causes a medial pivoting of the femur on the tibia plateau and compression on the lateral side of the knee. Therefore, an increase in medial yawing of the joint puts the ACL fibres at maximal tension . In addition, before the ACL injury appears, on average 48 milliseconds after the initial contact, other kinematics faults have been observed . During change-of-direction tasks, at the initial contact phase, the female players who sustained ACL injury showed less trunk, hip, and knee flexion . Consequently, this could be related to higher vertical ground reaction forces during impact stabilization. An extended position avoids the load damping of limb joints, which causes an increase in anterior tibial shear forces, potentially resulting in higher strain in the ACL . Zebis et al. indicated a risk reduction of 44% per each increase in 10deg of hip flexion at this phase . In addition, studies have considered greater hip and knee rotation movement during change-of-direction tasks as risks of ACL injury . Research shows that knee internal rotation at initial contact is significantly related with ACL injury risk, with a 13% increased risk per 1deg increase in knee internal rotation. Knee internal rotation was related to higher hip internal rotation during a change-of-direction task, which was considered as a risky movement in terms of non-contact mechanisms causing ACL injury . Internal hip rotation promotes a displacement of the ground reaction force vector, which is focused medial and posterior on the tibial plateau during the impact. Increased ACL load is caused by the resultant relative anterior and lateral shear of the tibia . Latest research has studied the incidence ratio based on limb dominance, related to the fact that in futsal the ball determinates the biomechanical pattern . Studies explain that the dominant limb (DL) usually has a higher injury incidence ratio than the non-dominant limb (NDL) . During kicking, each limb plays a different role: the DL usually impacts the ball, while the NDL performs a stabilization function to provide a foundation for the kicking task . These different activity profiles influence the load on each limb during kicking, a task that takes place many times during each training session or match . This imbalance in loading between the two limbs influences the kinematic response of the limbs to the rest of the tasks in the match, especially in tasks such as changes of direction. Changes of directions have been identified as task related to a high risk of ACL injury. Most previous studies have analysed the implications of the biomechanical risks factors between two groups, injured and non-injured players , the former category including injured players who have suffered an ACL injury. Thus, in this group, surgery could have modified the biomechanical patterns. Currently no studies have used as a sample injured players who have already suffered a knee injury based on the valgus collapse mechanism, causing damage to the ACL or another joint structure with the same injury mechanism, which has been treated without surgical intervention. We hypothesized that female futsal players with previous knee injury based on the valgus collapse mechanism, without surgical intervention, had kinematic patterns similar to those identified as risk patterns for ACL injury, in a change-of-direction task. Therefore, this study aimed to identify kinematic differences at initial contact between female futsal players with and without previous knee injury, in a motor pattern test including change of direction, stabilization, and acceleration. A secondary aim was to determine the kinematic differences between the DL and NDL for the whole group, in the same tasks. 2. Materials and Methods 2.1. Study Design This study has a cross-sectional design. The allocation ratio was [1:1] between two groups. Allocation depended on clinical history: previous knee injury (KI) involving the valgus collapse mechanism without surgical intervention (injury group), or no injury (control group). The Research Ethics Committee of Community of Aragon approved this study (code PI20/127), which observed the ethical principles of the Declaration of Helsinki (64th WMA General Assembly, Fortaleza, Brazil, October 2013) . 2.2. Sample Size The sample size was calculated based on the outcomes of previous studies . The main variable used for sample size calculation was dynamic knee valgus at the first contact. The sample size was calculated with the GRANMO 7.12 calculator (Institut Municipal d'Investigacio Medica, Barcelona, Spain) accessed on 1 November 2021), with an alpha risk of 0.05, a beta risk of 0.20, and the two-side test. We used a common standard deviation of 5.1 degrees and a minimum expected difference of 8.4 degrees , estimating a follow-up loss of 20%. A total sample of 16 subjects (8 per group) was obtained. 2.3. Participants The president of the Real Federacion de Futbol de Ceuta was contacted regarding participation in the study. He contacted all the national female futsal players registered in the federation, of whom 16 volunteered to participate in the study. The average age was 23.4 + 5.03 years and the average height was 1.62 +- 0.06 m. They had an active national futsal licence, and they had attended futsal training for more than 4 h per week for at least 4 months. Players were excluded if they had had an injury incompatible with regular training in the past 4 months. All the players gave written informed consent prior to their participation in the study. 2.4. Procedure The first part of the evaluation was a survey to collect the individual clinical history of each participant. The data from the clinical history were used to allocate the subjects into the KI or control group. All players who had suffered a knee injury involving the valgus collapse non-contact mechanism, without surgical intervention, were included in the KI group . The recorded information included age, height, weight, knee injury history, lower limb dominance, injury mechanism, medical diagnosis, pain region, time to recovery, treatment received, possible relapse, and futsal level league at the time the injury occurred. Eight players were allocated to each group. The data collection was conducted in one session. Before the test procedure, a short mobility and warm-up activity was carried out. The evaluation protocol included the functional change-of-direction and acceleration test (CODAT) . This was conducted for each lower limb dominant (DL) and non-dominant (NDL). Limb dominance criteria was defined as the preferred kicking limb . A 3D motion capture system (Qualisys AB, Goteborg, Sweden) was used to analyze the kinematics of change of direction with a full body model marker set without head and upper extremities. Twenty-six reflective markers were placed with adhesive tape on the players' skin on both sides of the lower limbs and trunk. The palpation of the reflective markers was carried out following anatomical references. A force plate (Optima HPS464508-2000, AMTI, Watertown, MA, USA) was used to record the maximal torque of the ground reaction force during the initial contact phase. The 26 markers were placed to make a static picture. The locations were at the first and fifth metatarsal head, second metatarsophalangeal, medial and lateral malleolus, large posterior surface of calcaneus, lateral and medial femoral epicondyle, anterior and posterior superior iliac spine, acromioclavicular joints, inferior scapula angle, and thoracic spinous process of T3 and T12. In addition, a cluster with four markers was placed in the lateral of the shank and thigh of both limbs. Finally, another cluster with three markers was fixed to the lateral part of the pelvic girdle on both sides. After calibration in order for the computer to recognize precisely the situation of the cameras and all the markers to create a static record for the CODAT test performance, the malleolus, epicondyles, posterior superior iliac spine, and acromioclavicular joint markers were removed from the player to avoid interference with the maximal speed task. The set-up of the markers was in line with the recommendations of Codamotion system protocols (Charnwood Dynamics Ltd., Leicestershire, UK). The reflective marker locations were registered through 12 infrared high-speed cameras at a rate of 250 Hz. The calibration of the space was conducted with a wand (with a length of 751.1 mm) before each data collection and the standard deviations of the wand's length measurements were below 0.5 mm. Visual3D software (C-Motion Inc., Germantown, MD, USA) was used to analyze the change-of-direction task . Players carried out the CODAT test . This is a specific test that combines a sprint mechanism with the stabilization and acceleration needed for a change of direction. It involves placing a high load onto the knee in a similar way to tasks performed during training or a match . Moreover, most injuries involving non-contact mechanisms occur in defensive roles, so we performed the CODAT test without a ball to recreate the defensive role during the match . The CODAT test integrates a four-diagonal change-of-direction task, two of 45deg and the other two of 90deg, mixed with 3-m sprints and followed by a 10-m sprint. All the tests were performed at maximal speed. Prior research has observed that the average time of each sprint in soccer is 2 s and that the average distance is 10 m, which agrees with the maximal distance in the CODAT test . Moreover, a 3-m sprint allows for a complete gait cycle before the change-of-direction task. 2.5. Outcome Variables Since the risk of ACL injury is highest during the initial contact phase, only the moment of the maximal ground reaction torque forces at the initial contact phase in the 90deg change of direction was analysed . Mean and standard deviation (in degrees) of the flexion/extension, adduction/abduction and internal/external rotation of the trunk, pelvis, hip, and knee were computed for the DL and NDL. For the variables in the sagittal plane projection angle (x-axis), positive values (>0) refer to flexion, and negative values (<0) refer to extension. In the frontal plane projection angle (y-axis), positive values (>0) refer to trunk inclination towards the non-supporting limb side (contralateral), contralateral pelvic tilt, hip abduction, and knee varus; and negative values (<0) refer to the trunk inclination towards the supporting limb side (ipsilateral), ipsilateral pelvic tilt, hip adduction, and knee valgus. In the transversal plane projection angle (z-axis), positive values (>0) refer to the non-supporting limb side, contralateral trunk rotation, contralateral pelvis rotation, and hip and knee internal rotation; and negative values (<0) refer to ipsilateral trunk displacement, ipsilateral pelvis rotation, and hip and knee external rotation. 2.6. Data Analysis Data were analysed with SPSS software v.25 (SPSS Inc., Chicago, IL, USA). Normality was determined by the Kolmogorov-Smirnov test. To determine the differences in the kinematic angles between the KI and control groups, independent t-tests were used to compare the means. Furthermore, to determinate the differences in the kinematic angles between the DL and NDL, independent t-tests analysis was developed without distinguishing between players with and without injury. The level of statistical significance was set at p < 0.05. The effect size of the kinematic angles between the groups and limbs was determined using Cohen's d. The following values were used to distinguish the levels of the effect size: 1 to 0.8 (strong effect size); 0.8 to 0.5 (moderate effect size); and 0.5 to 0.0 (less or no effect size). 3. Results Eight players were allocated to each of the two groups, KI and control. The KI players had suffered a previous knee injury involving the valgus collapse mechanism, treated without surgical intervention, four of them in their DL and the rest in their NDL. The independent t-test revealed that there were no significant differences between the groups in any kinematic parameters. However, strong Cohen's d effect sizes, above 0.8, between the groups were found in the hip adduction, hip rotation, and pelvis rotation in the dominant limb (Table 1). The KI group had higher hip adduction than the control group (14.15 +- 4.64 degrees versus 10.69 +- 4.92 degrees in the control group) (Cohen's d = 0.82). The KI group presented a hip internal rotation of 1.26 +- 14.68 degrees, versus 11.55 +- 14.29 degrees of hip external rotation in the control group (Cohen's d = 0.88). The KI group showed a contralateral pelvis rotation of 6.11 +- 8.21 degrees, versus 1.35 +- 5.67 degrees of ipsilateral pelvis rotation in the control group (Cohen's d = 1.06) (Table 1). The analysis based on limb dominance taking both groups together was significant only for the knee valgus variable. Knee valgus was higher in the DL (9.02 +- 7.31 degrees versus 1.27 +- 9.05 degrees in the NDL) (p < 0.05), with a strong effect size (Cohen's d = 0.94) (Table 2). All the other variables showed similar values between the DL and NDL. 4. Discussion The main purpose of this study was to investigate kinematic differences at initial contact between female futsal players with and without previous knee injury, in a motor-pattern test including change of direction, stabilization, and acceleration. None of the variables showed significant differences between female futsal players with and without previous knee injury. However, a strong effect size between groups was obtained in some kinematics in the DL. With respect to the secondary aim of this study, to determine kinematic differences between the DL and NDL for the whole group, only knee valgus was significantly higher in the DL. Knee valgus was significantly higher in the DL (9.02 +- 7.31 degrees) than in the NDL (1.27 +- 9.05 degrees) (p = 0.049) in the whole group. As other studies have explained, the ACL usually breaks at an average of 13 degrees of knee valgus at initial contact and 22 degrees of knee valgus at the moment of injury, 48 milliseconds after the initial contact . In our findings, the KI and control players were near to these values at initial contact in the DL, without significant differences between them (KI: 10.58 +- 5.64 degrees; control group: 8.87 +- 8.45). However, in the NDL, the values were much lower (KI: 0.15 +- 10.99 degrees; control group: 2.87 +- 8.01). Knee valgus is one of most relevant risk factors in ACL non-contact injury mechanisms, and 88% to 100% of the knee injuries in female soccer are induced by non-contact mechanisms . As observed in the pivot shift test, during a valgus knee movement, the femur moves medially relative to the tibia, which causes the lateral condyle to slide into the medial side. These movements cause medial yawing of the knee that increases the ACL load. If the load on the ACL is too high, it might break and cause subluxation of the tibia, usually at around 30 degrees of knee flexion that reduces in deeper flexion . Recently, Di Paolo et al. and Collings et al. have verified that higher knee valgus values in different tasks were associated with future noncontact ACL injury in elite female soccer players. Our results showed a higher ACL injury risk position in the DL than in the NDL. DeLang et al. , in their meta-analysis, explain that soccer players are more likely to suffer injuries in their DL regardless of their playing level or gender. This is due to two main reasons. Firstly, there is neuromuscular fatigue in the DL as a result of the maximal effort involved in the kicking activity and the high-intensity stabilization actions. In futsal, the DL also accumulates more burden than the NDL. Futsal is a sport with changes of intensity and direction each 3.3 s on average. Therefore, 26% of the match is played at high intensity . This fact produces fatigue in both limbs, but the dominant one is also the kicking leg. Studies explain that players receive the ball twice a minute on average, and 84% of this is with the DL . In this way, the DL accumulates fatigue relative to the intensity of the game with additional fatigue due to the maximal effort of kicking. Secondly, there are intrinsic (capability, comfortability, or awareness) and extrinsic factors (opponent position or game situation) that make it necessary to use the DL as the stabilization limb, and it may not be used to these actions . Furthermore, most ACL injuries occur in defensive "pressing/tackling" or offensive duel "tackling" situations. These are high-speed actions and are driven by the match conditions, in which player does not have enough time to decide on the use of the DL or NDL. These forced actions are the most likely to result in injury. In contrast, both groups presented better knee valgus values in the NDL; this might be due to better neuromuscular control in this limb, since it is more used to the stabilization task. "Valgus collapse" has been defined as the combination of hip adduction, hip internal rotation, and knee abduction. In the current study, in the DL, the limb which had a level of knee valgus near to the injury risk threshold, the KI players had more hip adduction than the control players in the change-of-direction task (Cohen's d: 0.82). This was explained by the fact that when the KI players carried out a task that promoted high knee valgus values, their stabilization pattern was pathological, as explained by what is described in the literature as the "perfect storm" of ACL injury mechanism . These results agree with previous research, such as the study by Dix et al. , who verified that players who suffered ACL injury had a higher "valgus collapse", a combination of knee valgus, hip adduction, and internal hip rotation, during preseason testing, before ACL injury. The authors noted significant differences between injured and non-injured players only in the hip adduction variable. This study developed prospective data collection in national female soccer players, comparing initial kinematic values in a change-of-direction task of 90deg between groups. Therefore, the hypothesis of our KI group performing a kinematic pattern similar to the ACL injury pattern is confirmed. Hip and knee internal rotation are involved in knee valgus definition, as explained in video analysis research . In the current study, both groups had knee internal rotation at the evaluation moment, but the KI players had hip internal rotation in contrast to control players who developed hip external rotation (Cohen's d: 0.88). Hip internal rotation, combined with hip adduction and knee abduction, increases structural stress on the ACL due to its anatomical situation from the front internal tibial surface to the back external femur condyle . Therefore, if the hip internal rotation range of movement is increased, the strain fibres are at maximum stress and are broken easily. At the same time, increases in knee abduction and hip adduction cause medial displacement of the center of mass , and the joining of both conditions facilitates ACL risk injury. As is explained by Lucarno et al. in their systematic video analysis, 80% of the non-contact ACL injuries that occurred during matches in female players in six of the top leagues in the Federation International of Football Association (FIFA) Women's World Ranking were associated with hip internal rotation movement. Koga et al. show the same result in female players of other sports, such as basketball or handball. Our results showed that the KI players had a greater hip internal rotation range of motion than the control players, in agreement with previous research. Furthermore, hip internal rotation might be the result of weakness in the hip external rotation muscles., especially the gluteus maximus, which becomes weak due to accumulated fatigue. Fatigue could be the result of carrying out many functions at the same time. As strong external rotation is an important factor in avoiding knee valgus, we can say that it is a protective factor of ACL injury involving non-contact mechanisms. In fact, our control players showed hip external rotation in the DL during the change-of-direction task. All the players in our study, in both the KI and control groups, had a contralateral trunk rotation from the supporting limb. Many authors have demonstrated that if the contralateral trunk rotation increases, the knee valgus increases too, raising the risk of ACL injury . As Della Villa et al. shows in their research, 53% of the players with ACL injuries had contralateral trunk rotation at the moment of injury, especially during pressing and landing tasks. As Lloyd et al. explain in their "perfect storm" definition of ACL injury mechanisms, contralateral rotation causes a medial displacement of the center of mass, which increases the loading on the medial knee compartment. However, no prior authors have studied the influence of pelvic rotation. In our study, the KI players performed a contralateral pelvic rotation following the trunk motion direction. On the contrary, members the control group in whom contralateral trunk rotation existed realized an ipsilateral pelvic rotation to the DL (Cohen's d: 1.06). This might be a balance mechanism to counteract the opposite trunk rotation, and to decelerate the medial velocities suffered by the knee as a result of the trunk rotation movement . It would be interesting to develop studies to explore this hypothesis in the future. Limitations This study is limited by the relatively small sample size and by the cross-sectional design conducted in a single geographic location; thus, any causality can be referred to the relationship in the relevant results. Due to the study design, it was not possible to state whether the worst kinematic patterns observed in the KI group were present before the knee injury, making the injury more likely to occur, or whether they existed as a result of the disfunctions induced by the injury. A future larger cohort and prospective studies might support our findings and develop new analysis in pelvic kinematics. However, the current findings may be relevant for the development of specific preventive training in female soccer players. The preventive training should be based on intensive neuromuscular training to avoid fatigue of the muscles, especially of the DL, and in the reinforcement of the hip external rotation muscles. 5. Conclusions The current study found kinematic differences at initial contact between female futsal players with and without previous knee injury, in a motor pattern test. The players with no previous history of knee injury had a more physiological position to avoid the valgus collapse mechanism in hip adduction and internal rotation, and in the pelvis rotation, in the dominant limb. The players with previous injury had a kinematic pattern closer to those related to LCA injury, which might have existed before the injury, making it more likely to occur, or as a result of the disfunctions induced by the injury. All the players showed more knee valgus in their dominant limb, which is the limb with a greater risk of injury, revealing the clinical relevance of neuromuscular stabilization training for this limb. Acknowledgments The authors thank the volunteer subjects for their altruistic participation. Author Contributions Conceptualization, L.F.-L. and J.M.T.-M.; methodology, L.F.-L., L.V.-P. and R.S.-R.; formal analysis, L.F.-L. and M.O.L.-L.; investigation, L.F.-L., L.V.-P., E.O.-G. and J.H.-J.; data curation, E.O.-G. and J.H.-J.; writing--original draft preparation, L.F.-L., M.O.L.-L., E.O.-G. and C.H.-G.; writing--review and editing, L.F.-L., M.O.L.-L., E.O.-G. and C.H.-G.; visualization, L.F.-L., L.V.-P. and R.S.-R.; project administration, J.M.T.-M. and L.F.-L.; resources, E.O.-G. and J.H.-J.; supervision, J.M.T.-M. and J.H.-J. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Research Ethics Committee of Community of Aragon (protocol code PI20/127; date of approval: 18 March 2020). Informed Consent Statement Informed consent was obtained from all the subjects involved in the study. Written informed consent was obtained from the subject in Figure 1. Data Availability Statement The datasets presented in this study are available on request from the corresponding author. All data covered by this study are included in this manuscript. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Capture moment of kinematic data during CODAT test: (a) Capture moment from a 2D camera that shows the player's task; (b) Signal from 12 infrared high-speed cameras being processed with Visual3D software; (c) Final avatar processed by Virtual 3D software. Figure 2 CODAT test diagram. The initial point of the test is drawn with a green ball. The green square shows the location of the force plate. The red cross identifies the change-of-direction task that was recorded with the 3D motion capture system. diagnostics-13-00928-t001_Table 1 Table 1 Comparative analysis of the kinematic outcomes between KI and control groups in DL and NDL. Dominant Limb Non-Dominant Limb KI Control KI Control Mean +- SD Mean +- SD p-Value Cohen's d CI (95%) Mean +- SD Mean +- SD p-Value Cohen's d CI (95%) Knee Flexion (deg) (+flexion/-extension) 29.64 +- 9.74 29.60 +- 9.87 0.994 0.00 (-10.93-11.01) 26.54 +- 20.44 35.50 +- 12.21 0.314 0.53 (-27.44-9.52) Pelvis Flexion (deg) (+flexion/-extension) 10.30 +- 10.24 13.38 +- 12.71 0.618 0.27 (-16.09-9.93) 12.93 +- 17.19 13.44 +- 10.69 0.945 0.04 (-16.10-15.22) Trunk Flexion (deg) (+flexion/-extension) 11.66 +- 4.70 12.22 +- 13.42 0.934 0.06 (-15.07-13.93) 14.04 +- 18.84 11.41 +- 12.87 0.754 0.16 (-15.15-20.41) Knee Valgus (deg) (+varus/-valgus) -10.58 +- 5.64 -8.87 +- 8.45 0.657 0.24 (-15.79-(-5.36)) -0.15 +- 10.99 -2.87 +- 8.01 0.59 0.28 (-9.57-3.83) Hip Adduction (deg) (+abduction/-adduction) -14.15 +- 4.64 -10.69 +- 4.92 0.184 0.82 ** (-8.84-1.87) -14.02 +- 15.00 -15.82 +- 13.36 0.810 0.12 (-14.02-17.60) Pelvis tilt (deg) (+contralateral/-ipsilateral) -6.24 +- 9.31 -10.57 +- 8.02 0.350 0.50 (-14.85-2.36) -7.67 +- 8.82 -2.28 +- 15.77 0.439 0.42 (-15.47-10.90) Trunk displacement (deg) (+contralateral/-ipsilateral) -12.23 +- 8.97 -12.05 +- 14.30 0.977 0.01 (-20.53-(-3.94)) -14.18 +- 9.66 -8.27 +- 10.98 0.292 0.57 (-17.44-0.91) Knee rotation (deg) (+internal/-external) 6.36 +- 10.74 1.85 +- 9.30 0.399 0.45 (-3.57-16.29) 5.53 +- 8.20 4.99 +- 4.82 0.877 0.08 (-4.25-6.21) Hip rotation (deg) (+internal/-external) 1.26 +- 14.68 -11.55 +- 14.29 0.111 0.88 ** (-12.31-14.84) -8.97 +- 11.74 -1.17 +- 12.65 0.314 0.64 (-11.75-9.40) Pelvis rotation (deg) (+contralateral/-ipsilateral) 6.11 +- 8.21 -1.35 +- 5.67 0.059 1.06 ** (-13.70-1.48) 1.82 +- 14.01 8.52 +- 11.71 0.331 0.52 (-18.31-1.27) Trunk rotation (deg) (+contralateral/-ipsilateral) 3.22 +- 9.29 7.81 +- 12.90 0.450 0.41 (-11.81-5.38) 1.62 +- 9.96 5.89 +- 10.12 0.426 0.42 (-14.35-2.57) ** Effect size strong to excellent d > 0.8. diagnostics-13-00928-t002_Table 2 Table 2 Comparative analysis of the kinematic outcomes between the DL and the NDL in the whole group. DL NDL Mean +- SD Mean +- SD p-Value Cohen's d CI (95%) Knee Flexion (deg) (+flexion/-extension) 31.12 +- 10.93 32.62 +- 16.84 0.757 0.11 (-9.33-6.48) Hip Flexion (deg) (+flexion/-extension) 46.85 +- 37.07 41.98 +- 21.01 0.559 0.16 (-8.92-9.74) Pelvis Flexion (deg) (+flexion/-extension) 13.92 +- 13.50 15.35 +- 15.66 0.706 0.10 (-8.41-14.96) Trunk Flexion (deg) (+flexion/-extension) 10.66 +- 13.16 10.25 +- 17.67 0.926 0.03 (-11.61-8.62) Knee Valgus (deg) (+varus/-valgus) -9.02 +- 7.31 -1.27 +- 9.05 0.049 * 0.94 ** (-15.46-(-0.04)) Hip Adduction (deg) (+abduction/-adduction) -13.04 +- 5.64 -14.85 +- 13.20 0.624 0.18 (-5.90-9.52) Pelvis tilt (deg) (+contralateral/-ipsilateral) -9.23 +- 8.76 -5.62 +- 12.85 0.449 0.33 (-14.85-2.36) Trunk displacement (deg) (+contralateral/-ipsilateral) -12.47 +- 11.37 -11.35 +- 10.20 0.826 0.10 (-11.66-9.70) Knee rotation (deg) (+internal/-external) 4.36 +- 9.70 5.11 +- 6.17 0.809 0.09 (-3.57-16.29) Hip rotation (deg) (+internal/-external) -5.92 +- 14.98 -4.94 +- 12.05 0.847 0.07 (-11.66-9.70) Pelvis rotation (deg) (+contralateral/-ipsilateral) 2.08 +- 7.47 5.72 +- 12.47 0.391 0.35 (-5.15-12.43) Trunk rotation (deg) (+contralateral/-ipsilateral) 4.96 +- 11.20 2.99 +- 10.25 0.606 0.18 (-9.92-5.99) * Statistical significance p < 0.05/** Effect size strong to excellent d > 0.8. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Ruiz-Perez I. Lopez-Valenciano A. Jimenez-Loaisa A. Elvira J.L.L. de Ste Croix M. Ayala F. Injury incidence, characteristics and burden among female sub-elite futsal players: A prospective study with three-year follow-up PeerJ 2019 7 e7989 10.7717/peerj.7989 31720114 2. Olivares-Jabalera J. Filter-Ruger A. Dos'Santos T. Afonso J. della Villa F. Morente-Sanchez J. Soto-Hermoso V.M. Requena B. Exercise-Based Training Strategies to Reduce the Incidence or Mitigate the Risk Factors of Anterior Cruciate Ligament Injury in Adult Football (Soccer) Players: A Systematic Review Int. J. Environ. Res. 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PMC10000525 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050781 cells-12-00781 Editorial Advances in the Understanding of Frontotemporal Dementia Bandopadhyay Rina 1* Gatt Ariana 2 Lashley Tammaryn 2 1 Reta Lila Weston Institute of Neurological Studies, Department of Clinical and Movement Neuroscience, UCL Institute of Neurology, 1 Wakefield Street, London WC1N 1PJ, UK 2 Queen Square Brain Bank, Department of Neurodegenerative Diseases, UCL Institute of Neurology, 1 Wakefield Street, London WC1N 1PJ, UK * Correspondence: [email protected] 01 3 2023 3 2023 12 5 78122 2 2023 27 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). pmcFrontotemporal dementia (FTD) encompasses a group of clinically, genetically and pathologically heterogeneous neurodegenerative disorders that mainly affect people under the age of 64 years. However, around 25% of those affected have a later age of onset. FTD represents 10-20% of all dementia cases . It is predominantly characterized by the progressive atrophy of the frontal and temporal lobes . Disease duration ranges between 2 and 20 years, with 8 years being the mean following the onset of symptoms. FTD treatment is restricted to symptom control, and no disease-modifying treatments are available. The clinical hallmarks of FTD include gradual yet progressive deficits in behaviour and/or language with the relative preservation of memory. Subtypes of FTD are identified clinically according to the symptoms that appear prominently at presentation. Clinical diagnoses include behavioral variant FTD (bVFTD), which accounts for nearly 60% of cases; primary progressive aphasia (PPA), which affects language; and the movement disorders progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) . With disease progression, the debilitating symptoms cause marked impairments of social and/or occupational functioning. Early and accurate diagnosis is crucial for the streamlining and development of any disease-modifying treatment therapies. A third of FTD cases are genetically linked with mutations occurring in C9orf72, progranulin (GRN) and MAPT, with C9orf72 repeat expansions being the most common. Neuropathologically, TAR DNA binding protein-43 (TDP-43), fused in sarcoma (FUS) and tau are three major proteins that cause pathological deposits in FTD post-mortem brains . Those with C9orf72 expansions also have an additional pathology where di-peptide repeat proteins are also found deposited in patients. It is thought that disease pathogenesis is caused either by a gain of toxic function or a loss of nuclear function associated with protein dislocation from the nucleus, which in turn may lead to neuronal degeneration. FUS regulates the transcription of multiple genes, including the MAPT gene . Recent studies have highlighted the molecular pathways associated with lysosomal dysfunction, lipid dysregulation, RNA splicing aberrations, synaptic loss and neuroinflammation as putative causes of sporadic forms of FTD. The disease mechanisms are far from understood in FTD, especially the cellular changes occurring in the early disease stages. Continued research with improved animal models, iPS technologies, clinicopathological correlations with donated human brain tissue and the discovery of early biomarkers of disease progression should enable us to rationalize the mechanisms involved in these neurodegenerative diseases and identify much-needed therapeutic targets. This Special Issue will collect articles relating to all advances in FTD research, both clinical and non-clinical. Conflicts of Interest The authors declare no conflict of interest. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Olney N.T. Spina S. Miller B.I. Frontotemporal dementia Neurol. Clin. 2017 35 339 374 10.1016/j.ncl.2017.01.008 28410663 2. Lashley T. Rohrer J.D. Mead S. Revesz T. An update on clinical, genetic and pathological aspects of frontotemporal lobar degenerations Neuropathol. Appl. Neurobiol. 2015 41 858 881 10.1111/nan.12250 26041104 3. Ishigaki S. Fujioka Y. Okada Y. Riku Y. Udagawa T. Honda D. Yokoi S. Endo K. Ikenaka K. Takagi S. Altered trau isoforms ratio caused by Loss of FUS and SFPQ function leads to FTLD-like phenotypes Cell Rep. 2017 18 1118 1131 10.1016/j.celrep.2017.01.013 28147269 4. Sobue G. Ishigaki S. Watanabe H. Pathogenesis of frontotemporal lobar degeneration: Insights from loss of function theory and early involvement of the caudate nucleus Front. Neurosci. 2018 12 473 10.3389/fnins.2018.00473 30050404 |
PMC10000526 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051087 foods-12-01087 Article Frozen Ready-to-(h)eat Meals: Evolution of Their Quality during a Real-Time Short Shelf Life Dottori Ilenia Formal analysis Investigation Data curation Writing - original draft Writing - review & editing 1 Urbani Stefania Methodology Formal analysis Data curation 1 Sordini Beatrice Formal analysis Data curation 1 Servili Maurizio Visualization Project administration Funding acquisition 1* Selvaggini Roberto Data curation 1 Veneziani Gianluca Software Data curation 1 Ranucci David Data curation 2 Taticchi Agnese Data curation 1 Esposto Sonia Conceptualization Methodology Writing - review & editing Visualization Supervision 1 Otero Laura Academic Editor 1 Department of Agricultural, Food and Environmental Sciences, University of Perugia, 06124 Perugia, Italy 2 Department of Veterinary Medicine, University of Perugia, 06124 Perugia, Italy * Correspondence: [email protected] 03 3 2023 3 2023 12 5 108719 1 2023 20 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The purpose of this experimentation was to study the evolution of the quality of two types of blast-frozen ready-to-(h)eat meals, tortellini and a vegetable soup, during a short shelf life of 70 days. The analyses, performed in order to identify any variations resulting either from the freezing process or from the subsequent storage, carried out at the temperatures of -30 degC and -18 degC, respectively, examined the consistency of the tortellini and the soup, the acidity and the peroxide value of the oil extracted from them, the phenols and carotenoids present in the soup, the volatile compounds in the tortellini and the soup, and a sensory analysis of both products. The results showed that, during the 70 days of shelf life, there was no variation in the texture of the tortellini, but there were changes in the consistency of the soup, which decreased as the days of storage went on. Furthermore, statistically significant increases (p < 0.05) in the acidity and in the peroxide value of the oil of the soup were observed during the storage period; however, no statistically significant difference (p > 0.05) in the peroxide value of the oil of the tortellini was found. Moreover, no quantitative changes were observed in the phenolic compounds and carotenoids in the soup or in the volatile substances of either product. Finally, the sensory analysis confirmed, together with the chemical data, that the blast-freezing process adopted was suitable to maintain the good quality of these fresh meals, even if some technical modifications (in particular, lower freezing temperatures) should be adopted to improve the final quality of the products. ready meals frozen short shelf life evolution of quality texture peroxide value phenolic compounds carotenoids volatile compounds sensory analysis European Union--Next Generation EUECS00000041 This publication was funded by the European Union--Next Generation EU (Project Code: ECS00000041; Project CUP: C43C22000380007; Project Title: Innovation, digitalization and sustainability for the diffused economy in Central Italy--VITALITY). pmc1. Introduction The term 'convenience food' refers to ready-to-eat foods, such as ready-to-eat vegetables and salads, ready-made soups and sauces, frozen dietetic dishes, pizza, meals for microwaves, etc. These preparations satisfy the user's need to speed up preparation times and are designed and appreciated especially by those who work, by single people, by those with little experience in the kitchen or little time available, and by the elderly . More precisely, convenience foods can be sorted into two distinct categories depending on their degree of processing: partially prepared foods (ready-to-cook) and ready-to-eat/ready-to-(h)eat foods. These convenience products are, therefore, foods for which a significant fraction of the preparation time, cooking skills and necessary applied energy is performed by the food industry or retailers, instead of by people at home. Regarding the preservation of these products, freezing is one of the preferred processes, because it keeps the qualitative characteristics of the food almost intact and prolongs its shelf life . Freezing is an operation by which a food is brought to a temperature below its freezing point and a part of the water in it undergoes a change in state, forming ice crystals. Extreme cold retards the growth of microorganisms and slows down chemical changes that can affect the food quality and cause its spoilage . The main thermal events during the freezing process are accompanied by a reduction in the heat content of the material to be frozen, which cools down to the temperature at which the nucleation phase begins; indeed, before the ice formation, it is necessary to form a nucleus on which the crystal can grow. Once the first crystal appears in the solution, there is a phase change from liquid to solid with further crystal growth; thus, there is an accretion phase . The number of crystallization nuclei increases with the increase in the undercooling interval, and the latter is longer the higher the freezing speed is. When thawed, the food retains its texture and intracellular fluids . Very frequently, frozen ready meals are heated in a microwave oven as an alternative to using an electric oven. With this technology, heat is generated throughout the material, leading to faster heating rates and shorter processing times compared to conventional heating. Furthermore, in order to maintain a high nutritional value and a high level of quality, the technology selected for packaging should also be carefully considered and studied. Packaging technology is essential not only for food protection, but also for consumer convenience; indeed, the fusion of packaging technology with advanced materials and functional packaging has provided more convenience to consumers, and several innovative packaging materials have been introduced in the ready meal market, such as microwave susceptors, self-heating packaging, active and intelligent packaging, and biodegradable packaging . It is evident that, especially in recent years, ready-to-(h)eat meals are becoming more common and the food industry is looking for technological solutions that guarantee both food safety and the high quality of these products. Therefore, the purpose of this experimentation was to investigate the evolution of the quality of two different types of frozen ready-to-(h)eat meals after microwave heating and during a real-time short shelf life lasting 70 days. Notably, the two products were very different from each other, both in their ingredients and in their nutritional composition; the tested samples were tortellini stuffed with meat with a cream and cooked ham sauce, and a creamy pumpkin and carrot soup made with barley. The quality of ready meals must be maintained not only while they are frozen and in the market, but also throughout their DMD. In this work, it was not possible to take that longer period into consideration, but a series of two-stage, real-time short shelf life experiments were performed. Such experiments are very useful for these particular products, since the company that supplied the two frozen ready meals works mainly with the HO.RE.CA channel, which generally uses large quantities of these products within short periods of time. 2. Materials and Methods 2.1. Products The products used for this work were kindly donated by Pronto Green S.p.A., a company in Perugia (Umbria, Italy) that produces and markets frozen foods. For the purpose of carrying out this study, the following two products were used: fresh and frozen samples of pumpkin and carrot soup (325 g each), and fresh and frozen samples of tortellini with cream and cooked ham (300 g each). The ingredients of the soup were as follows: water, pumpkin 32%, carrots 12%, mashed potatoes, barley 4%, leek, sunflower seed oil and salt. Regarding the tortellini, the ingredients were as follows: fresh stuffed egg pasta cooked (55%) (ingredients: fresh egg pasta (50%) (ingredients: durum wheat semolina, egg (20%), wheat gluten), meat filling (32%) (ingredients: beef (27%), pork (20%), mortadella (18%), cheese, breadcrumbs, onion, celery, carrots, egg, sunflower oil, nutmeg, garlic, pepper), water and salt), cream (23%), rehydrated skimmed milk, cooked ham (3.6%), wheat flour, butter, cheese, salt and nutmeg. The two ready-to-(h)eat meals were taken to the Department of Agricultural, Food and Environmental Sciences of the University of Perugia, where the fresh samples were placed inside a cold room at the temperature of 4 degC, while the frozen samples were distributed inside two chest freezers at the temperature of -18 degC. 2.2. Real-Time Short Shelf Life Test The analyses of the samples were carried out with the aim of performing a real-time short shelf life test, in order to determine whether there were any changes in the rheological and texture properties, and the sensory characteristics of the two products during their storage during the short-term period. The products were then employed as follows for analysis: at time 0, both the fresh samples and samples that had just undergone the freezing treatment were used; at time 1, frozen samples kept at a temperature of -18 degC for 35 days were used; at time 2, frozen samples kept at a temperature of -18 degC for 70 days were used. To carry out the rheological and texture analyses, the chemical analyses and the sensory analysis, the samples were prepared following the instructions given on the packaging. In particular, the tortellini with cream and ham were heated, still frozen, in a microwave oven, without opening the package, for 4 min at "high" power. The creamy pumpkin and carrot soup with barley was heated, still frozen, in a microwave oven, slightly lifting the protective film on the package, for 8 min at "medium-high" power. Both products were then mixed before being used for the analyses. 2.3. Texture Profile Analysis of the Tortellini The ready-to-(h)eat tortellini were subjected to TPA analysis using the TVT 6700 Texture Analyzer machine (Perten, Stockholm, Sweden) consisting of a 672040 Compression Plate 40 mm stainless steel piston that exerts mechanical pressure on the samples. The instrument settings for the analysis were as follows: the sample height was 18.0 mm, the starting distance from the sample was 3.0 mm, the number of cycles was 2, the compression was 50%, the custom force or distance was 0.0 mm, the hold time was 2.0 s, the distance above the trigger was 1.0 mm, the initial speed was 1.0 mm/s, the test speed was 1.0 mm/s, the retract speed was 1.0 mm/s, the trigger force was 5.0 g, the data rate was 200.0 pps and the diameter was 0.0 mm. For the analysis, both the fresh tortellini and the frozen tortellini at time 0, time 1 and time 2 were previously heated in a microwave oven and allowed to cool to room temperature. Furthermore, only completely intact tortellini were taken into consideration and an attempt was made to eliminate the small pieces of ham which formed part of the sauce. During the TPA analysis, two forces were exerted on the tortellini, which gave the results "Peak Force A" (g) and "Peak Force B" (g), which represented the work necessary to deform the samples in the first and second compressions, respectively. The parameters obtained from the analysis were hardness, i.e., the maximum load detected during the first compression cycle; cohesiveness, which was the ratio between the work performed in the second compression cycle and the work performed during the first compression cycle, calculated by dividing the area under the second peak by the area under the first peak; springiness, i.e., the return of the compressed sample in the time between the end of the first compression cycle and the beginning of the second cycle, measured as the compression distance to arrive at "Peak Force B" divided by the compression distance to arrive at "Peak Force A"; adhesiveness, which was the work required to overcome the attractive forces between the sample and the piston surface during the return of the first cycle; gumminess, which was the result of hardness x cohesiveness; and chewiness, which was the result of gumminess x springiness . 2.4. Evaluation of the Consistency of the Soup The evaluation of the consistency of the soup was determined using a Bostwick viscometer consistometer (Greensenselab, Wagram an der Donau, Austria), an instrument equipped with a 2 mm thick stainless steel tank and a capacity of 100 mL, with adjustment feet and a level bubble supplied. A movable bulkhead separated the sample space from the 23 cm long slide lane, graduated in 0.5 cm fractions. Each sample, after being heated in a microwave oven (as described in Section 2.2) and allowed to cool down to room temperature (about 20 degC), was placed on the tray closed by the bulkhead, taking care to even out the level with a spatula. After releasing the bulkhead by acting on the snap system, the sliding stroke of the sample was read over a time of 30 s and the operation was repeated twice for each sample. 2.5. Determination of the Acidity and the Peroxide Value of the Oil Extracted from Soup and Tortellini For the extraction of the oil from the soup and tortellini, 100 g and 70 g of product were taken, respectively, and mixed with hexane in a 1:3 ratio (300 mL for the soup and 210 mL for the tortellini), using ULTRA-TURRAX T25-IKA for 1 min at 17,000 rpm, and subsequently kept under stirring at 215 rpm at room temperature for 30 min. The mixture thus obtained was filtered with Perfect 2 Cordenons filter paper (Milan, Italy) and the filtrate was evaporated under a vacuum at 35 degC until the complete evaporation of the solvent. The acidity and the peroxide value were determined for the residual oil in accordance with the provisions of EU Reg. 2019/1604 . 2.6. Extraction and Evaluation of Phenols and Carotenoids in the Soup The extraction of the phenolic compounds and carotenoids present in the soup was carried out, as reported in the work of Motilva et al. , making the following modifications: 5 g of soup was homogenized with ULTRA-TURRAX T25 for 1 min at 17,000 rpm with 10 mL of a hexane/acetone/ethanol mixture (50:25:25 v/v). The homogenate was centrifuged at 9000 rpm for 10 min, then the supernatant was placed in a separatory funnel and 10 mL of water was added, and the two phases were separated and further purified, as reported by Motilva et al. ; the supernatants obtained from each phase (organic and aqueous) were evaporated by rotavapor. The organic extract obtained was used for the determination of carotenoids, while the aqueous extract was used for the evaluation of phenolic compounds. The determination of carotenoids was carried out using an Agilent Technologies HPLC instrument model 1100, consisting of a quaternary pump complete with degasser, autosampler, thermostatted column compartment, UV-Vis (DAD) and fluorescence (FLD) photodiode detector. A Lichrospher Si 60 250 x 4 mm normal-phase column with a particle diameter of 5 mm (Merk KgaA, Darmstadt, Germany) was used for the analysis of b-carotene. Before being analyzed in HPLC, the sample was filtered with 0.22 mm PVDF syringe filters (Carlo Erba Reagents, Milan, Italy); the injected volume was 50 mL and the eluent flow was 1.3 L/min, using a mixture n-hexane/isopropyl alcohol (99.5:0.5 v/v) (solvent A) and n-hexane/isopropyl alcohol (70:30 v/v) (solvent B). The gradient was varied as follows: 100% solvent A and 0% solvent B for 2 min, in 8 min, 95% solvent A and 5% solvent B, in 5 min, 25% solvent A and 75% solvent B for 4 min and back to the initial conditions in 3 min, maintained for 5 min. The total chromatographic run time was 35 min. The ChemStation, also from Agilent Technologies, in addition to controlling the entire instrumentation, performed the processing of the chromatographic data (Agilent Technologies, Palo Alto, CA, USA). For the determination of b-carotene and lutein, the DAD was set at 450 nm. The quantification of b-carotene and lutein was performed using the calibration curves of the standard compounds, and the results are expressed as mg/kg. The evaluation of the phenolic compounds that were present in the aqueous extract obtained from the soup was carried out with the same HPLC instrumentation reported previously for the determination of b-carotene and lutein. The aqueous extract was filtered with 0.22 mm PVDF syringe filters (Carlo Erba Reagents, Milan, Italy), and the analysis and determination of the phenolic compounds was performed as reported by Taticchi et al. . 2.7. Evaluation of Volatile Compounds in Soup and Tortellini The evaluation of the composition of volatile substances in the soup and the tortellini was carried out by mass spectrometry analysis coupled to gas chromatography (GC/MS) through headspace sampling by solid phase microextraction (SPME). The samples (2 g) were placed in 20 mL vials, 1 mL of a saturated solution of NaCl and 100 mL of an internal standard (4-methyl-2-pentanol 750 mg/L) were added, and the vials were hermetically closed and placed in the autosampler. SPME sampling of volatile compounds was performed by exposing the fiber consisting of Carboxen/divinylbenzene/polydimethylsiloxane 50/30 mm, 2 cm long (Supelco Inc., Bellefonte, PA, USA). Before adsorption, the sample was kept under stirring (750 rpm) for 30 min at 40 degC. The adsorbed compounds were then thermally desorbed for 5 min by inserting the fiber into the GC injector maintained at 250 degC. The analyses were carried out with an Agilent Technologies 7890B GC, equipped with a "Multimode Injector" (MMI) 7693A (Agilent Technologies, Santa Clara, CA, USA) and a thermostatted PAL3 RSI 120 autosampler equipped with a fiber conditioning module and shaker (CTC Analytics AG, Zwingen, Switzerland); this was coupled to a single quadrupole MS 5977B (MSD) with an XTR (Extractor Ion Source) electron impact source (Agilent Technologies, Santa Clara, CA, USA). For the separation of the volatile compounds, a DB-WAXetr fused silica capillary column was used, with a length of 50 m, an i.d. of 0.32 mm and a film thickness of 1 mm (Agilent Technologies, Santa Clara, CA, USA). Helium was used as carrier gas at a flow of 1.7 mL/min, which was kept constant throughout the analysis time by means of an Electronic Flow Control (EFC) device. The GC column oven temperature was set according to the following schedule: the initial temperature was 35 degC and maintained for 4 min, then increased to 45 degC at 5 degC/min, further increased to 150 degC at 4 degC/min, further increased up to 180 degC at 8 degC/min, maintained for 2 min, and finally brought to 210 degC at 11 degC/min and maintained for 13.77 min; under these conditions, the total analysis time was 55 min. The injector was set at a temperature of 250 degC. The temperature of the "transfer line" was set at 215 degC; regarding the experimental conditions of the mass spectrometer, the temperature of the source was 190 degC and that of the quadrupole was 150 degC. The electron impact mass spectrum (EI) was recorded with an ionization energy of 70 eV in the mass range 25-350 a.m.u., 4.3 scans/s, and the MS spectra were acquired in scan mode. The processing of the collected data was carried out using the Agilent MassHunter B.08.00 software with the Unknown Analysis module. The identification of volatile compounds was performed by comparing the mass spectra and retention times thus obtained with those of pure analytical standards and with the spectra of the NIST-2014 library. The volatile compounds were quantified and expressed in mg/kg by comparing the area of each peak of the extracted ion (corresponding to each compound evaluated) with the ion area of the peak of the internal standard (4-methyl-2-pentanol), as reported by Xiao et al. . 2.8. Sensory Analysis At the Department of Agricultural, Food and Environmental Sciences of the University of Perugia, for both the tortellini and the soup, a triangle test according to the ISO 4120:2021 standard was performed on the fresh and frozen samples at time 0 after being heated in a microwave oven (as described in Section 2.2) and cooled to room temperature; this was in order to observe whether 25 judges were able to distinguish the fresh product from the frozen one. Each panel member was presented with three samples that were coded differently, two of which were identical and one was different. In this type of test, the taster has the task of identifying the different samples; even if he is unable to do so, he must still give an answer (forced choice). The three samples were presented accompanied by a sheet, which provided instructions for carrying out the test and which indicated, according to the tasting sequence, the codes of the samples to be examined . The criteria for determining the significance of the freezing treatment were based on tables for the binomial distribution of the triangle test. For this test, 25 tasters (12 men and 13 women aged between 25 and 55) were employed and the results were considered significant by applying a risk factor a equal to 0.01 with probability Pd 30% (percentage of correct answers beyond chance, upper limit value of the one-tailed confidence interval corresponding to b = 0.01). The results were elaborated through the tables of significance for this type of test. The form used by the tasters for this test is shown in Form S1 in the Supplementary Materials. A quantitative descriptive sensory analysis (QDA) was also performed on both products when fresh, frozen at time 0, frozen at time 1 and frozen at time 2, according to the ISO 13299:2016 standard and using 10 expert panelists (4 men and 6 women aged between 25 and 55) who had been trained to recognize and quantify the sensory characteristics of each of the two products. The number of trained panelists was decided based on the amount of product available. The evaluations were conducted in a classroom with single stations, one for each judge, where approximately 40 g of product was served for each sample after being heated in a microwave oven (as described in Section 2.2), cooled to room temperature, and then placed in plastic tasting glasses marked by an alphanumeric code. The quantitative descriptive sensory analysis was performed using a specific sensory analysis form for each product. The specific descriptors for appearance, odor, taste, texture, trigeminal sensations and final sensations were included on the two forms (Form S2 and Form S3 in the Supplementary Materials). The different attributes were quantified on a 9 cm unstructured ordinal intensity rating scale. 2.9. Statistical Analysis To compare the results obtained in the experimentation and test the differences between the different products, the Tukey test was used; it was performed with SigmaStat v.2.0 software. PanelCheck software version 1.4.2 (Nofima, Tromso, Norway) was used for the statistical processing of sensory analysis data, which took place through the application of PCA (principal component analysis). 3. Results 3.1. Evolution of the Texture of the Tortellini The data concerning the structural characteristics of the tortellini are reported in Table 1, but they have an important standard deviation; this depends on a whole series of extrinsic and intrinsic variables linked to the product itself and to the conditions in which it was found. Indeed, the product analyzed had a condiment, i.e., a sauce made from cream and cooked ham, which was distributed in a heterogeneous way on the tortellini. For this reason, the tortellini analyzed could have different amounts of sauce. Furthermore, the shape of the container used for their packaging and heating could result in not all the tortellini receiving the same amount of heat and not heating up in the same way. Another important factor was that tortellini are a type of filled pasta; therefore, the meat could occupy a space inside the tortellini that was not exactly the same for each of them. For these reasons, the matrix examined was very heterogeneous, and this could explain the high values obtained for the standard deviation. It can be observed how the hardness value for the sample at time 2 decreased by 31.4% compared to that for the fresh sample. As was also reported in the work of Zhang et al. , hardness is an important parameter of dough quality; the lower the hardness in a given range, the softer the dough. Therefore, increasing the hardness does not improve the dough . It can be assumed that there was a decrease in hardness during the frozen storage of the product because some macrocrystals could be formed during the storage period that, at the time of thawing, probably damaged cell walls and thus had an effect on the consistency of the product. Regarding the springiness, chewiness and gumminess of the sample at time 2 compared to the fresh sample, these decreased by 32.8%, 56.4% and 34.4%, respectively. In particular, the decrease in chewiness may have happened because the gluten network was damaged during frozen storage, leading to the increase in the leaked soluble substance on the noodle surface when reheating . 3.2. Evolution of the Consistency of the Soup Figure 1 shows that there was a statistically significant difference (p < 0.05) in the texture of the soup that had been frozen compared to the fresh soup. The distance traveled along the slide lane by the fresh soup was equal to 4.5 cm, while for the frozen one at time 0, the value was equal to 11.1 cm. A value comparable to the latter was also found at time 1 (11.0 cm), while there was a further increase in the distance traveled by the frozen soup at time 2, equal to 15.3 cm. This result was in accordance with what was reported in the work of Araujo-Rodrigues et al. , which examined baby carrot and cherry tomato pulps, studying the impact of the freezing process and monitoring parameters such as consistency over 6 months of storage. The results of that study showed that, in both cases, a significant decrease in viscosity was observed after freezing. In the carrot pulp, although the decrease in viscosity was more evident in the first months of freezing, there was a significant decrease throughout the storage period, except from the fifth to the sixth month of storage when there were no significant changes in viscosity values. Regarding the cherry tomato pulp, the variation in viscosity was even more evident in the first months of frozen storage, but the results suggested significant variations in all the months analyzed. This was possibly because the ice crystals produced during the freezing process could have caused damage to the integrity of the cell membranes, and because the consequent loss of water from the intracellular compartments affected the physicochemical and physical properties of the product, such as viscosity. In general, lower material properties are found in frozen vegetable foods than in their fresh equivalents . 3.3. Evolution of Acidity and Peroxide Values of the Oil Extracted from Soup and Tortellini Figure 2a shows a statistically significant progressive increase (p < 0.05) in the acidity (%) of the soup over time, from a value equal to 0.71% for the fresh soup to 1.40% for the frozen soup tested at time 2 (+97.2%). This could be because the product was processed using a freezing technology, but the temperature at which it was stored was -30 degC in a forced air cell for an entire night. This means that there was the formation of a smaller number of crystals compared to an ultra-rapid freezing process (which can employ temperatures of -50 degC/-70 degC) and that these crystals were also larger in size. It is plausible that, as the storage time of the product at a temperature of -18 degC increases, these crystals may grow further; at the time of thawing, there may then be a greater rupture of the cell membranes, with the consequent release of the cellular content, in which there are intracellular enzymes such as lipases. The lipases act on triglycerides by hydrolyzing the ester bond and leading to the formation of free fatty acids, which increase the acidity of the products. In this case, the lipases could not be completely inactivated because the freezing occurred at temperatures that were not low enough. Therefore, since the freezing process lasted overnight, there could be some areas of free super-concentrated water that was not completely crystallized and was available for enzymes. Regarding the peroxide values, a parameter evaluated to measure the degree of the oxidative rancidity of fats, Figure 2b shows that there was a statistically significant (p < 0.05) increase when comparing both the fresh and frozen soups at time 0 with the frozen soups at times 1 and 2 of storage. Thereafter, the value remained unchanged from time 1 to time 2 of storage. In Figure 3, when comparing the fresh product to the frozen product at storage time 2, it can be observed that the peroxide value in the tortellini had increased by 16.7%, but the data were not statistically significant (p > 0.05). Data relating to the peroxide values suggested that the products were well protected from oxidation by oxygen. This could depend mainly on the packaging used, which included a film that sealed the container and ensured that the products were not only protected from oxygen, but also from other factors that could promote the oxidation of fatty acids, such as light. There was a statistically significant increase (p < 0.05) in the number of peroxides in the soup, but not in the tortellini because of the different types of fatty acids contained in the two products. The tortellini contained mainly fats of animal origin (derived from the meat and cream used), so they were mostly saturated fatty acids, which are more stable with respect to oxidation. In the soup, on the other hand, the ingredients were all of vegetable origin, so there was a greater content of mono and polyunsaturated fatty acids, which are more unstable and more easily subject to oxidation. 3.4. Evolution of Phenolic Compounds and Carotenoids in the Soup Regarding the content of phenolic compounds and carotenoids in the soup, the molecules extracted and evaluated from the product were b-carotene, lutein, a-tocopherol, quercetin-3-o-rutinoside and quercetin. Table 2 shows that there seemed to be a progressive tendency towards a decrease in these compounds over time; comparing the fresh product with the frozen at time 2, the b-carotene underwent a decrease of 3.1%, lutein decreased by 4.2%, a-tocopherol decreased by 3.0%, quercetin-3-o-rutinoside decreased by 1.7% and quercetin decreased by 11.1%. However, the decreases observed were not statistically significant (p > 0.05); therefore, it could be assumed that the freezing process did not have a negative impact on the nutritional and health qualities linked to the carotenoid and phenol contents of the soup, and especially that there were no statistically significant differences even during the storage period of 70 days at -18 degC. The work of Im et al. analyzed the total phenol content of frozen potatoes and carrots treated with different pre-treatment and thawing methods. From the results of that study, it was seen that there was no significant difference in the total phenol content of potatoes after thawing (p > 0.05); however, when taking into consideration different pre-treatments, the phenol content was between 2.07 and 2.09 mg GAE/mg in the control (not pre-treated before freezing), between 1.44 and 1.54 in the HB product (blanched in hot water at 100 degC), and between 1.59 and 1.72 in the SB product (blanched in steam at 100 degC). During the heat treatment, the total phenol content showed a tendency to decrease compared to the control. One study has shown that when a lotus root was blanched in hot water, the total phenol content decreased with increasing the heat treatment time, and in another work, it was evident that blanching within 5 min could preserve the nutritional content. The difference in the total phenol content between the same pre-treatment groups was 0.02~0.13 mg GAE/mg, and no significant change was observed according to the thawing method. Therefore, it was concluded that the total phenol content of potatoes after thawing varied depending on the pre-treatment method, rather than on the thawing method. Regarding the polyphenol content of carrots, this did not show a clear trend according to the pre-treatment method or the thawing method; however, when pre-treated with SB and thawed in running water, they did show a higher total phenol content, at 1.45 +- 0.21 mg GAE/mg . 3.5. Evolution of Volatile Compounds in Soup and Tortellini Figure 4 shows that the content of volatile substances in the fresh soup was 89.7% terpenes, followed by 4.4% aldehydes, 2.5% furans, 1.8% alcohols, 0.9% sulfur compounds and 0.7% ketones. The total of volatile compounds in the fresh soup was equal to 14,852.5 mg/kg (expressed as 4-methyl-2-pentanol). Table 3 highlights the fact that most of the volatile substances belonging to the various classes of compounds remained unchanged during the real-time short shelf life test, and that there were no statistically significant differences (p > 0.05) between the fresh soup and the frozen soup at storage time 2. Observing the data, however, it is possible to see how some substances gradually increased; for example, hexanal, which is one of the main oxidation indices for food products, had increased by 11.0%. The same trend was also found for other aldehydes linked to oxidation, such as pentanal (+0.4%), nonanal (+2.6%) and 2,4-decadienal (+21.8%), while there was a small decrease in (E)-2-heptenal (-1.2%). In general, there was an increase of 6.3% in the total aldehydes between the fresh product and the frozen product tested at storage time 2, but the data were not statistically significant (p > 0.05). The alcohols in the soup, in particular 2-methyl-1-butanol, 1-pentanol and 1-hexanol, were probably derived from the barley grains it contained. Indeed, as reported in the study by Cramer et al. , alcohols are the major quantitative constituents of barley volatiles, followed by aldehydes, ketones and furans. The alcohol content in the soup appeared to have a decreasing trend over time (-4.7% in the frozen soup at time 2 compared to the fresh soup), but the data were not statistically significant (p > 0.05). Regarding ketones, in the soup there was only acetoin, which decreased by 4.7% at storage time 2; however, in that case, the result was also not statistically significant (p > 0.05). The most abundant compounds in the soup were terpenes, such as limonene, a-pinene, b-pinene, b-myrcene, g-terpinene and caryophyllene. This was because the product was completely plant-based and one of the main ingredients was carrots. As reported in the study by Kjeldsen et al. , which examined changes in the volatile compounds of carrots (Daucus carota L.) during refrigerated and frozen storage, terpenoids, such as monoterpenes, sesquiterpenes and irregular terpenes, were the predominant class of volatile compounds in carrots in terms of number and quantity. Terpenoids accounted for more than 99% of the total volatile mass in carrots. The main monoterpenes were a-pinene, sabinene, b-myrcene, limonene, g-terpinene, p-cymene and terpinolene . These results agreed fairly well with the data from the present study. In general, all plants are naturally rich in terpenes, as the latter perform important biological activities. Indeed, these metabolites have an important role in nature since they can act as an indirect form of defense in plants against herbivores and pathogenic microorganisms, but also against extreme abiotic factors such as temperature, sun exposure, humidity and a lack of nutrients . The total number of terpenes seemed to undergo a very small decrease of 0.2%, but the data were not statistically significant (p > 0.05). Inside the fresh product there was also a small amount of furans (2.5%), which probably derived from the cooking process to which both the fresh and the frozen soup were subjected. The quantity of furans underwent an increase of 16.7% during the short-term shelf life up to time 2, but this result also was not statistically significant (p > 0.05). Another small percentage of volatile substances found in the soup product was indicative of sulfur compounds (0.9% in fresh soup), in particular dimethyl sulfide and dipropyl disulfide. Generally, sulfur compounds are found as secondary metabolites in both plants and microorganisms, where they mostly have pleasant odors rather than offensive ones. These compounds are distributed in some plant families, including Brassicaceae, Apiaceae, Liliaceae, Caricaceae, Capparaceae, Solanaceae and Rutaceae ; therefore, it is not surprising to find small quantities of them in plant-based products, such as the soup under examination in this work. The amount of sulfur compounds had an increasing trend (+16.2% at storage time 2), but the data were not statistically significant (p > 0.05). In general, when observing all the volatile compounds present in the soup at storage time 2, there were no statistically significant changes in them (p > 0.05) compared to the fresh product. As shown in Figure 5, even for the fresh tortellini, the content of volatile substances was mostly made up of terpenes (92.2%), followed by ketones (5.6%), aldehydes (1.1%), alcohols (0.6%) and organic acids (0.5%). The total amount of volatile compounds in fresh tortellini was 31,556.0 mg/kg (expressed as 4-methyl-2-pentanol). As was the case with the soup, in the tortellini (Table 4), there was also an increase in the total number of aldehyde compounds (+9.5%) when comparing the fresh product to the frozen one at storage time 2, but the data were not statistically significant (p > 0.05). In particular, there was an increase in aldehydes linked to oxidative processes, such as pentanal (+12.0%), hexanal (+10.2%), (E)-2-heptenal (+41.3%), nonanal (+16.1%) and 2,4-decadienal (+27.2%); however, in this case, the results were also not statistically significant (p > 0.05). Moreover, in the tortellini, there was a small percentage of alcohols (0.6% in the fresh product), in particular 1-pentanol and 1-hexanol, since the wheat flour used for the production of the tortellini contained volatile compounds such as alcohols and ketones . The alcohol content of the tortellini showed a decreasing trend (-5.3%) during the storage period up to time 2, but the data were not statistically significant (p > 0.05). Regarding ketones, these constituted a greater percentage of the total volatile substances in the tortellini (5.6% in the fresh ones) than was found in the soup. This was not only because of the ketone content in the volatile compounds of the wheat flour used in the dough of the tortellini, but also because this dish had a sauce (cream and cooked ham) that contained a high quantity of lipids that could undergo oxidative processes. The ketones (acetoin, 2-pentanone, 2-heptanone, 2-nonanone) seemed to undergo an increase of 3.3% during storage up to time 2, but the data were not statistically significant (p > 0.05). In the tortellini, as in the soup, most of the volatile substances found were terpenes (92.2% in the fresh product); in this case, their presence was mainly linked to the spices present in the filling of the tortellini, as well as to those used to prepare the sauce used as a condiment. During the storage period, the total number of terpenes tended to decrease (-1.0%) compared to the fresh product, but the data were not statistically significant (p > 0.05). A very small percentage of volatile substances, equal to 0.5% in the fresh tortellini, was made up of organic acids, such as acetic acid, butanoic acid and pentanoic acid. The presence of these last two organic acids was mainly linked to the cream present in the sauce of the tortellini. There was an increase in the sum of organic acids at storage time 2 compared to the fresh product (+3.3%), but this result was not statistically significant (p > 0.05). 3.6. Sensory Analysis In order to determine any sensory differences related to the freezing treatment, the first sensory evaluation consisted of a discriminant triangle test. Table 5 shows that there was a significant difference between the fresh and frozen versions of both types of ready-to-(h)eat products studied. Of the 25 expert panelists who served as judges, 22 were able to identify the "different" sample when a factor b = 0.01 was applied, while 17 was the maximum number of correct choices to conclude that there was a similarity between the samples, according to ISO 4120:2021 . The next step was to understand in what ways and how much the products differed. For this reason, further sensory evaluation consisted of a quantitative descriptive sensory analysis performed by a trained sensory panel (10 panelists), which compared all the samples of soup and tortellini in terms of their appearance, odor, taste and texture/mouthfeel attributes. The collected data were statistically analyzed using principal component analysis (PCA). Two biplots illustrate the results of the PCA: the first one is for the visualization of the soup samples analyzed and the second one is for the tortellini . Figure 6 shows that the first two principal components (PC1 and PC2) explained 88.6% of the total variability. In addition, it is possible to observe how the samples were distributed differently depending on whether or not they were subjected to the deep-freezing treatment, and also depending on the storage time. In particular, along the first principal component (PC1), there was a clear distinction among the fresh soup sample (NFS), the frozen soup samples at time 0 (FS T0) and at time 1 (FS T1), and the frozen sample at time 2 (FS T2). Furthermore, along the second principal component (PC2), there was a clear distinction, especially for the FS T0 sample; this was located in the lower part of the biplot compared to the NFS, FS T1 and FS T2 samples, which were located in the upper part. The variables that had the greatest weight in differentiating the NFS sample along the first component (PC1) were adhesiveness, creaminess, viscosity, softness and consistency. The FS T0 sample, on the other hand, differed in variables such as moisture and homogeneity of color, while the FS T1 sample was also distinguished by variables such as consistency, chewiness, crunchiness (of the barley grains contained in it), fresh vegetable odor, potato odor and cohesiveness. Finally, in the FS T2 sample, all the descriptors that characterized the NFS, FS T0 and FS T1 samples were less relevant; in particular, this sample differed visually, due to its translucency/wateriness. Along the second component (PC2), the differentiation of the samples was reconfirmed based on the storage time in the freezer at a temperature of -18 degC. Figure 7 shows that the first two principal components (PC1 and PC2) could help explain 82.1% of the total variability in the tortellini samples. Furthermore, it is possible to observe how, in this case also, the samples were distributed in a different way depending on whether or not they were subjected to the deep-freezing treatment and also as a function of the conservation time. In particular, the samples frozen at time 1 (FT T1) and at time 2 (FT T2) were on the right side of the first principal component (PC1), opposite to the sample frozen at time 0 (FT T0) and the fresh sample (NFT), which were located in the left part of the first component (PC1); similarly, they were found distributed in the upper and the lower parts of the second principal component (PC2), respectively. The short shelf life for tortellini allowed us to identify, along the first principal component (PC1), a similarity between the fresh sample and the freshly frozen sample; this is the case even if after a certain storage time, in the FT T1 and FT T2 samples, it was possible to notice some differences related to the concentration of certain descriptors, including aftertaste, persistence, umami, meat odor, vegetable odor and moisture. The FT T0 sample differed from the others for variables such as the bright yellow color of the pasta, firmness and the smoothness/sliminess of texture. Finally, the NFT sample was located in the lower left quadrant and differed along the first principal component (PC1) for visual characteristics, such as the clotted cream of the sauce and being overcooked; meanwhile, along the second principal component (PC2), variables related to texture, such as chewiness, springiness and gumminess, were also distinguished. It seems that the freezing process did not have a negative impact on tortellini even if it was not ultra-rapid, probably due to the lower water content in this type of food. Indeed, if water had been present in larger quantities, it could have been subject to migration and might have created more difficult areas to freeze. 4. Conclusions To the best of our knowledge, this is the first scientific work that has fully evaluated the impact of the freezing process and subsequent microwave heating on the rheology, chemical composition and sensory quality of ready-to-(h)eat meals. From the data obtained in the experimentation, the influence that the freezing process can have on ready-to-(h)eat meals can be seen; in addition, and above all, how the quality of this type of product can evolve during a real-time short shelf life can also be observed. The rheological analyses of the tortellini highlighted that the fresh product was harder, more elastic, more chewable and gummier than the frozen ones, data that were corroborated by the results of the sensory analysis. As far as the consistency of the soup was concerned, in that case also the sensory analysis data reflected the results of the instrumental analyses; the fresh soup appeared to have a greater consistency than the frozen ones at all three storage times, and notably, the consistency seemed to decrease with the increase in the days of storage. The chemical analyses underlined that there was an increase in the acidity of the oil in the soup, probably linked to the temperatures and freezing times of the product. In both the soup and the tortellini there was also an increase in the peroxide values, particularly at storage time 2, but the data were statistically significant (p < 0.05) only in the case of the soup. Regarding the content of phenols and carotenoids in the soup, the decreases found over the days of storage were not statistically significant (p > 0.05). Finally, the variations in the volatile compounds of the two products were also not statistically significant (p > 0.05). The sensory analysis data confirmed those data obtained from chemical and rheological analyses, and in some cases, they added information that was not examined at an instrumental level. In conclusion, the freezing process and the subsequent storage time at -18 degC during a real-time short shelf life test lasting 70 days did not affect the general acceptability of the two products, but only had an impact on some sensory characteristics. In general, it should be emphasized that the final quality of the products strongly depended on the temperature and the duration of the freezing process; the lower the temperatures and the shorter the freezing times, the more the damage caused by freezing was reduced, as numerous scientific works have amply demonstrated. Since the products analyzed were products from a small-medium-sized company, it was normal that the systems used for freezing utilized a blast-freezing method that did not drop below -30 degC, unlike large industries that often have much more powerful equipment in terms of operating capacity and product quality. One useful technological improvement could be to circulate the air in the cold room at a higher speed so as to allow the process to have a shorter duration. Finally, it should also be noted that the products were already packaged when they underwent the freezing process, so the packaging barrier should also be taken into consideration. Acknowledgments The authors thank the company Pronto Green S.p.A. for supplying the products analyzed in this work. Supplementary Materials The following supporting information can be downloaded at: Form S1: Triangle test form; Form S2: Ready-to-(h)eat creamy soup sensory analysis form; Form S3: Ready-to-(h)eat tortellini sensory analysis form. Click here for additional data file. Author Contributions I.D.: formal analysis, investigation, data curation, writing--original draft preparation, writing--review and editing. S.U.: data curation, formal analysis, methodology. B.S.: data curation. M.S.: visualization, project administration, funding acquisition. R.S.: data curation, software, validation. G.V.: data curation. D.R.: formal analysis, data curation. A.T.: data curation. S.E.: conceptualization, methodology, writing--review and editing, visualization, supervision. All authors have read and agreed to the published version of the manuscript. Data Availability Statement No new data were created or analyzed in this study. Data sharing is not applicable to this article. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Figure 1 Evolution of the consistency of the soup. The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh soup (not frozen); Frozen T0 = frozen soup at the time of freezing treatment; Frozen T1 = frozen soup after 35 days of storage; Frozen T2 = frozen soup after 70 days of storage. Figure 2 (a) Evolution of acidity of the oil extracted from the soup; (b) evolution of peroxide value of the oil extracted from the soup. The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh soup (not frozen); Frozen T0 = frozen soup at the time of freezing treatment; Frozen T1 = frozen soup after 35 days of storage; Frozen T2 = frozen soup after 70 days of storage. Figure 3 Evolution of the peroxide value of the oil extracted from the tortellini. The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh tortellini (not frozen); Frozen T0 = frozen tortellini at the time of freezing treatment; Frozen T1 = frozen tortellini after 35 days of storage; Frozen T2 = frozen tortellini after 70 days of storage. Figure 4 Percentage distribution of volatile compounds in the fresh soup. Figure 5 Percentage distribution of volatile compounds in the fresh tortellini. Figure 6 Biplot of the two most significant principal components, PC1 and PC2, by a principal component analysis (PCA) of the descriptive parameters of the soup samples analyzed. NFS = fresh soup (not frozen); FS T0 = frozen soup at the time of freezing treatment; FS T1 = frozen soup after 35 days of storage; FS T2 = frozen soup after 70 days of storage. Figure 7 Biplot of the two most significant principal components, PC1 and PC2, by principal component analysis (PCA) of the descriptive parameters of the tortellini samples analyzed. NFT = fresh tortellini (not frozen); FT T0 = frozen tortellini at the time of freezing treatment; FT T1 = frozen tortellini after 35 days of storage; FT T2 = frozen tortellini after 70 days of storage. foods-12-01087-t001_Table 1 Table 1 Evolution of the texture of the tortellini *. Fresh Frozen T0 T1 T2 Peak Force A (g) 1000.3 +- 301.5 a 573.3 +- 231.2 b 611.5 +- 249.1 b 686.2 +- 254.0 b Springiness 0.8 +- 0.1 a 0.5 +- 0.2 b 0.6 +- 0.1 ab 0.5 +- 0.1 b Adhesiveness 0.3 +- 0.4 a 41.8 +- 34.7 b 4.6 +- 6.7 a 46.6 +- 29.8 b Cohesiveness 0.5 +- 0.1 ab 0.5 +- 0.1 a 0.6 +- 0.1 b 0.5 +- 0.1 ab Chewiness 408.9 +- 147.9 a 158.6 +- 136.3 b 236.0 +- 133.9 b 178.1 +- 99.0 b Gumminess 533.9 +- 172.3 a 277.0 +- 150.0 b 356.7 +- 162.7 ab 350.4 +- 127.3 ab * The results are the mean of ten determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh tortellini (not frozen); Frozen T0 = frozen tortellini at the time of freezing treatment; Frozen T1 = frozen tortellini after 35 days of storage; Frozen T2 = frozen tortellini after 70 days of storage. foods-12-01087-t002_Table 2 Table 2 Evolution of phenolic compounds and carotenoids (mg/kg) in the soup *. Fresh Frozen T0 T1 T2 b-carotene 274.9 +- 5.3 a 270.7 +- 3.6 a 267.6 +- 4.7 a 266.3 +- 7.0 a Lutein 41.5 +- 0.6 a 42.0 +- 1.3 a 40.3 +- 2.5 a 39.7 +- 1.6 a a-Tocopherol 12.8 +- 0.1 a 12.9 +- 0.3 a 12.6 +- 0.5 a 12.4 +- 0.6 a Quercetin-3-O-rutinoside 50.7 +- 1.4 a 52.5 +- 3.9 a 51.2 +- 1.8 a 49.9 +- 2.4 a Quercetin 11.3 +- 0.8 a 10.4 +- 1.5 a 10.5 +- 0.4 10.0 +- 1.3 a * The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh soup (not frozen); Frozen T0 = frozen soup at the time of freezing treatment; Frozen T1 = frozen soup after 35 days of storage; Frozen T2 = frozen soup after 70 days of storage. foods-12-01087-t003_Table 3 Table 3 Evolution of volatile compounds (mg/kg expressed as 4-methyl-2-pentanol) of the soup *. Fresh Frozen T0 T1 T2 Aldehydes Acetaldehyde 40.4 +- 0.6 a 44.4 +- 3.4 a 42.9 +- 2.2 a 44.1 +- 2.2 a Pentanal 229.0 +- 3.7 a 235.6 +- 6.6 a 230.7 +- 9.1 a 230.0 +- 12.7 a Hexanal 200.0 +- 18.0 a 192.0 +- 6.5 a 206.2 +- 11.0 a 222.0 +- 12.7 a (E)-2-Heptenal 36.7 +- 3.2 a 32.9 +- 2.4 a 33.4 +- 1.8 a 36.3 +- 2.9 a Nonanal 87.2 +- 6.3 a 87.6 +- 4.0 a 90.3 +- 6.8 a 89.5 +- 1.4 a 2,4-Decadienal 56.2 +- 3.4 a 61.1 +- 2.1 a 64.6 +- 1.0 a 68.4 +- 5.1 a Sum of aldehydes 649.5 +- 19.9 a 653.6 +- 11.1 a 668.1 +- 16.1 a 690.2 +- 19.1 a Alcohols 2-Methyl-1-butanol 8.0 +- 0.8 a 8.0 +- 0.3 a 8.2 +- 0.5 a 7.0 +- 0.7 a 1-Pentanol 116.0 +- 5.2 a 108.3 +- 4.3 a 117.1 +- 15.5 a 126.9 +- 2.1 a 1-Hexanol 142.6 +- 3.0 ab 159.5 +- 13.1 a 138.2 +- 3.6 ab 119.9 +- 1.2 b Sum of alcohols 266.5 +- 6.1 a 275.8 +- 13.8 a 263.5 +- 16.0 a 253.8 +- 2.5 a Ketones Acetoin 106.6 +- 4.4 a 111.8 +- 6.4 a 123.5 +- 18.6 a 101.6 +- 9.0 a Terpenes Limonene 258.5 +- 3.3 a 254.2 +- 9.4 a 310.7 +- 15.9 b 257.8 +- 17.5 a a-Pinene 6424.7 +- 157.7 a 6413.0 +- 128.5 a 6439.0 +- 106.9 a 6449.5 +- 117.6 a b-Pinene 1436.1 +- 50.2 a 1454.5 +- 46.5 a 1396.4 +- 121.3 a 1408.9 +- 237.9 a b-Myrcene 3302.7 +- 33.3 a 3326.1 +- 54.4 a 3429.1 +- 8.7 a 3300.5 +- 46.2 a g-Terpinene 1243.7 +- 14.2 a 1228.3 +- 96.6 a 1227.3 +- 46.9 a 1205.0 +- 77.8 a Caryophyllene 652.0 +- 11.4 a 667.1 +- 2.5 a 646.5 +- 43.7 a 674.1 +- 23.0 a Sum of terpenes 13,317.7 +- 169.8 a 13,343.2 +- 176.3 a 13,449.1 +- 174.9 a 13,295.9 +- 281.9 a Sulphur compounds Dimethyl sulfide 97.4 +- 3.4 a 102.9 +- 6.7 a 99.9 +- 2.5 a 110.1 +- 7.4 a Dipropyl disulfide 40.9 +- 2.5 a 43.1 +- 3.0 a 41.2 +- 2.2 a 50.7 +- 3.9 a Sum of sulphur compounds 138.3 +- 4.2 a 146.0 +- 7.4 a 141.0 +- 3.3 a 160.8 +- 8.3 a Furans Furfural 69.5 +- 4.5 a 70.6 +- 4.0 a 66.9 +- 0.0 a 75.8 +- 7.6 a 2-Pentyl-furan 304.4 +- 18.8 a 299.0 +- 12.8 a 399.3 +- 24.4 b 360.5 +- 28.6 ab Sum of the furans 373.9 +- 20.3 a 369.6 +- 17.0 a 466.1 +- 24.8 a 436.3 +- 31.9 a * The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh soup (not frozen); Frozen T0 = frozen soup at the time of freezing treatment; Frozen T1 = frozen soup after 35 days of storage; Frozen T2 = frozen soup after 70 days of storage. foods-12-01087-t004_Table 4 Table 4 Evolution of volatile compounds (mg/kg expressed as 4-methyl-2-pentanol) of the tortellini *. Fresh Frozen T0 T1 T2 Aldehydes Acetaldehyde 34.3 +- 3.3 a 32.2 +- 3.3 a 29.2 +- 2.3 a 30.6 +- 3.4 a Pentanal 72.1 +- 6.4 a 69.5 +- 6.7 a 77.3 +- 0.8 a 80.7 +- 7.5 a Hexanal 209.2 +- 4.1 a 198.8 +- 10.8 a 219.7 +- 4.4 a 230.6 +- 10.3 a (E)-2-Heptenal 3.3 +- 0.3 a 3.9 +- 0.3 a 4.0 +- 0.7 a 4.7 +- 0.1 a Nonanal 34.9 +- 0.2 a 36.4 +- 4.2 a 38.4 +- 0.5 a 40.5 +- 3.7 a 2,4-Decadienal 2.8 +- 0.3 a 3.2 +- 0.3 a 3.4 +- 0.1 a 3.6 +- 0.2 a Sum of aldehydes 356.6 +- 8.3 ab 344.0 +- 13.7 b 372.1 +- 5.1 ab 390.6 +- 13.7 a Alcohols 1-Pentanol 45.7 +- 2.0 a 47.9 +- 2.2 a 43.5 +- 2.9 a 40.6 +- 2.9 a 1-Hexanol 147.1 +- 6.3 a 153.0 +- 2.4 a 155.2 +- 6.4 a 142.1 +- 1.8 a Sum of alcohols 192.8 +- 6.6 a 200.9 +- 3.3 a 198.7 +- 7.0 a 182.7 +- 3.4 a Ketones Acetoin 159.5 +- 15.9 a 171.7 +- 16.3 a 186.9 +- 15.5 a 184.7 +- 7.8 a 2-Pentanone 474.8 +- 41.1 a 482.4 +- 30.2 a 474.4 +- 20.0 a 486.0 +- 22.5 a 2-Heptanone 896.1 +- 34.9 a 864.9 +- 22.0 a 898.1 +- 7.3 a 900.0 +- 19.3 a 2-Nonanone 241.6 +- 7.5 a 251.7 +- 11.7 a 262.6 +- 20.6 a 260.4 +- 12.5 a Sum of ketones 1772.0 +- 56.7 a 1770.6 +- 42.4 a 1822.0 +- 33.4 a 1831.1 +- 33.1 a Terpenes Limonene 2515.1 +- 106.0 a 2520.9 +- 29.7 a 2509.5 +- 50.3 a 2560.1 +- 53.0 a a-Pinene 14,445.0 +- 492.5 a 14,418.2 +- 555.6 a 14,428.0 +- 354.5 a 14,537.1 +- 445.6 a b-Pinene 2985.8 +- 77.5 a 2956.1 +- 91.3 ab 2870.2 +- 17.5 ab 2836.7 +- 12.1 b Camphene 291.1 +- 15.5 a 303.8 +- 17.6 a 309.7 +- 20.9 a 299.5 +- 22.7 a b-Myrcene 1357.7 +- 30.0 a 1290.5 +- 6.5 a 1292.3 +- 85.4 a 1255.1 +- 61.4 a a-Phellandrene 699.8 +- 3.8 a 705.8 +- 9.7 a 722.2 +- 66.2 a 729.0 +- 33.9 a b-Phellandrene 3093.9 +- 175.0 a 2978.9 +- 61.4 a 3077.7 +- 67.6 a 3104.9 +- 38.6 a g-Terpinene 3467.4 +- 231.0 a 3451.8 +- 65.1 a 3360.6 +- 174.2 a 3253.4 +- 132.9 a Linalool 240.1 +- 8.7 a 244.1 +- 7.5 a 236.0 +- 11.2 a 222.0 +- 14.5 a Sum of terpenes 29,095.9 +- 587.4 a 28,870.0 +- 571.3 a 28,806.2 +- 419.1 a 28,797.8 +- 475.7 a Organic acids Acetic acid 46.7 +- 3.9 a 40.9 +- 2.6 a 47.7 +- 1.4 a 45.1 +- 3.4 a Butanoic acid 41.4 +- 3.7 a 36.7 +- 2.9 a 43.8 +- 0.4 a 42.3 +- 4.7 a Pentanoic acid 50.5 +- 3.2 a 47.9 +- 4.1 a 50.6 +- 3.3 a 55.7 +- 4.2 a Sum of organic acids 138.6 +- 6.3 a 125.5 +- 5.7 a 142.2 +- 3.6 a 143.2 +- 7.2 a * The results are the mean of two determinations +- the standard deviation. The comparison between the different storage times was carried out by one-way ANOVA. Different lowercase letters indicate a statistically significant difference (p < 0.05). Fresh = fresh tortellini (not frozen); Frozen T0 = frozen tortellini at the time of freezing treatment; Frozen T1 = frozen tortellini after 35 days of storage; Frozen T2 = frozen tortellini after 70 days of storage. foods-12-01087-t005_Table 5 Table 5 Results of the triangle test performed on frozen soup and tortellini samples at the time of freezing treatment (FS T0 and FT T0) compared to fresh ones (NFS and NFT), and the maximum number of correct responses required (values extracted from ISO 4120:2021). 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PMC10000527 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050722 cells-12-00722 Review Role of Astrocytes in the Pathophysiology of Lafora Disease and Other Glycogen Storage Disorders Duran Jordi 123 Brenner Michael Academic Editor Parpura Vladimir Academic Editor 1 Institut Quimic de Sarria (IQS), Universitat Ramon Llull (URL), 08017 Barcelona, Spain; [email protected] 2 Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain 3 Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain 24 2 2023 3 2023 12 5 72214 12 2022 05 2 2023 22 2 2023 (c) 2023 by the author. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Lafora disease is a rare disorder caused by loss of function mutations in either the EPM2A or NHLRC1 gene. The initial symptoms of this condition are most commonly epileptic seizures, but the disease progresses rapidly with dementia, neuropsychiatric symptoms, and cognitive deterioration and has a fatal outcome within 5-10 years after onset. The hallmark of the disease is the accumulation of poorly branched glycogen in the form of aggregates known as Lafora bodies in the brain and other tissues. Several reports have demonstrated that the accumulation of this abnormal glycogen underlies all the pathologic traits of the disease. For decades, Lafora bodies were thought to accumulate exclusively in neurons. However, it was recently identified that most of these glycogen aggregates are present in astrocytes. Importantly, astrocytic Lafora bodies have been shown to contribute to pathology in Lafora disease. These results identify a primary role of astrocytes in the pathophysiology of Lafora disease and have important implications for other conditions in which glycogen abnormally accumulates in astrocytes, such as Adult Polyglucosan Body disease and the buildup of Corpora amylacea in aged brains. glycogen aggregation Lafora disease neuroinflammation neurodegeneration epilepsy Spanish Ministerio de Ciencia e Innovacion (MCIU/FEDER/AEI)PID2020-118699GB-I00 National Institutes of Health (NIH-NINDS)NS097197-05S1P01 Spanish Ministry of Economy (MINECO)JD's laboratory is funded by grants from the Spanish Ministerio de Ciencia e Innovacion (MCIU/FEDER/AEI) (PID2020-118699GB-I00) and the National Institutes of Health (NIH-NINDS) (NS097197-05S1P01). IRB Barcelona anb IBEC are the recipients of a Severo Ochoa Award of Excellence from the Spanish Ministry of Economy (MINECO). pmc1. Brain Glycogen Cells store glucose in the form of glycogen--a branched polymer of glucose--to minimize the increase in osmotic pressure that would be associated with the accumulation of free glucose. Glycogen molecules can store up to 55,000 glucose units in a water-soluble form that can be rapidly degraded when energy is required. This polysaccharide is synthesized through the coordinated action of glycogen synthase (GS), which joins glucose units by a-1,4-glycosidic linkages, and glycogen branching enzyme (GBE), which introduces branching points via a-1,6-glycosidic linkages . Similarly, glycogen is broken down by the coordinated action of glycogen phosphorylase and glycogen debranching enzyme, which digest a-1, a-1,6-glycosidic linkages, respectively. In normal glycogen, branches are introduced at even intervals and this branched structure is important for its function and solubility, generating a spherical molecule that can be rapidly degraded when the cell needs glucose. In contrast, in poorly branched glycogen, long a-1,4 linked glucose chains can form single or double helices that exclude water, thereby impeding the degradation of glycogen and decreasing its solubility. Some tissues, such as skeletal muscle and particularly the liver, accumulate high amounts of glycogen (up to 2% and 8% of wet weight, respectively) . Muscle glycogen provides energy for contraction during intense exercise, while liver glycogen is mobilized during fasting periods to produce glucose, which is then released into the blood to be used by the rest of the body. All other tissues and cell types contain glycogen, although at lower concentrations than those found in the liver and skeletal muscle. Within the brain, glycogen concentration is relatively low--about 0.1% of wet weight--and it is present mostly in astrocytes . However, neurons also have an active glycogen metabolism that plays an essential role in the function of these cells . Given the low concentration of glycogen in the brain, its role in this organ was traditionally overlooked and widely presumed to serve as an emergency reservoir for pathophysiological conditions like hypoglycemia or ischemia . However, it is now clear that glycogen plays key roles in the normal functioning of the brain under physiological conditions . Brain glycogen is mobilized as supplemental fuel when energy needs increase due to neuronal activity , and substantial deficits in learning and memory arise when its use is blocked . To support neuronal function, and according to the astrocyte-neuron lactate shuttle hypothesis, astrocytes degrade glycogen to generate lactate, which they then release and which is taken up and oxidized by neurons . Another simpler hypothesis is that, in situations of high-energy demand, astrocytes use glucose obtained from their own glycogen store, thereby sparing interstitial glucose for neurons . 2. Lafora Disease Despite the key physiological role of glycogen, this polysaccharide can also participate in brain pathology. In some conditions, glycogen abnormally accumulates in the nervous tissue. Lafora disease (LD, OMIM 254780) is probably the most striking example of the consequences of the abnormal buildup of glycogen in the brain. In LD, poorly branched glycogen accumulates in the brain and other tissues in the form of aggregates known as Lafora bodies (LBs). Glycogen in LBs is not accessible to glycogen phosphorylase and glycogen debranching enzyme. Thus, it cannot be degraded and progressively accumulates. Glycogen in LBs also contains high levels of covalently bound phosphate, which had been hypothesized to participate in glycogen insolubility in LD . However, it seems now clear that abnormal glycogen branching, not hyperphosphorylation, underlies glycogen insolubility in LD . In addition to poorly branched, hyperphosphorylated glycogen, LBs contain several proteins, including GS, ubiquitin, and the autophagy adaptor p62 . The onset of LD occurs in adolescence, in previously healthy children, normally in the form of epileptic seizures that are difficult to distinguish from idiopathic generalized epilepsies. Seizures escalate over time, together with a rapid decline in cognitive function. The patient develops severe dementia and eventually enters a vegetative state with continuous seizures. Death invariably comes 5 to 10 years after the onset as a consequence of status epilepticus or complications derived from neurodegeneration . LD is a rare disease with an estimated prevalence of ~4 cases per million individuals in the world . However, the number of undiagnosed cases might be higher, particularly in developing countries. Current treatment remains palliative, with limited success in the modulation of symptoms. LD is an autosomal recessive disease caused by mutations in two genes: EPM2A, encoding laforin, a dual phosphatase that contains a carbohydrate-binding domain , and EPM2B/NHLRC1, encoding malin, an E3-ubiquitin ligase . Mutations in either of these genes cause an indistinguishable disease. The exact roles of malin and laforin in glycogen metabolism are not yet fully understood, but it is widely accepted that malin uses laforin as a scaffold to bind to glycogen and ubiquitinate proteins involved in glycogen metabolism . The accumulation of poorly branched glycogen in LD suggests that malin and laforin form this functional complex to regulate glycogen synthesis and prevent glycogen insolubility . To minimize the toxic consequences of the accumulation of poorly branched glycogen, proteins like the autophagy adaptor p62 promote its compaction in the form of LBs . This protective mechanism is reminiscent of the condensation of ubiquitinated, misfolded proteins into larger structures to be degraded by autophagy . To study LD, several mouse models of the disease lacking laforin or malin have been generated . These animals present similar pathophysiological phenotypes that recapitulate the human disease; i.e., they accumulate LBs in several tissues, including the brain, show a progressive neuronal loss, behavioral impairments, neuroinflammation with reactive astrocytes and microglia, altered autophagy, and increased susceptibility to epileptogenic drugs such as kainate and pentylenetetrazole . In these LD models, the accumulation of LBs increases with age and the pathological phenotypes also worsen progressively as the animals age . The role of LBs in the pathophysiology of LD has been unclear for many years. For instance, it was hypothesized that the primary cause of LD was an impairment in autophagy and that the accumulation of LBs was a consequence of this defect . However, several groups, including ours, took advantage of mouse models of LD to demonstrate that excess glycogen underlies the pathology of this disease. Indeed, impeding or reducing glycogen synthesis in laforin-deficient mice prevents LB formation and prevents all the pathologic traits of the disease . These models also showed that autophagy impairment is secondary to LB accumulation since autophagy markers are also normalized when glycogen accumulation is prevented . Furthermore, we also used Drosophila and mouse models to demonstrate that forced accumulation of glycogen in neurons induces their death by apoptosis . All these findings identified excessive glycogen accumulation as an inducer of neurodegeneration, and glycogen synthesis therefore became a putative target for the treatment of LD. Therapies based on the inhibition of glycogen synthesis are the focus of current research efforts . 3. Lafora Bodies in Neurons and Astrocytes In the first description of LD in 1911, Dr. Gonzalo Rodriguez-Lafora reported the presence of LBs in neurons . Until recently, it was widely believed that LBs accumulated exclusively in this cell type, and thus, all the pathologic traits of the disease were attributed to the toxic effects of neuronal LBs . However, the premise that LBs are present exclusively in this cell population was inconsistent with the fact that, as mentioned before, brain glycogen is present mainly in astrocytes in normal conditions. It is now clear that LBs also accumulate in astrocytes. In 2011, we first reported the presence of LBs in these cells in a malin-deficient mouse model , but the significance of this discovery was underestimated. Several years later, we and others demonstrated that most LBs are present in astrocytes, particularly in regions like the hippocampus. We classified these bodies into neuronal (nLBs), and Corpora amylacea-like (CAL), the latter present in astrocytes, which were named this way because of their resemblance to Corpora amylacea, which are glycogen aggregates that accumulate in aged brains (see below). Interestingly, CAL and nLBs differ not only in the cell type in which they accumulate but also in their shape and subcellular localization. CAL are polymorphic and present predominantly in astrocytic processes, and they show a patchy distribution, each patch corresponding to an individual astrocyte. In contrast, nLBs are normally present in the form of a single spherical aggregate close to the neuronal nucleus, and they resemble inclusion bodies formed by protein aggregates such as Lewy bodies . The progressive accumulation of CAL and nLBs takes place in parallel, and both types of LB are already present at early stages in mouse models of LD . Astrocytes have been shown to have phagocytic activity and can engulf apoptotic cells . Thus, LBs present in astrocytes might not have originated in astrocytes themselves, but instead, they may have a neuronal origin; i.e., proceeding from the phagocytosis of an apoptotic body derived from a dead neuron. To decipher the origin of astrocytic LBs, as well as to understand their contribution to the pathology of LD, we generated a malin-deficient mouse in which GS was specifically deleted from astrocytes (malinKO + GSGfap-KO mice), thus preventing the synthesis of glycogen specifically in this cell type. The brains of these animals contained nLBs but were devoid of CAL, thereby unequivocally demonstrating that the latter originate in astrocytes . 4. Role of Astrocytic LBs in the Pathophysiology of LD The demonstration that LBs are also present in astrocytes opened up the possibility that these astrocytic LBs contribute to the pathology of LD. In fact, the quantification of CAL and nLBs showed that in brain regions like the hippocampus, CAL are clearly predominant over nLBs . The analysis of malinKO+GSGfap-KO brains confirmed this quantification since the hippocampi of these mice are largely free of LBs . Furthermore, RNA-Seq studies indicated that most of the upregulated genes in the brains of laforin-deficient mice encode pro-inflammatory mediators and that reactive glia, including astrocytes, are responsible for the expression of these inflammatory genes . To understand the contribution of astrocytic LBs to the pathology of LD, the characteristic pathologic traits of the disease were analyzed in malinKO + GSGfap-KO mice. Neuroinflammation is considered one of the initial determinants of LD . The brains of LD mouse models present clear astrogliosis, microgliosis, and increased expression of inflammatory genes . In contrast, the analysis of malinKO + GSGfap-KO brains revealed normal levels of all these markers of neuroinflammation, thereby indicating that astrocytic LBs underlie neuroinflammation in LD . The link between the excessive accumulation of astrocytic glycogen and neuroinflammation was further confirmed with another mouse model in which a constitutively active form of GS was expressed specifically in astrocytes. These mice, which accumulate high amounts of glycogen in astrocytes, present profound astrogliosis and microgliosis, as well as a marked increase in the expression of inflammatory genes . These results confirmed that the excessive accumulation of glycogen in astrocytes induces neuroinflammation. However, the mechanism that links excessive astrocytic glycogen accumulation with neuroinflammation is currently unknown and is the focus of current research efforts. As mentioned before, the initial symptom of LD is most commonly the presence of epileptic seizures, which worsen progressively with age. Animal models of LD reproduce this pathologic trait of the disease in the form of increased susceptibility to epileptogenic drugs like kainic acid. Astrocytes play essential roles in brain function, including the regulation of extracellular potassium and glutamate homeostasis, thus making them crucial actors in epilepsy . In this regard, astrocytic glycogen has been shown to fuel potassium uptake into astrocytes, since the astrocytic sodium/potassium pump uses ATP obtained from glucose 6-phosphate originating from glycogen breakdown . The non-clearance of extracellular potassium would result in neuronal hypersynchronization and burst firing, which would result in seizure generation and propagation. Thus, it has been suggested that alterations in glycogen metabolism contribute to the imbalance of glutamatergic and GABAergic neurotransmission associated with epileptic seizures . Accordingly, it was reasonable to hypothesize that the impairment of astrocytic glycogen metabolism in LD compromises potassium uptake, which would increase excitability and thus be responsible for the epileptic phenotype of the disease. In line with this hypothesis, the presence of glycogen aggregates in astrocytes has also been described in patients with temporal lobe epilepsy . Surprisingly, malinKO + GSGfap-KO mice do not show a significant amelioration of susceptibility to epilepsy , thereby indicating that astrocytic glycogen accumulation is not the main factor responsible for the epileptic phenotype of LD. Importantly, the deletion of GS specifically in astrocytes does not increase susceptibility to epilepsy per se . Thus, the epileptic phenotype of LD might be attributable to neuronal LBs, most likely to those present in GABAergic interneurons, which would impair their function and generate an imbalance of glutamatergic and GABAergic transmission. In line with this notion, we described that parvalbumin interneurons of the hippocampus accumulate LBs and this buildup is accompanied by damage to GABAergic neurons in mouse models of LD . In summary, astrocytic glycogen accumulation drives the neuroinflammatory phenotype of LD but not the increased susceptibility to epilepsy, which might be attributable to neuronal LBs. 5. Corpora amylacea The accumulation of glycogen in the nervous tissue is not exclusive to LD. As mentioned before, the presence of glycogen aggregates known as Corpora amylacea ("starch bodies" in Latin, due to their resemblance to starch) has also been observed in aged human brains . Interestingly, these aggregates accumulate to a greater extent in neurodegenerative conditions like Alzheimer's, Parkinson's, Huntington's, and Pick's diseases, as well as in patients with temporal lobe epilepsy . Although the cellular localization of Corpora amylacea has been a source of debate, several articles have described their presence in astrocytes . Similar aggregates progressively accumulate with age in the astrocytes of control mice . The composition of Corpora amylacea greatly resembles that of LBs, consisting of insoluble, poorly branched glycogen and a minor content of protein, including GS, ubiquitin, and p62 . Interestingly, these glycogen aggregates are not found in the brains of aged GS knockout mice . This observation thus indicates that, as for LBs, glycogen synthesis is a prerequisite for the formation of Corpora amylacea. In contrast, the formation of these aggregates is enhanced in models of accelerated aging, such as the Senescence Accelerated Mouse-Prone 8 (SAMP8) mouse . The overexpression of protein targeting to glycogen (PTG), an activator of GS, also resulted in an increase in the formation of these glycogen aggregates . This observation suggests that an imbalance between GS activity and GBE activity favors the formation of poorly branched glycogen, which would accumulate in the form of Corpora amylacea-like structures (see adult polyglucosan body disease below). Strikingly, the brains of control, SAMP8, and PTG-overexpressing animals show the presence of CAL but not nLBs . Therefore, the latter seem to be exclusive to LD models. Collectively, all of points explained above suggest that the progressive accumulation of Corpora amylacea in the nervous system contributes to the neurological decline associated with aging . Mutations in malin and laforin would drastically increase the rate of this process; i.e., LD could be considered an accelerated aging process with respect to the consequences of glycogen accumulation in the brain. Furthermore, the increased presence of Corpora amylacea in neurodegenerative conditions like Alzheimer's and Parkinson's disease opens up the possibility that the toxicity induced by glycogen accumulation also participates in the pathology of these disorders. Alternatively, the presence of waste elements in Corpora amylacea has led some authors to hypothesize that these structures are waste containers in which deleterious or residual products are isolated for later removal by the natural immune system . 6. Adult Polyglucosan Body Disease Another rare genetic condition in which glycogen accumulates abnormally in the nervous tissue is adult polyglucosan body disease (APBD, OMIM 263570). This is an autosomal recessive neurodegenerative disorder with onset normally in the 5th or 6th decade of life and slow progression, affecting the central and peripheral nervous system with severe leukodystrophy, atrophy of the spine and medulla, and cognitive impairment . The disease is caused by mutations in GBE that result in the formation of glycogen with low solubility due to the lack of branching. Consequently, there is a progressive intracellular accumulation of glycogen aggregates (the so-called polyglucosan bodies), which are similar to LBs. In fact, the term "polyglucosan body" is also used to refer to LBs and Corpora amylacea APBD is caused by mutations that generate a partial loss of GBE activity (with 5-20% residual activity), the most common of which is p.Y329S, found in patients of Ashkenazi Jewish descent . Other mutations in GBE cause a clinically heterogeneous disorder collectively known as glycogen storage disease IV (OMIM 232500), with hepatic and neuromuscular presentations . A mouse model with the GBE mutation p.Y329S presents a phenotype that is reminiscent of APBD in humans, with the accumulation of polyglucosan bodies and neurological dysfunction . This model has allowed researchers to demonstrate that, like LD, APBD can be rescued by inhibiting GS , again evidencing the role of glycogen accumulation in the etiopathogeny of neurodegeneration. In this regard, strategies targeting glycogen synthesis have proven effective in mouse models of both LD and APBD . Similarly to LD, polyglucosan bodies have been reported to accumulate in astrocytes and neurons in APBD . The exact contribution of astrocytic polyglucosan bodies to the pathophysiology of this disease is not clear. To unequivocally dissect this contribution, GS should be ablated specifically in astrocytes in the APBD mouse model, in a similar fashion as malinKO + GSGfap-KO mice for LD . However, after all of the considerations above, it is reasonable to hypothesize that astrocytic polyglucosan bodies participate in the pathophysiology of APBD, probably by inducing neuroinflammation in a similar fashion as LBs in LD. In fact, the presence of polyglucosan bodies in astrocytes is sufficient to cause APBD . 7. RBCK1 Deficiency RANBP2-Type and C3HC4-Type Zinc Finger Containing 1 protein (RBCK1, also known as HOIL1) is another E3 ubiquitin ligase that is related to glycogen metabolism. Mutations in the RBCK1 gene result in polyglucosan body myopathy with or without immunodeficiency (OMIM 615895). This disease affects children, and courses with progressive proximal muscle weakness and dilated cardiomyopathy, accompanied in some cases by severe immunodeficiency and a hyperinflammatory state . The muscle and the heart of these patients show extensive polyglucosan body accumulation . Although the disease is primarily a skeletal and cardiac myopathy, a mouse model of this condition also shows the presence of profuse aggregates of poorly branched glycogen in the nervous tissue, especially in the hippocampus, cerebellum, and spinal cord . Interestingly, these polyglucosan bodies are localized mainly in astrocytes, and this accumulation is accompanied by astrogliosis and microgliosis, again linking neuroinflammation to the excessive accumulation of glycogen in astrocytes . These observations indicate that the accumulation of polyglucosan bodies in the nervous tissue might also play a role in the pathophysiology of human RBCK1 deficiency. As with LD and APBD, the inhibition of glycogen synthesis rescues the pathological traits of the mouse model of RBCK1 deficiency, once again demonstrating that glycogen synthesis is a prerequisite for the formation of the polyglucosan bodies that underlie the disease . Of note, a recent report has shown that the substrate of RBCK1 ubiquitination is not a protein but glycogen itself. More specifically, RBCK1 targets unbranched glucosaccharides, participating in a mechanism aimed at preventing polyglucosan body accumulation . Thus, different E3 ubiquitin ligases (malin and RBCK1) are involved in preventing abnormal glycogen accumulation. Interestingly, ubiquitin is present in glycogen aggregates both in the absence of malin and of RBCK1 . The genuine substrate of malin is still not clear, but the restoration of malin expression in a malin-deficient mouse model results in the degradation of the accumulated GS and laforin , thereby indicating that these two proteins are targets of malin ubiquitination. These experiments also showed that, once LBs have accumulated in the CNS, malin restoration is not able to promote their removal. This observation thus indicates that the role of malin is related to preventing the accumulation of abnormal glycogen rather than eliminating it after its accumulation. 8. Concluding Remarks Comparison of the pathology of LD, APBD, and RBCK1 deficiency opens up a number of questions. Why do LD and RBCK1 deficiency affect children while APBD affects adults? Why are the neurological presentations so different between the three diseases? Do LBs, Corpora amylacea and the polyglucosan bodies that accumulate in APBD have any distinguishing features amongst them that would offer insights into the differences among glycogen storage diseases? The observation that APBD patients do not present epilepsy reinforces the idea that the epileptic phenotype of LD is due to the accumulation of LBs in GABAergic interneurons. But then, if the malin-laforin complex, GBE, and RBCK1 are all important to prevent the accumulation of abnormal glycogen, why does the lack of one or the other result in the accumulation of polyglucosan bodies with different cell type-specificity? Over recent years, the role of astrocytic dysfunction in neurodegenerative diseases previously thought to have an exclusively neuronal origin is becoming apparent. LD is not only an example of such diseases but also one in which the pathology is due in part to a defect originated primarily in astrocytes. In conclusion, the study of LD has allowed the identification of the toxic consequences of the excessive accumulation of glycogen in astrocytes, a process that plays a key role in the pathophysiology of LD. This pathologic mechanism might have important implications for other conditions in which glycogen abnormally accumulates in astrocytes, such as in other rare conditions like APBD and RBCK1 deficiency, and more common neurodegenerative conditions like Alzheimer's, Parkinson's, Huntington's, and Pick's diseases, or even during normal aging. Further research is needed to understand the molecular mechanisms that link excess glycogen in astrocytes with neuroinflammation. Acknowledgments We thank Tanya Yates for correcting the manuscript. Conflicts of Interest The author declares no conflict of interest. Figure 1 Brain glycogen metabolism in normal conditions and in LD. In normal conditions, malin and laforin prevent the accumulation of poorly branched glycogen that is generated as a side product of glycogen metabolism. In LD, due to the absence of malin or laforin, poorly branched glycogen accumulates in astrocytes and neurons. Proteins like the autophagy adaptor p62 promote its aggregation in the form of LBs to minimize the toxic consequences of its accumulation. Figure 2 Accumulation of glycogen aggregates in neurons and astrocytes and neuroinflammation in mouse models of LD. GS, glial fibrillary acidic protein (Gfap) and ionized calcium-binding adapter molecule 1 (Iba1) immunostainings of mouse hippocampi are shown. GS immunostaining reveals the presence of few CAL aggregates in control mice. 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PMC10000528 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050861 diagnostics-13-00861 Review Metabolomics: A New Era in the Diagnosis or Prognosis of B-Cell Non-Hodgkin's Lymphoma Alfaifi Abdullah 12 Refai Mohammed Y. 3 Alsaadi Mohammed 14 Bahashwan Salem 456 Malhan Hafiz 7 Al-Kahiry Waiel 7 Dammag Enas 7 Ageel Ageel 7 Mahzary Amjed 8 Albiheyri Raed 1 Almehdar Hussein 1 Qadri Ishtiaq 1* Sartaj Sohrab Sayed Academic Editor 1 Department of Biological Science, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia 2 Fayfa General Hospital, Ministry of Health, Jazan 83581, Saudi Arabia 3 Department of Biochemistry, College of Science, University of Jeddah, Jeddah 21493, Saudi Arabia 4 Hematology Research Unit, King Fahad Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia 5 Department of Hematology, Faculty of Medicine, King Abdulaziz University, Jeddah 21589, Saudi Arabia 6 King Abdulaziz University Hospital, King Abdulaziz University, Jeddah 21589, Saudi Arabia 7 Prince Mohammed Bin Nasser Hospital, Ministry of Health, Jazan 82943, Saudi Arabia 8 Eradah Hospital, Ministry of Health, Jazan 82943, Saudi Arabia * Correspondence: [email protected] 23 2 2023 3 2023 13 5 86120 1 2023 19 2 2023 22 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). A wide range of histological as well as clinical properties are exhibited by B-cell non-Hodgkin's lymphomas. These properties could make the diagnostics process complicated. The diagnosis of lymphomas at an initial stage is essential because early remedial actions taken against destructive subtypes are commonly deliberated as successful and restorative. Therefore, better protective action is needed to improve the condition of those patients who are extensively affected by cancer when diagnosed for the first time. The development of new and efficient methods for early detection of cancer has become crucial nowadays. Biomarkers are urgently needed for diagnosing B-cell non-Hodgkin's lymphoma and assessing the severity of the disease and its prognosis. New possibilities are now open for diagnosing cancer with the help of metabolomics. The study of all the metabolites synthesised in the human body is called "metabolomics." A patient's phenotype is directly linked with metabolomics, which can help in providing some clinically beneficial biomarkers and is applied in the diagnostics of B-cell non-Hodgkin's lymphoma. In cancer research, it can analyse the cancerous metabolome to identify the metabolic biomarkers. This review provides an understanding of B-cell non-Hodgkin's lymphoma metabolism and its applications in medical diagnostics. A description of the workflow based on metabolomics is also provided, along with the benefits and drawbacks of various techniques. The use of predictive metabolic biomarkers for the diagnosis and prognosis of B-cell non-Hodgkin's lymphoma is also explored. Thus, we can say that abnormalities related to metabolic processes can occur in a vast range of B-cell non-Hodgkin's lymphomas. The metabolic biomarkers could only be discovered and identified as innovative therapeutic objects if we explored and researched them. In the near future, the innovations involving metabolomics could prove fruitful for predicting outcomes and bringing out novel remedial approaches. metabolomics B-cell non-Hodgkin's lymphoma biomarkers metabolites early diagnosis therapeutic This research received no external funding. pmc1. Introduction B-cell non-Hodgkin's lymphomas (B-NHLs) are a genetically, metabolically, and clinically heterogeneous group of neoplasms, with most emerging from B lymphocytes in the germinal centre (GC). B-NHLs account for approximately 90% of all non-Hodgkin's lymphomas . Diffuse large B-cell lymphomas (DLBCLs), follicular lymphoma (FL), Burkitt lymphoma (BL), and B-cell chronic lymphocytic leukaemia/small lymphocytic lymphoma (CLL/SLL) are typical B-NHL subtypes . Myc amplification and metabolic heterogeneity in B-NHL are important biologically because they influence therapy responses and can predict clinical outcomes . As cells are driven to grow, proliferate, or die, their metabolic needs fluctuate, and it is essential that cellular metabolism correspond to these needs . B-cell lymphoma and cancer cells have dysregulated metabolisms that promote uncontrolled proliferation . This altered metabolism leads to metabolic phenotypes that can be utilised for earlier cancer detection and/or therapy response biomarkers . Fluorodeoxyglucose-PET imaging is an essential tool for the management of many malignancies, including B-cell lymphomas . Other metabolites in biological samples have been in the limelight for diagnosis, monitoring, and therapy . Metabolomics is a comprehensive evaluation of both qualitative and quantitative parameters of all the metabolites present in cells, tissues, and bodily fluids, which can reveal crucial information about the cancer state that would not be obvious otherwise. Metabolomics-based diagnosis investigates the metabolites present in the human body and how they react under stress conditions, like various diseases and disorders . Metabolomics is a powerful tool that can identify cancer biomarkers and drivers of tumorigenesis. An example includes the de novo synthesis of phospholipid compounds in malignant tissues, which increases at the time of the progression of the tumour . Worthy, LDH-A was the first metabolic target demonstrated to be directly regulated by an oncogene (MYC), and genetic or pharmacologic inhibition of LDH-A diminishes MYC-dependent tumours . Even now, it is a challenging task to detect and treat the lymphoma at an initial stage. This review provides an overview of existing and future metabolomics prospects to improve B-cell non-Hodgkin's lymphoma diagnosis, monitoring, and treatment. First, we review B-cell non-Hodgkin's lymphoma metabolism. We then introduce general metabolomics techniques, including their analytical advantages and disadvantages. In the final section, we present instances where metabolomics has been employed in the clinical and research areas as a way to lead prospective future applications for the prognosis and diagnosis of B-cell non-Hodgkin's lymphoma. In practice, metabolomics has been widely covered. For more information on best practises in metabolomics analysis, the reader is referred to other excellent reviews cited throughout this article. 2. Metabolism in B-Cell Non-Hodgkin's Lymphoma (B-NHL) Cell metabolism is a well-defined set of metabolic activities that generate and store energy equivalents, maintain redox homeostasis, synthesise biologically active macromolecules, and eliminate organic waste . Catabolism breaks down carbon sources into simpler intermediates, which are then employed as building blocks in the production of lipids, amino acids, carbohydrates, and nucleotides (anabolism) . Tumour cells are able to survive, grow, and divide because of their metabolic versatility and plasticity, which allow them to produce ATP as an energy source while maintaining the reduction-oxidation (redox) balance and devoting resources to biosynthesis . Recent sequencing approaches have not discovered significant metabolic genes as direct lymphoma driver mutations . Metabolic alterations in B-NHL are characterised by the production of enough energy and maintenance of anabolism for survival, growth, and division in the face of low levels of nutrients and oxygen (such as HIF1 and MYC), deregulation of metabolic regulators (like mTORC1), and rewiring of metabolic pathways (e.g., BCR signalling) . The Warburg effect promotes aerobic glycolysis over aerobic oxidation , and this is supported by HIF1-alpha and MYC. This leads to the production of lactate and poor producing ATP, but helps create biomass. As a result, the body's reaction to hypoxia-induced metabolic abnormalities may promote anabolism in GC-derived B-cell lymphoma . MYC oncogene aberrations, including translocations or overexpression, are characteristics of B-cell lymphoma aetiology . B-cell lymphomas require higher MYC levels to maintain their rapid proliferation rate. MYC upregulates nucleoside metabolism, which is essential for cell development. Glutamine metabolism is similarly regulated by MYC expression . Glucose uptake, glycolysis, and lipid biosynthesis are all controlled by MYC as well . On the other hand, alpha-ketoglutarate (aKG) synthesis can be inhibited by hypoxia and mitochondrial dysfunction, which in turn reduces the activity of aKG-dependent enzymes, leading to increased DNA and histone hypermethylation and stabilisation of HIF1a. HIF1a is the primary transcriptional regulator of the adaptive response to hypoxia and is constitutively stabilised in a significant proportion of DLBCLs and FLs . HIF1a and MYC promote anaerobic glycolysis by activating genes for glucose transporter (GLUT), hexokinase (HK), monocarboxylate transporter (MTC), pyruvate dehydrogenase (PDK), phosphofructokinase (PFK), phosphoglycerate kinase (PGK), pyruvate kinase (PK), and lactate dehydrogenase (LDHA) . mTORC1 is essential for generating metabolic precursors via the tricarboxylic acid cycle (TCA) and stimulating cellular proliferation. Activation of mTORC1 thereby enhances the survival of B-cell lymphoma. T-cell-selected GC B cells in the light zone necessitate mTORC1 activation in order to proliferate and mutate in the dark zone. mTORC1 may be aberrantly activated in GCB-DLBCL through activating mutations of PI3K/Akt/mTOR pathway genes . A further marker of B-cell lymphoma is altered B-cell receptor (BCR) signalling, which is essential for the maintenance and creation of both healthy and malignant B cells . PI3K/AKT/mTORC1 is one of the BCR signalling pathway's downstream branches. PI3K regulates glycolysis and energy generation, and consequent AKT signalling influences the cellular metabolome. AKT promotes glucose uptake and glycolysis by increasing the expression and translocation of GLUT1 and glycolytic enzymes, including hexokinase (HK) expression and activation . In a subset of DLBCL and MCL, PTEN mutations lead to AKT/mTORC1 pathway gene expression . RagC mutations in FL enhance mTORC1 signalling by eliminating amino acid dependence . Numerous anabolic and energy-generating processes, including protein synthesis, pyrimidine synthesis, HIF1a expression, glycolysis, the oxidative portion of the pentose phosphate pathway (PPP), lipid and mitochondrial metabolism, and glutaminolysis, are stimulated by mTORC1 expression . There is an urgent need for biomarkers based on non-invasive sampling procedures (e.g., blood, urine, etc.) that can help in the diagnosis of lymphoma, such as metabolite profiling. The perfect test should be easy, reliable, and accurate. "What simple, non-invasive, painless, and convenient tests can be used to detect cancer early?" ranked as the most important research priority for the early detection of cancer in the UK-focused research gap survey performed by the James Lind Alliance, which includes patients and doctors . Accordingly, serum biomarkers of lymphoma activity have been studied extensively over the last decade , and we conclude that they are clinically relevant for the diagnosis, prognosis, and therapeutic monitoring of lymphomas. In this review, we shed light on the major metabolic dysregulation described in B-cell non-Hodgkin's lymphoma research (Table 1 and the 3rd Table in Section 3.5). Figure 1 Altered gene expression and mutations associated with key metabolic pathways found in B-NHL subtypes. The figure illustrates: (A) The major B-cell non-Hodgkin's lymphoma subtypes that emerge from different cells that originate within the lymph node; (B) mutated genes that influence metabolic reprogramming; and (C) critical metabolic pathways observed in B-NHL subtypes. The references used for this figure are CLL/SLL , MCL , BL , FL , and DLBCL . 2.1. Diffuse Large B-Cell Lymphoma (DLBCL) The most prevalent B-cell non-Hodgkin's lymphoma is DLBCL. Over 40% of DLBCL patients are refractory and have a worse prognosis for survival . The International Prognostic Index (IPI) is currently used as the primary risk-stratification tool for prognosis in the clinic, and higher IPI scores indicate a worse outcome . However, IPI cannot identify high-risk individuals . Multiple investigations have failed to replicate the predictive power of the molecular heterogeneity of DLBCLs , which is widely regarded as a crucial factor influencing the response to therapy . Therefore, additional research is required to identify new prognostic biomarkers to enhance the current DLBCL stratification system and direct the optimisation of therapeutic strategies. Increased uptake of the glucose analogue 18F-fluoro-2-deoxy-D-glucose (18F-FDG) and up-regulated expression of GLUT1 and HK are indicative of the robust metabolism of DLBCL cells . Metabolic heterogeneity, as shown by malignancies' varied substrate dependency, is common among tumour types and subtypes . DLBCL is metabolically heterogeneous and categorised into oxidative phosphorylation (OxPhos) and BCR groups . Few studies to date have identified specific metabolic indicators involved in the diagnosis and prognosis of DLBCL (the 3rd Table in Section 3.5); the reader is directed to previous studies on these topics . 2.2. Follicular Lymphoma (FL) An indolent lymphoma originating from germinal centre B cells is called follicular lymphoma (FL) . It is the second most prevalent lymphoid malignancy, and accounts for 20% of non-Hodgkin's lymphomas and is a disease of adults . Transformation into DLBCL is related to increased glycolytic enzyme expression, which is in line with higher glucose uptake by 18F-FDG PET/CT . Banoei et al. found higher levels of ADP, AMP, GTP, NADHP, glucose, and uridine diphosphate glucose (UDP-glucose) in FL compared with controls; and this was linked to aggressive cases of FL . Regrettably, little is known about the metabolism of FL. 2.3. Mantle Cell Lymphoma (MCL) MCL represents about 5-10% of B-NHLs. MCL is classified as indolent, but the disease progresses quite aggressively . Many studies have pointed to a disruption of the upstream PI3K/AKT pathway as a driver of mTOR in MCL. Supporting this idea is the finding that PTEN, an intrinsic PI3K/AKT inhibitor, is often absent or at low levels in MCL . Evidence from clinical trials shows that mTOR inhibition effectively targets MCL metabolism, and so it is authorised for the relapsed/refractory (r/r) setting . Glycolysis, PPP, and lipid biosynthesis are all stimulated by mTOR signalling . Higher quantities of lactic acid, TCA metabolites, and amino acids were found in MCL compared with controls, which may suggest a cancer-specific energy metabolic mechanism to ensure ongoing proliferation within the constrained resources of their microenvironment, as reported by Sekihara et al. . By analysing the metabolic processes of MCL cells and their response to the Bruton's tyrosine kinase (BTK) inhibitor ibrutinib (IBR), Lee et al. proposed imaging biomarkers (lactate and alanine) to detect response and resistance to IBR in MCL and suggested pathways to overcome IBR resistance, most notably glutaminolysis, the major oxidative ATP-producing pathway in these cells . 2.4. Burkitt Lymphoma (BL) Dennis Burkitt discovered the rare and aggressive Burkitt lymphoma (BL) . BL is characterised by chromosomal rearrangements of the c-Myc proto-oncogene, which stimulates the expression of multiple enzymes in serine biosynthesis . Serine is necessary for one-carbon metabolism and nucleotide synthesis . Yang et al. studied BL mice serum metabolomics. Glucose, glutamate, and unsaturated lipids were significantly different in BL and controls. Abnormal metabolism and metabolites of BL were found. These discoveries may help create noninvasive approaches for BL diagnosis and prognosis based on these biomarkers . 2.5. Chronic Lymphocytic Leukaemia (CLL) Chronic lymphocytic leukaemia (CLL) is characterised by the heterogeneous malignant proliferation of mature monoclonal B cells in the blood, bone marrow, and lymphoid organs . Alterations in carbohydrate metabolism, lipid metabolism, and OXPHOS are all part of the dynamic metabolic reprogramming of CLL that occurs at different stages of the tumour . Furthermore, TP53, ATM, and MYC, among others, are tumour-suppressor genes that regulate the metabolic reprogramming that occurs during CLL . CLL cells are highly glycolytic, but not as much as DLBCL cells . CLL cells exploit altered lipid metabolism to promote mitochondrial function via activating STAT3 . High FDG uptake in a PET/CT scan is an indication of a glycolytic phenotype in CLL cells, which may predict Richter's transformation into an aggressive lymphoma, most often DLBCL . diagnostics-13-00861-t001_Table 1 Table 1 Significant metabolites in common B-NHL subtypes. B-NHL Subtypes Metabolites Study Purpose Potential Clinical Utility References B-cell lymphoma | Uracil Uracil levels in normal and malignant B cells from mice and humans Early detection FL | ADP, | AMP, | GTP, | NADHP, | glucose, and | UDP-glucose Metabolomics signatures that distinguish FL from controls Predictive of outcome MCL | lactate and | alanine Examine ibrutinib's mechanism of action in MCL cells Therapeutic monitoring BL | Glucose, | glutamine, and | choline Investigated the serum metabolomics of BL mice models Diagnosis Prognosis CLL | Glucose, | glutathione, | lipid, and | glycerolipid Investigate miR-125b's role in CLL Diagnosis Prognosis 3. Metabolomics and B-NHL Biomarker Discovery Metabolomics uses nuclear magnetic resonance (NMR) or mass spectrometry (MS) to look at global, dynamic, and endogenous metabolites . Metabolomics has been used to explore disease pathogenesis and discover novel biomarkers. Thus, metabolomics can be utilised not just to identify new biomarkers but also to develop noninvasive diagnostic and prognostic tools for medical conditions . In the study of cancer, introducing certain novel technologies such as metabolomics is found to impart fruitful and reliable information regarding cancer metabolism, particularly for the main mechanism in tumour proliferation . The impact of B-cell lymphoma on the patient's metabolomics is still not fully known. Little research has been conducted on the treatment response and prognosis of B-cell lymphoma . When looking for alternative methods to improve the rate of detection and compliance in the assessment of B-cell non-Hodgkin's lymphoma, the study of metabolomics with its comprehensive and unbiased exploration for changes in the metabolic profile has been found to be an effective approach . Thus, developing metabolomics technology and functional metabolic assessment in B-cell non-Hodgkin's lymphoma remains an interesting subject for enhanced diagnosis and therapy . As discussed below, there are a variety of steps to metabolomics analysis , each with their own set of benefits and drawbacks . 3.1. Metabolomics Study Design Metabolomics studies can be divided into two classes: targeted and non-targeted. Targeted analysis is used for the identification and quantification of pre-defined metabolites and can be used for quantitative as well as qualitative analysis . Non-targeted analysis consists of analysing all accessible metabolites in a given sample and is the first choice for cancer biomarker discovery studies . Therefore, non-targeted metabolomics research necessitates advanced analytical methodologies, computerised spectral data processing, biological data elucidation, and hypothesis generation . In the DLBCL studies, non-targets were the most frequently applied, with an average of 61.5% compared with targeted methods (the 3rd Table in Section 3.5). 3.2. Sample Collection and Preparation The collection of the sample, its preparation, and storage are the second step in the metabolomics study plan. The most common samples for conducting clinical metabolomics research are blood and urine . It is important to design the research based on metabolomics to reduce the influence of certain constituents such as age, gender, state of fasting, diet, physical activity, exercise, and the day and time of sample collection. Before starting the actual research, it is important to conduct a pilot study of healthy individuals and report it as part of the research to validate the results' reproducibility. The samples (particularly plasma, serum, and urine) must be kept in various aliquots soon after collection to avoid the production of compounds from the many freeze-thaw cycles used for different metabolomics studies . The factors used for processing the sample, such as pH buffering and extraction, should also be uniform and follow standard operating procedures (SOPs) . The samples that are non-invasive in nature, such as blood or urine, are the best for regular clinical analysis . Comparing the serum metabolomics of high-risk individuals with those who have been cured by standard chemotherapy can provide useful information about the prognosis of DLBCL as well as the mechanisms involved in failed treatment procedures . For best practices in metabolomics, the reader is directed to previous reviews on these topics . 3.3. Analytical Techniques The study of metabolomics is regarded as one of the most trustworthy and comprehensive tools for investigating the physiological parameters of an individual, analysing the metabolic pathways, and discovering new biomarkers by employing mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy technologies . 3.3.1. LC-MS The MS technique has the ability to isolate the intricate mixture of compounds for their detection and quantification with elevated sensitivity and specificity, and can also demonstrate information regarding molecular structures . MS separation techniques are essential for reducing sample complexity and minimising ionisation suppression effects . A preceding separation stage, such as high-performance liquid chromatography (HPLC), or ultra-performance liquid chromatography (UPLC), and capillary electrophoresis (CE), is frequently required. There are three main components in a mass spectrometer: an ion source, a mass analyser, and a detector. The ion source is used for converting the sample molecules into ions, which are then resolved into an electromagnetic field or time-of-flight tube by the mass analyser, while the detector is employed for measuring the end results. For maximising the coverage of the metabolome, it is advisable to conduct the analysis of biological samples in the m/z 50-1000 scan range and in both positive and negative ionisation forms . Electrospray ionisation (ESI) is used in metabolomics trials due to its "soft ionization" competency and ability to produce unbroken molecular ions . Medriano et al. examined the metabolomics of two types of blood cancers, myeloma and non-Hodgkin's lymphoma, using plasma samples from both cancer patients and healthy individuals to detect all the potential metabolites and pathways that were affected by employing metabolomics based on LC-MS. Their results revealed a significant metabolomic difference between the healthy control individuals and the myeloma and NHL patients, with disturbed metabolic pathways such as choline metabolism and oxidative phosphorylation being associated with the progression and growth of tumours . 3.3.2. GC-MS GC-MS is a technique that combines great separation efficacy with sensitive, selective, and versatile mass evaluation and is suitable for comprehensive analysis. It is a combination of MS and GS that is used for the detection and quantification of a wide range of chemical compounds, such as natural products, blood, and urine. GS-MS is used in many fields of study, such as detecting drugs, amino acid evaluation, doping control, and the detection of natural materials like food products . EI, or electron ionization, is used for combining MS with GC in almost all the metabolomics applications that are based on GC. The EI-MS method works well for chemical compounds that do not change when heated and that are volatile and are separated by chromatography at high temperatures . Bueno Duarte et al. collected urine samples from NHL patients and conducted their metabolic analysis by employing untargeted GC-MS, which was found to be a valuable tool for distinguishing the population under study. Their GC-MS results indicated the presence of as many as 18 metabolites in the urine sample that contributed to differentiating healthy subjects from DLBCL patients with an accuracy of about 99.8% (p < 0.001). GC-MS is considered a valuable option for studying metabolomics due to its operational simplicity, low cost, reliable identification of metabolites, robustness, and easy availability . 3.3.3. NMR NMR spectroscopy is a universal metabolite detection method that allows for direct analysis of samples with little sample preparation and simultaneous measurement of numerous types of tiny metabolites . However, it has limitations, such as high equipment costs, high maintenance costs, and decreased sensitivity . Mass spectrometry is better than NMR in several ways, although NMR has its own advantages (Table 2). The B-NHL study design determines the optimal analysis. diagnostics-13-00861-t002_Table 2 Table 2 Comparison between LC-MS, GC-MS, and NMR platforms. Characteristics LC-MS GC-MS NMR Sensitivity High High Low Reproducibility Moderate Low High Quantitative analysis Not very quantitative Quantitative Quantitative Metabolite identification More (database available) Few Limited Non-destructive sample No No Yes Sample preparation Need derivatisation/chemical modification Requires sample derivatisation Requires minimum sample preparation Tissue samples extraction Required Required Not required Experimental time Slow Slow Fast Experiment cost High Affordable Low 3.4. Data Acquisition and Processing When the metabolomics data are produced, it is important to ensure that they are reproducible . Quality standardisation and quality control are considered for the optimisation of the reproducibility of results. Data analysis and bioinformatics are used to process the data, which are then subjected to statistical analysis. There are two classical approaches to the statistical analysis of multivariate data: unsupervised learning and supervised learning. A popular unsupervised learning method is principal component analysis (PCA). The second main approach is supervised learning, such as with artificial neural networks (ANN), partial least squares discriminate analysis (PLS-DA), etc., which can be used for excavating the data further to obtain the biomarkers . The discovery process of biomarkers can be driven through supervised models that can be linked with clinical results, histopathological scores, and various other omics data. It is important to test the supervised models with precise internal cross-validation processes or external tests to obtain trusted biomarkers and models and to decrease the chances of data overfitting . 3.5. Metabolites Identification: Biomarker Discovery and Validation Profiling the metabolites in each biological entity is incomplete without accurate data measurement and precise interpretation. To identify the features of potent spectral biomarkers, attempts are made to recognise the unidentified spectral biomarkers. The peaks can be identified with the help of public metabolomics databases and in-house spectral databases such as the Golm database, LIPID MAPS, human metabolome database (HMDB), METLIN database, etc. Following the identification of metabolomics biomarkers, additional experiments are required to validate or test the biomarkers . DLBCL is the most common non-Hodgkin's lymphoma, and therefore 13 publications of relevance to our research interest are included in this review (search query in PubMed: "Metabolomics" and "DLBCL"), and summarised in Table 3. 4. Applications of Metabolomics in B-NHL In the clinical setting, metabolomics is finding an expanding number of applications, including disease diagnosis and understanding, the discovery of novel drug targets, the customisation of medication treatment, and the monitoring of therapeutic results . In this last section, we discuss the clinical applications of metabolomics and offer examples to clarify how metabolism will open a new era in lymphoma research and how this will positively influence diagnosis and treatment. 4.1. Discovering Targeted Therapies Based on Metabolomics Metabolism in B-NHL plays a crucial role in established therapeutic approaches (Table 4). Antimetabolites were the name given to the chemical compounds that were first used to treat cancer. The reason for choosing this name was that these compounds were found to resemble endogenous metabolites in their chemical structure and disrupt the process of normal metabolism. In comparison to other omics, metabolomics is best for evaluating the potential of these cancer treatment regimens. This study was carried out to discover whether the therapies could cause alterations in the metabolic pathways and detect the pharmacokinetics of drugs simultaneously or not. In the coming time, it will become crucial to combine the study of pharmacometabolomics with other biological systems knowledge, such as mRNA, genetics, miRNA, and imaging. This will help in determining the correlation of the metabolomics response with the cancer stage, undesirable incidents, and the growth or recession of the tumour. The study of pharmacometabolomics is capable of monitoring a patient's metabolic response to a drug; thus, it is very interesting to use metabolomics in detecting cancerous growth, prognosis, and therapy management . Moreover, the therapies based on metabolomics can not only enhance the responses of immune cells to extremely immunogenic tumours but can also elevate the immunogenicity of cancer cells, thereby increasing the ability of immunotherapy to cure a vast variety of carcinomas. For further information, the reader is directed to previous reviews on these topics . 4.2. Determining B-NHL Diagnostic and Prognostic Biomarkers A recent metabolomics study suggested a methodology for discovering novel biomarkers that can be used for the diagnosis and characterisation of various lymphoma subtypes. The GC-MS method was used for the investigation and evaluation of plasma samples taken from individuals with different subtypes of lymphomas. The results showed a significant prevalence of elaidic acid and hypoxanthine (HX) in patients suffering from Hodgkin's lymphoma, MM, CLL, and DLBCL compared with healthy control individuals in all the study groups . Yoo et al. analysed the urine samples taken from lymphoma patients and translated the data into ions of low mass, i.e., less than 1000 m/z. They chose three peaks of high intensity and low mass ions for the analysis, of which the peak in the range of 137.08 m/z ion was detected as HX. The levels of HX and xanthine inside the cells are found to be inversely proportional to the energy modifications of adenylate and thus to the ATP of the cells. Additional research is required as abnormal metabolic processes are detected as initial lymphoma biomarkers . For further information, the reader is directed to previous reviews on these topics . 4.3. Determining the Lymphomagenesis Risk Factors Genetic mutations accumulate sequentially during tumour development, eventually resulting in malignant tumours. However, it has also been shown that metabolic processes and inflammatory factors indirectly contribute to the development of the tumour . In their study, Pettersena et al. proved that the cell line of B-cell lymphoma surrounds numerous amplified genomic uracil concentrations in comparison with non-lymphoma cell lines or normal lymphocytes. They utilised a method based on liquid chromatography combined with mass spectrometry (LC/MS) for quantifying the genomic sequence of 2-deoxyuridine and proving their study. In harmony with uracil generated by activation-induced cytidine deaminase (AID), they discovered a distinctive mutational signature of an AID hotspot in the lymphoma area where there was clustered mutation. They also presented an important revelation about the expression of SMUG1 and uracil-DNA glycosylases UNG along with the excision capacity of uracil by stating its negative correlation with the concentration of genomic uracil, which somewhat decreased the AID effect . Another study was also conducted on the metabolomic pattern of Burkitt lymphoma that was induced by MYC glucose deprivation, as well as hypoxic and aerobic conditions. They used a [U-13C, 15N]-glutamine tracer to detect glutamine import and metabolism via the TCA cycle under hypoxia conditions and discovered that glutamine is significantly precipitated to citrate carbons. The deficiency of glucose leads to the significant augmentation of citrate, fumarate, and glutamine-derived malate. Their arrangements showed a different pathway for the generation of energy called glutaminolysis, which is associated with the glucose-independent TCA cycle. Under the conditions of hypoxia and scarcity of glucose, the critical role of glutamine in the proliferation of cells makes them susceptible to BPTES (glutaminase inhibitors), which in turn can be used for treating tumours . 5. Conclusions As the use of metabolomics is continuously increasing in clinical trials, it may soon become one of the most successful tools for detecting and healing cancerous growths. The changes related to metabolic pathways may occur in a broad range of B-cell non-Hodgkin's lymphomas. Researching and knowing about them can help in identifying new remedial targets and discovering novel metabolic biomarkers. In the near future, the study of metabolomics will become crucial for outcome prediction and the revelation of new treatment regimens. There is a need for conducting metabolomics research on B-cell lymphomas in large cohort trials to discover new biomarkers, which will thus prove to be an influential step in the path of clinical integration of biomarkers that are discovered by metabolomics. Author Contributions A.A. (Abdullah Alfaifi), M.Y.R. and M.A. designed the review format; A.A. (Abdullah Alfaifi) and M.A. wrote the first draft of manuscript; S.B., H.M., W.A.-K., E.D., A.A. (Aqeel Aqeel) and A.M. edited and reviewed the flow of information in review; R.A., H.A. and I.Q. supervised and corrected grammatical errors in manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 2 B-NHL Metabolomics Workflow Steps: (1) study design; (2) pre-analytical process, including sample collection and processing; (3) analytical process, which is platform choice (either LC-MS, GC-MS, or NMR); and (4) post-analytical process, including data processing, results interpretation, and biomarker identification. diagnostics-13-00861-t003_Table 3 Table 3 Metabolic markers of diagnostic and prognostic significance in DLBCL. Metabolic Markers Study Design Sample Type Analytical Platform Statistics References Alanine, aspartate, glutamate, cysteine, & methionine Untargeted Cell lines UHPLC/MS t-test & partial least square discriminant analysis (PLS-DA) Asparagine & serine Targeted Cell lines NMR Two-sided Fisher's exact test & principal component analysis (PCA) lysine & arginine Untargeted Serum NMR Supervised multivariate analysis Valine, hexadecenoic acid & pyroglutamic acid Untargeted Serum GC/MS PCA & PLS-DA 2-aminoadipic acid, 2-aminoheptanedioic acid, erythritol & threitol Untargeted Plasma GC/MS t-test, multivariate analyses & PLS-DA Ornithine Untargeted Cell lines GC/MS t-test, one-way ANOVA) & orthogonal partial least-squared discrimination analysis (OPLS-DA) Pyruvic acid Targeted Cell lines & FFPE NMR & GC/MS The Shapiro-Wilk test, two-sided Welch test, the nonparametric Mann-Whitney U test & PCA Malate Untargeted Plasma GC/MS two-tailed Student's t-test, one-way ANOVA, PCA, a supervised PLS-DA & OPLS-DA 2-arachidonoylglycerol (2-AG) Untargeted Serum & cell lines HPLC/MS Two-tailed t-test, and XCMS/R Lactate Targeted Cell lines GC/MS Two-tailed t-test, Kaplan-Meier curves & log-rank test Glycine Targeted Cell lines HPLC/MS t-test Choline Targeted Serum UPLC/MS Two-tailed t-test Choline Untargeted Plasma UHPLC/MS & GC/MS t-tests & supervised multivariate analysis diagnostics-13-00861-t004_Table 4 Table 4 Therapeutic drugs for B-NHL metabolism. 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PMC10000529 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050806 cells-12-00806 Article Changes in Liver Lipidomic Profile in G2019S-LRRK2 Mouse Model of Parkinson's Disease Corral Nieto Yaiza Methodology 1+ Yakhine-Diop Sokhna M. S. Methodology 234+ Moreno-Cruz Paula Methodology 1 Manrique Garcia Laura 1 Gabrielly Pereira Amanda Methodology 1 Morales-Garcia Jose A. 356 Niso-Santano Mireia Methodology 234 Gonzalez-Polo Rosa A. 234 Uribe-Carretero Elisabet Methodology 234 Durand Sylvere Methodology 7 Maiuri Maria Chiara Methodology 78 Paredes-Barquero Marta Methodology 24 Alegre-Cortes Eva Methodology 24 Canales-Cortes Saray Methodology 24 Lopez de Munain Adolfo 39101112 Perez-Tur Jordi 31314 Perez-Castillo Ana 36 Kroemer Guido Conceptualization 7815 Fuentes Jose M. 234* Bravo-San Pedro Jose M. 13* Ko Hanseok Academic Editor 1 Departamento de Fisiologia, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain 2 Departamento de Bioquimica y Biologia Molecular y Genetica, Facultad de Enfermeria y Terapia Ocupacional, Universidad de Extremadura, 10003 Caceres, Spain 3 Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas-Instituto de Salud Carlos III (CIBER-CIBERNED-ISCIII), 28029 Madrid, Spain 4 Instituto Universitario de Investigacion Biosanitaria de Extremadura (INUBE), 10003 Caceres, Spain 5 Instituto de Investigaciones Biomedicas "Alberto Sols" (CSIC-UAM), 28029 Madrid, Spain 6 Departamento de Biologia Celular, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain 7 Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, 94805 Villejuif, France 8 Centre de Recherche des Cordeliers, Equipe Labellisee par la Ligue Contre le Cancer, Inserm U1138, Universite Paris Cite, Sorbonne Universite, 75006 Paris, France 9 Neuroscience Area of Biodonostia Health Research Institute, Donostia University Hospital, 20014 San Sebastian, Spain 10 Department of Neurology, Donostia University Hospital, OSAKIDETZA, 20014 San Sebastian, Spain 11 Ilundain Foundation, 20018 San Sebastian, Spain 12 Department of Neurosciences, University of the Basque Country UPV-EHU, 20014 San Sebastian, Spain 13 Instituto de Biomedicina de Valencia-CSIC, Unidad de Genetica Molecular, 46010 Valencia, Spain 14 Unidad Mixta de Genetica y Neurologia, Instituto de Investigacion Sanitaria La Fe, 46026 Valencia, Spain 15 Institut du Cancer Paris CARPEM, Department of Biology, Hopital Europeen Georges Pompidou, AP-HP, 75015 Paris, France * Correspondence: [email protected] (J.M.F.); [email protected] (J.M.B.-S.P.) + These authors contributed equally to this work. 04 3 2023 3 2023 12 5 80628 12 2022 07 2 2023 01 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The identification of Parkinson's disease (PD) biomarkers has become a main goal for the diagnosis of this neurodegenerative disorder. PD has not only been intrinsically related to neurological problems, but also to a series of alterations in peripheral metabolism. The purpose of this study was to identify metabolic changes in the liver in mouse models of PD with the scope of finding new peripheral biomarkers for PD diagnosis. To achieve this goal, we used mass spectrometry technology to determine the complete metabolomic profile of liver and striatal tissue samples from WT mice, 6-hydroxydopamine-treated mice (idiopathic model) and mice affected by the G2019S-LRRK2 mutation in LRRK2/PARK8 gene (genetic model). This analysis revealed that the metabolism of carbohydrates, nucleotides and nucleosides was similarly altered in the liver from the two PD mouse models. However, long-chain fatty acids, phosphatidylcholine and other related lipid metabolites were only altered in hepatocytes from G2019S-LRRK2 mice. In summary, these results reveal specific differences, mainly in lipid metabolism, between idiopathic and genetic PD models in peripheral tissues and open up new possibilities to better understand the etiology of this neurological disorder. lipids liver LRRK2 metabolome neurodegeneration Parkinson Instituto de Salud Carlos IIIFondo de Investigaciones SanitariasPI15/0034 CIBERNED-ISCIIICB06/05/0041 2015/03 European Regional Development Fund (ERDF)Ramon y Cajal ProgramRYC-2018-025099-I Spain's Ministerio de Ciencia e InnovacionPID2019-108827RA-I00 Community of MadridCT5/21/PEJ-2020-TL/BMD-17685 CT36/22-41-UCM-INV CIBERNED-ISCIIIMINECO Spanish MinistryPRE2020-092668 Ramon y Cajal ProgramRYC-2016-20883 FPU predoctoral fellowshipFPU16/00684 FPU19/04435 University of Extremadura fellowshipJunta de Extremadura, SpainIB18048 MINECOSAF2014-52940-R SAF2017-85199-P CIBERNED-ISCIIICB06/05/1123 2015/03 Ligue contre le Cancer (equipe labellisee)Agence National de la Recherche (ANR)--Projets blancsthe ERANet for Research on Rare DiseasesAMMICa US/CNRS UMS3655Association pour la recherche sur le cancer (ARC)Association "Le Cancer du Sein, Parlons-en!"Canceropole Ile de-FranceChancelerie des universites de Paris (Legs Poix)Fondation pour la Recherche Medicale (FRM)European Research Area Network on Cardiovascular Diseases (ERA-CVD, MINOTAUR)Gustave Roussy Odyssea, the European Union Horizon 2020 Project OncobiomeFondation CarrefourHigh-end Foreign Expert Program in ChinaGDW20171100085 Institut National du Cancer (INCa)Inserm (HTE)Institut Universitaire de FranceLeDucq Foundationthe LabEx Immuno-OncologyANR-18-IDEX-0001 the RHU Torino LumiereSeerave FoundationIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE)the SIRIC Cancer Research and Personalized Medicine (CARPEM)This research was supported by "Instituto de Salud Carlos III", "Fondo de Investigaciones Sanitarias" (PI15/0034), "CIBERNED-ISCIII" (CB06/05/0041 and 2015/03), and partially supported by "European Regional Development Fund (ERDF)" from the European Union. J.M.B.-S.P. is funded by "Ramon y Cajal Program" (RYC-2018-025099-I) and supported by Spain's Ministerio de Ciencia e Innovacion (PID2019-108827RA-I00). Y.C.N. and L.M.G. are funded by Community of Madrid (CT5/21/PEJ-2020-TL/BMD-17685 and CT36/22-41-UCM-INV respectively). S.M.S.Y.-D. was supported by CIBERNED-ISCIII. P.M.-C. is funded by the MINECO Spanish Ministry (FPI grant, PRE2020-092668). M.N.-S. was funded by "Ramon y Cajal Program" (RYC-2016-20883). E.U.-C. and S.C.-C. were supported by an FPU predoctoral fellowship (FPU16/00684) and FPU19/04435), respectively, from "Ministerio de Educacion, Cultura y Deporte". M.P-B was funded by a University of Extremadura fellowship. E.A-C was supported by a Grant (IB18048) from Junta de Extremadura, Spain. J.M.F. received research support from the "Instituto de Salud Carlos III"; "Fondo de Investigaciones Sanitarias" (PI15/0034) and CIBERNED-ISCIII (CB06/05/0041 and 2015/03). A.P.-C. was supported by MINECO (SAF2014-52940-R and SAF2017-85199-P). J.P.-T. received funding from CIBERNED-ISCIII (CB06/05/1123 and 2015/03). G.K. is supported by the Ligue contre le Cancer (equipe labellisee); Agence National de la Recherche (ANR)--Projets blancs; ANR under the frame of E-Rare-2, the ERANet for Research on Rare Diseases; AMMICa US/CNRS UMS3655; Association pour la recherche sur le cancer (ARC); Association "Le Cancer du Sein, Parlons-en!"; Canceropole Ile de-France; Chancelerie des universites de Paris (Legs Poix), Fondation pour la Recherche Medicale (FRM); a donation by Elior; European Research Area Network on Cardiovascular Diseases (ERA-CVD, MINOTAUR); Gustave Roussy Odyssea, the European Union Horizon 2020 Project Oncobiome; Fondation Carrefour; High-end Foreign Expert Program in China (GDW20171100085), Institut National du Cancer (INCa); Inserm (HTE); Institut Universitaire de France; LeDucq Foundation; the LabEx Immuno-Oncology (ANR-18-IDEX-0001); the RHU Torino Lumiere; the Seerave Foundation; the SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE); and the SIRIC Cancer Research and Personalized Medicine (CARPEM). pmc1. Introduction Parkinson's disease (PD) is the second most common neurodegenerative disorder , only below Alzheimer's disease. In recent years, it has experienced a very rapid growth in prevalence, becoming one of the main causes of disability worldwide . PD is a progressive neurological disorder mainly characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc), a critical area for movement control in the brain , leading to the major clinical motor symptoms of the disease, such as bradykinesia and rigidity . Thus, there is, on the one hand, a direct and evident relationship between disorders at the neural level and PD, but on the other hand, it is known that this disease is related to peripheral organs, including the liver. In fact, alpha synuclein accumulations have been observed both in brain and liver . Moreover, some common urinary markers, as 8-hydroxy-2'-deoxyguanosin, have been identified for PD and chronic liver disease patients and a correlation between patients with cirrhosis and PD has also been hypothesized and verified by a significant improvement of motor symptoms after the first year of liver transplantation in patients with cirrhosis and PD . The bases of the etiology of this disease have not been fully deciphered, so exposure to environmental toxins, genetic factors and aging are currently accepted as the major triggers of this type of neurodegeneration . Most patients diagnosed with PD (approximately 80-85%) have primary parkinsonism or idiopathic PD; that is, the cause of the disease remains unknown. Exposure to the catecholaminergic neurotoxin 6-OHDA has been widely used to generate PD models, which are considered appropriate for studying the idiopathic form of PD . Nevertheless, a small percentage of patients manifest a genetic form of PD. There are multiple PD-related genes (called PARK genes) unequivocally linked to the inherited monogenic disease. Mutations in SNCA (PARK1/4), Parkin (PARK2), PINK1 (PARK6), DJ-1 (PARK7), LRRK2 (PARK8) and ATP13A2 (PARK9) are responsible for the autosomal dominant or recessive mode of inheritance for PD. There are few missense variants of LRRK2/PARK8 that have been confirmed to increase the risk of PD, including variants G2019S, N1437H, R1441C/G/H/S, Y1699C, and I2020T. However, the substitution of the serine residue by a glycine residue in exon 41 of the protein kinase domain in LRRK2 (G2019S mutation) is the most common mutation across 51 countries , accounting for 1% of sporadic PD cases and 4% of familial PD cases, among all cases . It is well described that the presence of the G2019S mutation induces an increase in the kinase activity of this protein, which is the precursor of neuronal damage associated with the disease . In fact, inhibitors of LRRK2 kinase activity are one of the best potential therapeutics for the disease caused by the said mutation . The exact molecular mechanisms underlying LRRK2-associated PD pathology are far from clear; however, it is known that alterations in this gene affect important cellular processes such as microtubule dynamics, vesicular trafficking, synaptic transmission or autophagy . Omics analysis, especially metabolomics, is a very comprehensive tool for identifying molecular networks related to the pathogenesis of this little-known disease . There are multiple metabolomic studies based on the analysis of metabolites in cerebrospinal fluid , blood samples , urine , feces or neuronal tissue . However, analysis of liver cells has not been performed in neurodegenerative models of this disease. Our aim was to study the metabolic alterations produced in the liver and SNpc tissues samples after developing genetic or acute intoxication PD models. This was accomplished by examining the complete metabolomic profile of hepatocyte and striatum cells in both mouse models. 2. Materials and Methods Mass spectrometry was used to perform a metabolomic analysis of striatum (n = 5 mice/group) and liver (n = 4-5 mice/group) tissues in three different mouse models of PD and respective control mice: i, control mice (non-parkinsonian WT mice, untreated); ii, GS-PD mice (parkinsonian mice with whole body G2019S-LRRK2 mutation); iii, ai-PD mice (parkinsonian WT mice, treated with neurotoxin 6-OHDA). Mouse strains and housing: All animal experiments were allowed by the "Ethics Committee for Animal Experimentation" of the Biomedical Research Institute "Alberto Sols" (CSIC-UAM) in Madrid (Spain) and performed in accordance with the European Communities Council Directive (2010/63/EEC) and national regulations (normative RD1386/2018). Adult male WT-LRRK2 and G2019S-LRRK2 transgenic mice (Tg) (3 months old, 25-30 g) were obtained from Jackson Laboratories and backcrossed in house. Genotyping was performed via PCR using the following oligonucleotide primers: 5'-ATTACCATGGTTCGAGGTGA-3' (forward) and 5'-CAAGTGTCTGCAGGAAGGTT-3' (reverse) for G2019S-LRRK2; 5'-CTAGGCCACAGAATTGAAAGATCT-3' (forward) and 5'-GTAGGTGAAATTCTAGCATCATCC-3' (reverse) for an internal-positive control. About two to three animals were housed per cage with free access to chow and liquid under a 12 h light/dark cycle. Special care was taken to minimize pain and discomfort in animals. Acute intoxication PD model: This model was induced as previously described . Using a stereotaxic apparatus (Kopf Instruments, Tujunga, CA, USA), 6-OHDA (5 mg in 2.5 mL of saline with 0.02% ascorbic acid) was unilaterally injected into the SNpc of anesthetized mice at the subsequent coordinates from bregma: posterior, -3.2 mm; lateral, +2.0 mm; and ventral, +4.7 mm, with the skull flat between lambda and bregma, according to this mouse brain atlas . The mice were then housed for quick recovery. Mice were sacrificed 45 days after the 6-OHDA-induced damage (i.e., at 4.5 months of age), at which time the loss of dopaminergic neurons was over 65%, in line with what was described in human patients at the time of diagnosis of the disease. In both murine and human, it is the intermediate (mid-final) stage of neurodegeneration. In addition to motor alterations detected in animals subjected to the apomorphine injection test, we have previously demonstrated through histological and immunohistochemical analysis an increase in the production of proinflammatory factors (activation of microglia) and dopaminergic death in the substantia nigra . Tissue sample preparation for metabolomic analyses: About 30 mg of samples for each condition were solubilized into 1.5 mL tubes with ceramic beads with 1 mL of cold lysate buffer consisted of ISTD (MeOH/Water, 9/1, -20 degC). They were then homogenized three times for 20 s at 5500 rpm using Precellys 24 tissue homogenizer (Bertin Technologies, Montigny-le-Bretonneux, France), and centrifuged for 10 min at 15,000x g, 4 degC. Subsequently, the upper phase of supernatant was divided into two volumes of 300 mL, one was used for gas chromatography coupled by mass spectrometry (GC/MS) experiment in microtube, and the other was used for ultrahigh pressure liquid chromatography coupled by mass spectrometry (UHPLC/MS) experimentation. Regarding GC-MS aliquots, the volume of 300 mL was transferred to glass tubes and evaporated. Subsequently, we added 50 mL of methoxyamine (20 mg/mL in pyridine) to the dry extracts and stored the samples overnight at room temperature in the dark. The next day, we added 80 mL of MSTFA and the final derivatization occurred at 40 degC for 30 min. Afterwards, samples were transferred in vials and directly injected into GC-MS. Concerning the UHPLC-MS aliquots, the volume of 300 mL was dried in microtubes at 40 degC in a pneumatically assisted concentrator (Techne DB3, Staffordshire, UK). The dry extracts were dissolved with 200 mL of MilliQ water. Samples were transferred in LC vials and injected into UHPLC-MS or stored at -80 degC until injection. Targeted analysis by GC coupled to triple quadrupole (QQQ) mass spectrometry: GC-MS/MS acquisitions were performed on a 7890B gas chromatograph coupled to a triple quadrupole 7000C detector (both from Agilent Technologies, Santa Clara, CA, USA), equipped with an electronic impact source (EIS) operating in positive mode and a 30 m x 0.25 mm I.D. x 0.25 mm film thickness HP5MS capillary column (Agilent Technologies). Sample aliquots of 1 mL were inoculated into an inlet operating in splitless mode and set at 250 degC. Helium gas flow rate was fixed at 1 mL/min and the septum purge flow at 3 mL/min. The temperature was programmed as follows: 60 degC for 1 min, +10 degC/min up to 210 degC, hold for 3 min, +5 degC/min up to 325 degC and hold for 5 min. The transfer line and ion-source temperatures were 250 degC and 230 degC, respectively. Targeted analysis by UHPLC coupled to triple quadrupole (QQQ) mass spectrometry: Targeted analysis was conducted on a RRLC 1260 system coupled to a triple quadrupole 6410 detector (Agilent Technologies), armed with an electrospray source operating in positive mode. Gas temperature was set at 350 degC, gas flow at 12 L/min, and capillary voltage at 3.5 kV. Sample aliquots of 10 mL were injected on a Zorbax Eclipse XDB-C18 column (100 mm x 2.1 mm, particle size 1.8 mm, Agilent Technologies), protected by an XDB-C18 guard column (5 mm x 2.1 mm, particle size 1.8 mm) and heated at 40 degC. The gradient mobile phase consisted of 2 mM of dibutyl ammonium acetate (DBAA) in water (A) and acetonitrile (B). The flow rate was set at 0.2 mL/min, and the gradient modified as follows: initial condition (90% phase A and 10% phase B) was maintained for 4 min, from 10% to 95% phase B over 3 min. The column was washed using 95% mobile phase B for 3 min and equilibrated using 10% phase B for 3 min. The autosampler was kept at 4 degC. Pseudo-targeted analysis of intracellular metabolites by UHPLC combined to a Q-Exactive mass spectrometer. Reversed phase acetonitrile method: The profiling experiment was done with a Dionex Ultimate 3000 UHPLC system (Thermo Scientific, Waltham, MA, USA) coupled to a Q-Exactive (Thermo Scientific) equipped with an electrospray source operating in both positive and negative mode and full scan mode from 100 to 1200 m/z. The Q-Exactive parameters were: sheath gas flow rate 55 au, auxiliary gas flow rate 15 au, spray voltage 3.3 kV, capillary temperature 300 degC, S-Lens RF level 55 V. The mass spectrometer was calibrated with sodium acetate solution specific for low mass calibration. Samples (10 mL) were injected on an SB-Aq column (100 mm x 2.1 mm particle size 1.8 mm) from Agilent Technologies, protected by a guard column XDB-C18 (5 mm x 2.1 mm particle size 1.8 mm) and warmed at 40 degC by a pelletier oven. The gradient mobile phase consists of 0.2% of acetic acid (A) and acetonitrile (B) in water. The flow rate was set to 0.3 mL/min. Initial condition was 98% phase A and 2% phase B. Molecules were then eluted using a gradient from 2% to 95% phase B in 22 min. The column was cleaned using 95% mobile phase B for 2 min and equilibrated using 2% mobile phase B for 4 min. The autosampler was kept at 4 degC. Peak detection and integration were carried out using the Thermo Xcalibur quantitative software (2.1.) Quantification and statistical analysis: The data are reported as the means +- standard error of the mean (SEM). The number of independent data points (N) is indicated in Table S1. For statistical analyses, p-values were estimated by one-way ANOVA (analyzing metabolites individually), or Pearson's correlation coefficients with 95% confidence intervals (Pearson's correlation coefficient (R)). Differences were considered statistically significant when p-values were: deg (p < 0.1), * (p < 0.05), ** (p < 0.01), *** (p < 0.001) and **** (p < 0.0001). 3. Results 3.1. Metabolic Changes Observed in Nerve Cells of Genetic and Acute Intoxication Models of PD A metabolomic approach was performed to study potential markers involved in the development of parkinsonian mice. For this, nervous and hepatic tissues extracted from mice with genetic model (GS-PD, due to G2019S-LRRK2 mutation) or acute intoxication model (ai-PD, WT mice treated with 6-OHDA) were analyzed to observe the complete metabolomic profile in striatum (Table S1) and hepatocyte cells (Table S2). Regarding the metabolomic results obtained from the nerve cells, we noticed an overall increase in most metabolites in the GS-PD model and in the ai-PD model . When we analyzed all metabolite changes observed in the striatum, we found a good correlation (Pearson correlation coefficient (R = 0.53 and p value < 0.0001) . These results indicate that metabolic modulations are independent of the etymological origin of the disease. Performing an in-depth analysis to independently study what is happening in the different metabolic pathways, we can determine which pathways are more or less altered in the two PD models studied . Thereby, we have observed a very strong correlation in most routes, with a great significance (amino acids: R = 0.53 and p value < 0.001; organic compounds; R = 0.88 and p value < 0.0001; lipids R = 0.58 and p value < 0.0001; nucleosides: R = 0.79 and p value = 0.02; carbohydrates: R = 0.87 and p value < 0.0001) . It should be noted that in the carbohydrates pathway, maltose and sucrose were exclusively reduced in ai-PD . We also found different modulations between both PD models when we focused on nucleotides and nitrogen bases . By looking into the different metabolites regulated in these pathways, we observed that NADH was increased in GS-PD, but decreased in ai-PD models . Moreover, uric acid levels were exclusively raised in GS-PD mice . 3.2. Metabolic Changes Observed in the Hepatocytes of Genetic and Acute Intoxication Models of PD Regarding the results obtained in liver cells, we found a drop in numerous metabolites, which occurs exclusively in the genetic model , with no significant changes in the liver of ai-PD model . Indeed, analyzing different metabolic responses of the two PD induction models in the liver, the correlation between the whole metabolite changes observed in both models is very low (R = 0.25) , corroborating the presence of numerous modulations of hepatic metabolism exclusively in the GS-PD model but not in the acute intoxication model. To better understand which metabolites are exclusively modulated in GS-PD or ai-PD mice, we performed a correlation analysis between the modulations observed in parkinsonian mice from both models. We notified a similar response in the parkinsonian mice from both models in some pathways: amino acids: R = 0.35 and p value = 0.02; carbohydrates: R = 0.83 and p value < 0.0001; organic compounds: R = 0.66 and p value = 0.002; nucleotides: R = 0.83 and p value = 0.0005; nucleosides: R = 0.62 and p value = 0.09 . However, we found that nitrogen bases (GS-PD vs. ai-PD correlation: R = 0.57 and p value = 0.14), bile acids (GS-PD vs. ai-PD correlation: R = 0.13 and p value = 0.79) and lipids (GS-PD vs. ai-PD correlation: R = -0.0001 and p value = 0.99) are mainly modulated in the genetic model, but not in the acute intoxication model in hepatocytes. . 3.3. Changes in Lipid Metabolites in Genetic or Acute Intoxication PD Models Liver According to the results obtained in the liver extract, genetic models and those resulting from the acute intoxication of PD exert a similar metabolic modulation. Within the metabolic routes in which we observed a similar behavior in both models, we can highlight a decrease in maltose disaccharide carbohydrates such as the pentoses ribose, ribitol and xylitol , as well a drop in hypotaurine levels . Finally, we found an increase in the NADP and ATP levels in parkinsonian mice liver, regardless of the origin of the disease . As previously mentioned, genetic and acute intoxication PD models exert similar metabolic modulation in the liver, with the exception of lipid metabolism, which is highly modulated in the genetic model . Analyzing the lipid metabolism in this organ in depth, we observed an important decrease in fatty acids (FAs), in the genetic GS-PD model with respect to healthy mice; such as long-chain saturated FAs (C14:0, C15:0 and C20:0), monounsaturated very long-chain FAs (C19:1, C20:1, C22:1, C24:1) and polyunsaturated very long-chain (C18:3, C18:4, C20;2, C20;3, C20;5, C22;4, C22;5, C22;6). However, no significant variations were observed for dicarboxylic acids (except for hexadecanedioic acid, C16:0) . Additionally, there were several changes in cell membrane phospholipids, with an important decrease in phosphatidylcholine (PC) (PC 16:0, PC 17:0, PC 18:0, PC 16:1, PC 18:2, PC 20:3, PC 20:4, PC 22:6) and phosphatidylethanolamine (PE 16:0) in parkinsonian GS-PD mice liver . Finally, we noticed a decrease for general carnitines, specifically carnitines C6:0 or C18:0, and an increase in acetyl-CoA levels on this genetic model . Regarding bile salts, there was a general decrease in hepatic levels of all intermediate metabolites considered exclusive in mice carrying the G2019S-LRRK2 mutation . 4. Discussion The factors that contribute to the onset of PD are highly variable. Indeed, the loss of dopaminergic terminals and lack of dopamine release have been reported in the striatum from models as varied as PD patients, transgenic animal models of PD, or different toxin-induced models . Understanding the differences between these disease triggers is very important to improve our comprehension and to generate specific therapies for each PD risk factor. For this, it would be interesting to detect common metabolic or specific modulations between all disease triggers. It is also essential to assess whether these factors have a metabolic influence, not only on the nervous system, but on the periphery as well. Metabolic problems associated with PD are not just restricted to plasma and nervous tissue but also to PARK gene defects and liver damage, such as the parkin defect and its relationship with alcohol-induced liver injury and steatosis in mice . The present study showed a metabolomic evaluation of brain and liver tissues in two different acute intoxication and genetic PD models. Analyzing the metabolic profiles obtained from the striatum, we observed that most metabolic changes occur in parallel in all parkinsonian mice, regardless of the genetic origin or due to acute intoxication of the disease. In general, an increase in a wide range of amino acids, organic compounds, lipids or nucleosides was reported . It is curious that in the acute intoxication model, but not in the genetic model, a decrease in sucrose and maltose levels is observed, and some previous studies have linked PD to problems with carbohydrate metabolism . However, analyzing all the data, we have not been able to observe significant modulations of the main metabolites related to carbohydrate metabolism, such as glucose, glucose-6-phosphate or fructose-6-phosphate in the striatum (Table S1) or in the liver (Table S2), so there do not appear to be important changes in the carbohydrate pathways in the striatum in both models. Therefore, we can conclude that the damage produced by the G2019S-LRRK2 mutation throughout the body, and by acute 6-OHDA intoxication, are very similar in terms of metabolic changes in the striatum of diseased mice compared to healthy mice. Nevertheless, when we check the metabolic profiles in the liver of GS-PD and ai-PD mice, the number of differences between both models is much greater . Analyzing in depth these differently modulated metabolites, we observed that almost all of them are part of lipid metabolism pathways . The lipidomic approaches in already published articles highlighted important functions of lipids and, in particular, dysfunctions in lipid metabolism in the pathogenesis of protein misfolding diseases, including PD . Interestingly, in the last decade, there has been a growth in the study of the interaction between macroautophagy and lipid metabolism and prior to this study, we have shown an excess in autophagy flux in fibroblasts from patients with the G2019S-LRRK2 mutation . Moreover, despite the fact that autophagy can help to eliminate hepatic steatosis , and that it is a powerful tool in multiple diseases , including neurodegenerative and liver-associated diseases, an excess of this autophagy response could be equally negative . Thus, it would be very interesting to study the specific role that the aberrant autophagy associated with the GS-PD mice has in the deregulation of lipid metabolism in the liver tissue samples. Going in depth into the observed changes, we noticed a decrease in polyunsaturated LCFA and VLCFA levels exclusively in the liver of GS-PD mice, but the level of these metabolites was not modified in the acute intoxication model , as previously described in rats treated with 6-OHDA . Therefore, it seems that there is a possible implication of the LRRK2 protein in the hepatic control of lipids. In this sense, previous studies have shown that activity of fatty acid oxidation is increased in LRRK2-overexpressing liver hepatic carcinoma cells ; conversely, in hepatocytes and stellate cells of LRRK2-KO mice, the lipid droplets accumulate more than in LRRK2-WT animals . Indeed, the present results indicate that there is an increase in the oxidation of very long-chain fatty acids in the genetic model, after having observed a decrease in fatty acids and a consequent increase in the production of NADH, NADPH, acetyl CoA and ATP . Importantly, this increase in acetyl-CoA appears to be consistent with the increased levels of acetylated proteins observed in patients with G2019S-LRRK2 mutation ; this phenotype was not observed in idiopathic PD patients. In addition, and also related to lipid metabolism, we found that PC and PE, major components of biological membranes, are exclusively decreased in hepatocytes obtained from GS-PD mice . Interestingly, a decrease in PC has already been observed in other samples, as plasma and frontal cortex from PD patients , in brain from animal PD models and in goldfish models treated with MPTP . It must be highlighted that G2019S-LRRK2 mutation has been directly linked with a-synucleinopathies and that the a-Syn deposits are not confined to the organs of the central nervous system and are found in other organs and cells, including hepatocytes of different animal and cellular models of PD and in humans . a-Syn is a protein that localizes to curved and ordered membranes inside the cell, and changes in PC concentrations in this membrane can affect a-syn fluidity and conformation, leading to its aggregation . Considering that modulations in the physiological fluidity of the membrane may promote the accumulation of insoluble materials associated with PD , and that the liver is involved in the clearance of pathological protein aggregates , it can be hypothesized that this decrease in PC and PE in the liver could have a negative effect on the role played by this organ in the cleaning of a-syn pools. Finally, there is a relationship between ceramides and sphingolipids and PD . Defective sphingolipid pathways are reported through some clinical studies on PD subclasses , and LRRK2 KO mice showed elevated levels of ceramides in the brain . In addition, treatment with specific LRRK2 inhibitors (in assays of clinical phase) increased b-Glucocerebrosidase activity, enhancing cognitive functions in patients with PD . For all these reasons, it would be interesting to analyze the levels of these lipid metabolites to understand if, as well as PC and PE, they are decreased in the liver of these GS-PD mice. Some limitations of this study should be addressed. To reduce the effect of estrogen modulations on metabolism, this study was performed only in male mice; however, a comparison could be made between the two genders. In addition, some metabolites of interest, such as ceramides and sphingomyelin, could not be analyzed, hence additional work may improve the information we have provided. The number of mice analyzed per group could be higher to enhance the robustness of the results; however, due to the high cost of this type of analysis in two different tissue samples and in three experimental groups, this sample size has not been allowed to increase. Overall, we intend to shed light on the general and specific metabolic changes in non-nervous tissues and thus understand if the liver may be at least partially responsible for the appearance of this neurodegenerative disease; however, it is essential to carry out experiments aimed at demonstrating any causal relationship between the liver disease, alteration, appearance and development of PD. Acknowledgments The authors are grateful to Maria Pura Delgado-Luceno and FUNDESALUD for helpful assistance. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Correlation analysis between the changes observed in striatal neurons of the genetic model of PD and acute intoxication compared to healthy mice (Control). Figure S2: Correlation analysis between the changes observed in hepatic cells of the genetic model of PD and acute intoxication compared to healthy mice (Control). Figure S3: Summary with the models used and the main metabolic results obtained in this work. Table S1: Metabolite changes in striatum cells from control and PD mouse models (GS-PD or ai-PD). Table S2: Metabolite changes in hepatic cells from control and PD mouse models (GS-PD or ai-PD). Click here for additional data file. Author Contributions Conceptualization, study design and data interpretation: J.M.F., J.M.B.-S.P., A.L.d.M., J.P.-T., A.P.-C. and G.K.; methodology: Y.C.N., S.M.S.Y.-D., P.M.-C., A.G.P., J.A.M.-G., M.N.-S., R.A.G.-P., E.U.-C., S.D., M.C.M., M.P.-B., E.A.-C. and S.C.-C.; formal analysis: L.M.G., S.D. and J.M.B.-S.P.; Literature search: J.M.F., J.M.B.-S.P., A.L.d.M., J.P.-T., A.P.-C. and G.K.; writing--original draft preparation, S.M.S.Y.-D., J.M.F. and J.M.B.-S.P.; writing--review and editing, S.M.S.Y.-D., Y.C.N., P.M.-C., L.M.G., A.G.P., J.A.M.-G., A.L.d.M., J.P.-T., A.P.-C., G.K., J.M.F., J.M.B.-S.P.; funding acquisition, J.M.F., A.L.d.M., J.P.-T. All authors agree to be responsible for all aspects of the work to ensure that questions relating to the accuracy or completeness of any part of the work are properly investigated and resolved. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Approval from the "Ethical Board" of Hospital Donostia (ALM-LRRK2-2016-01) and "Ethics Committee for Animal Experimentation" of the Biomedical Research Institute "Alberto Sols" (CSIC-UAM) in Madrid (Spain), in accordance with the European Communities Council Directive (2010/63/EEC) and national regulations (normative RD1386/2018) was obtained prior to the experiments. Informed Consent Statement Not applicable. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest G.K. has been holding research contracts with Daiichi Sankyo, Eleor, Kaleido, Lytix Pharma, PharmaMar, Osasuna Therapeutics, Samsara Therapeutics, Sanofi, Tollys and Vascage. G.K. has been consulting for Reithera. G.K. is on the Board of Directors of the Bristol Myers Squibb Foundation France. G.K. is a scientific co-founder of everImmune, Osasuna Therapeutics, Samsara Therapeutics and Therafast Bio. G.K. is on the scientific advisory boards of Hevolution, Institut Servier and Longevity Vision Funds. G.K. is the inventor of patents covering therapeutic targeting of aging, cancer, cystic fibrosis and metabolic disorders. G.K.'s wife, Laurence Zitvogel, has held research contracts with Glaxo Smyth Kline, Incyte, Lytix, Kaleido, Innovate Pharma, Daiichi Sankyo, Pilege, Merus, Transgene, 9 m, Tusk and Roche, was on the Board of Directors of Transgene, is a cofounder of everImmune, and holds patents covering the treatment of cancer and the therapeutic manipulation of the microbiota. G.K.'s brother, Romano Kroemer, was an employee of Sanofi and now consults for Boehringer Ingelheim. The funders had no role in the design of the study; in the writing of the manuscript, or in the decision to publish the results. The other authors declare no conflict of interest. Figure 1 Results of metabolic changes observed in striatum tissues for the control (Co) and parkinsonian genetic (GS-PD) or due to acute intoxication (ai-PD) groups (n = 5). (A) Heatmap with the average of the log2 area (+- standard error of the mean (SEM)) showed by metabolite groups (amino acids, nitrogen bases, carbohydrates, lipids, nucleosides, nucleotides, and organic compounds). (B,C) Volcano plot graphs are shown. The log2 FC shows changes observed on GS-PD model (B) or ai-PD model (C) by comparison to the control mice for each metabolite (represented by each dot). The -log10 p value represents non-significant (grey color) or significant (red represents significantly down-regulated metabolites, whereas green represents significantly up-regulated metabolites. (D) Correlation analysis between changes observed in striatal neurons of GS-PD compared to controls and ai-PD compared to controls. Statistical analysis was performed by obtaining p value (deg (p < 0.1), * (p < 0.05), ** (p < 0.01), **** (p < 0.0001)), and Pearson's correlation coefficient (R) between the noted changes. Figure 2 Results of metabolic changes observed in hepatic tissues for the control (Co) and parkinsonian genetic (GS-PD) or due to acute intoxication (ai-PD) groups (n = 4-5). (A) Heatmap with the average of the log2 area (+- standard error of the mean (SEM)) showed by metabolite groups (amino acids, nitrogenous bases, carbohydrates, lipids, nucleosides, nucleotides and organic compounds). (B,C) Volcano plot graphs are shown. The log2 FC indicates the changes observed on GS-PD model (B) or ai-PD model (C) in comparison to control mice for each metabolite (represented by each dot). The -log10 p value represents non-significant (grey color) or significant (red represents significantly down-regulated metabolites, whereas green represents significantly up-regulated metabolites. (D) Correlation analysis between changes observed in striatal neurons of GS-PD or ai-PD compared to controls. Statistical analysis was performed by obtaining p value (deg (p < 0.1), * (p < 0.05), ** (p < 0.01), *** p < 0.001), and Pearson's correlation coefficients (R) between the observed changes). Figure 3 Histograms showing the average (+- standard error of the mean (SEM)) of log2-fold change (Log2 FC) concentrations of different metabolites significantly decreased (A,B) or increased (C) in the liver of genetic (carrying the p.G2019S mutation in LRRK2; GS-PD) and acute intoxication PD (ai-PD) mouse models (n = 4-5). For statistical analyses, p-values were calculated by one-way ANOVA (analyzing the metabolites individually) and differences were evaluated as statistically significant when p-values were: deg (p < 0.1), * (p < 0.05) and ** (p < 0.01). Figure 4 Heatmaps showing the TTEST (p value) on the square above, and log 2-fold change (Log2 FC) on the square below for the different concentration of fatty acids (FA) (A), phospholipids in cell membranes (B) lipid-related metabolites (C) and bile acid metabolites (D) in the liver of WT group and genetic (carrying the p.G2019S mutation in LRRK2; GS-PD) and acute intoxication PD (ai-PD) mouse models (n = 4-5). For statistical data, p-values were estimated by one-way ANOVA (analyzing the metabolites separately) and differences were considered significant when p-values were: deg (p < 0.1), * (p < 0.05), ** (p < 0.01) and *** (p < 0.001). G, glycine; LC, long-chain; MC, medium-chain; PC, phosphatidylcholine; PE, phosphatidylethanolamine; T, taurine; VLC, very long-chain. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000530 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050793 cells-12-00793 Review Gut-Microbiota-Derived Metabolites Maintain Gut and Systemic Immune Homeostasis Wang Juanjuan 123+ Zhu Ningning 123+ Su Xiaomin 123+ Gao Yunhuan 123 Yang Rongcun 123* Giaroni Cristina Academic Editor 1 Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin 300071, China 2 Translational Medicine Institute, Affiliated Tianjin Union Medical Center of Nankai University, Nankai University, Tianjin 300071, China 3 State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China * Correspondence: [email protected] + These authors contributed equally to this work. 02 3 2023 3 2023 12 5 79326 1 2023 25 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The gut microbiota, including bacteria, archaea, fungi, viruses and phages, inhabits the gastrointestinal tract. This commensal microbiota can contribute to the regulation of host immune response and homeostasis. Alterations of the gut microbiota have been found in many immune-related diseases. The metabolites generated by specific microorganisms in the gut microbiota, such as short-chain fatty acids (SCFAs), tryptophan (Trp) and bile acid (BA) metabolites, not only affect genetic and epigenetic regulation but also impact metabolism in the immune cells, including immunosuppressive and inflammatory cells. The immunosuppressive cells (such as tolerogenic macrophages (tMacs), tolerogenic dendritic cells (tDCs), myeloid-derived suppressive cells (MDSCs), regulatory T cells (Tregs), regulatory B cells (Breg) and innate lymphocytes (ILCs)) and inflammatory cells (such as inflammatory Macs (iMacs), DCs, CD4 T helper (Th)1, CD4Th2, Th17, natural killer (NK) T cells, NK cells and neutrophils) can express different receptors for SCFAs, Trp and BA metabolites from different microorganisms. Activation of these receptors not only promotes the differentiation and function of immunosuppressive cells but also inhibits inflammatory cells, causing the reprogramming of the local and systemic immune system to maintain the homeostasis of the individuals. We here will summarize the recent advances in understanding the metabolism of SCFAs, Trp and BA in the gut microbiota and the effects of SCFAs, Trp and BA metabolites on gut and systemic immune homeostasis, especially on the differentiation and functions of the immune cells. gut microbiota SCFAs tryptophan metabolites bile acid metabolites tolerogenic macrophages regulatory T cells NSFC grants81901677 91842302 81970457 91629102 Tianjin Science and Technology Commission18JCZDJC35300 Ministry of Science and Technology2016YFC1303604 State Key Laboratory of Medicinal Chemical BiologyFundamental Research Funds for the Central University, Nankai University63191724 This research was supported by NSFC grants (grant number 81901677, 91842302, 81970457 and 91629102); the Tianjin Science and Technology Commission (grant number, 18JCZDJC35300); the Ministry of Science and Technology (grant number, 2016YFC1303604); the State Key Laboratory of Medicinal Chemical Biology and the Fundamental Research Funds for the Central University, Nankai University (63191724). pmc1. Introduction The gut microbiota is established at birth and evolves with age, and also maintains a commensal relationship with the host, being an integral part of the human body. The mammalian gastrointestinal tract harbors large amounts of different gut microbiota , including bacteria, archaea, fungi, viruses and phages. These gut microorganisms not only participate in food and energy metabolism but also contribute to the host immune response and homeostasis . The alteration of the gut microbiota can lead to the occurrence and development of many diseases . In recent years, with the rapid development of molecular biology, genomics, bioinformatics analyses and high-throughput sequencing techniques, great progress has been made in understanding the gut microbiota with diseases such as neurodegenerative diseases (Parkinson's disease and Alzheimer's disease), cardiovascular diseases (hypertension and atherosclerosis), metabolic diseases (obesity, diabetes, and non-alcoholic fatty liver disease (NAFLD)), and gastrointestinal diseases (inflammatory bowel diseases (IBD) and colorectal cancer (CRC)). These effects on the health of the host can occur through many ways such as energy absorption and the microbiota-gut-brain axis . However, the roles of altered gut microbiota in diseases are related to gut microbiota metabolites such as short-chain fatty acids (SCFAs), tryptophan (Trp) and bile acid (BA) metabolites from different microorganisms. The effects of gut microbiota metabolites on the local and systemic immunity have already attracted much attention. A growing body of clinical evidence has suggested an intricate relationship between the gut microbiota and the immune system. Most altered-gut-microbiota-mediated diseases are related to impaired immune responses . Gut-microbiota-derived metabolites not only affect genetic and epigenetic regulation but also impact the metabolism of the immune cells via their receptors in the immune cells . These metabolites from different microorganisms can not only promote the differentiation and function of immunosuppressive cells but also inhibit the inflammatory cells, together maintaining the gut and systemic immune homeostasis of the individuals . Since there are three main specific classes of metabolites, namely SCFAs, Trp and BA metabolites, that have been found in the gut microbiota so far, we here will summarize the recent advances in understanding the metabolism of SCFAs, Trp and BA in different microorganisms and the effects of SCFAs, Trp and BA metabolites on the gut and systemic immune homeostasis, especially on the differentiation and functions of immune cells. 2. Gut Microbiota and Metabolites 2.1. Gut Microbiota and Short-Chain Fatty Acids Short-chain fatty acids (SCFAs) are carboxylic acids produced from dietary fiber fermentation in the cecum and colon by gut bacteria (Table 1), mainly including acetate (C2), propionate (C3) and butyrate (C4). 2.2. Gut Microbiota and Tryptophan Metabolites Tryptophan (Trp) metabolism in the gut microbiota has been reviewed by us and others . Trp can be converted into various metabolites by the gut microbiota (Table 2) such as indole, indole-3-aldehyde (IAld), indole-3-acid-acetic (IAA), tryptamine, indoleacrylic acid (IA), indole ethanol (IE), indole-3-propionic acid (IPA), indole-3-acetaldehyde (IAAld) and 3-methylindole (skatole). Trp also produces kynurenine (Kyn) and downstream metabolites such as 3-hydroxykynurenine (3H-Kyn) and 3-hydroxyanthranilic acid (3-HAA) . 2.3. Gut Microbiota and Bile Acid Metabolites Two primary bile acids (BAs), i.e., cholic acid (CA) chenodeoxycholic acid (CDCA) are generated in the liver. These primary BAs can be conjugated, deconjugated and transformed into other metabolites in the gut microbiota (Table 3). Primary BAs are conjugated with glycine, taurine or other amino acids in hepatocytes and also in the gut microbiota. Conjugated BAs derived from the liver can be deconjugated in the gut microbiota through bile salt hydrolases (BSHs) in the small intestine . While BAs are deconjugated, BAs can be converted into secondary BAs, i.e., DCA and lithocholic acid (LCA). There are four distinct ways to transform BAs, including deconjugation, dehydroxylation, oxidation and epimerization in human . A range of oxo-, iso-derivatives by microbes is found, such as the oxo-bile acid metabolites 3-oxoLCA, 7-oxoCA, 7-oxoCDCA, 12-oxoCA and 12-oxoDCA , and others such as iso-LCA, 3-oxo-LCA, allo-LCA, 3-oxoallo-LCA, isoalloLCA, 3-ketoLCA, LCA acetate and LCA propionate . Chenodeoxycholic acid (CDCA) can be converted to UDCA and DCA to iso-DCA by 7a-hydroxysteroid dehydrogenase (7a-HSDH) and 7b-HSDH dehydrogenate . The metabolites of DCA, a 3b-hydroxydeoxycholic acid (isoDCA) has been also identified . However, more gut bacterium species that produce BA metabolites still need to be identified. 3. Receptors of Gut-Microbiota-Derived Metabolites in the Immune Cells 3.1. Receptors of Short-Chain Fatty Acids Several different ways such as passive diffusion, transporters and receptors help SCFAs enter cells. SCFA absorption can be promoted by the proton-coupled monocarboxylate-transporter 1 (MCT1) and the sodium-coupled monocarboxylate-transporter 1 (SMCT1) promote. Free-fatty acid receptor (FFAR) 2, G-protein coupled receptor (GPR) 43, FFAR3 (GPR41), hydroxycarboxylic acid receptor 2 (HCAR2) (also called GPR109a), Olfr-78 (OR51E2) in humans and Olfr-87 in mice can be activated by SCFAs . The SCFAs acetic, propionic and butyric acids mainly activate GPR43 and/or GPR41, whereas butyric and b-hydroxybutyric acids are stimulators of GPR109a. In addition, SCFAs, mainly propionic and butyric acids, also participate in the activation of the peroxisome proliferator-activated receptor g (PPARg) . 3.2. Receptors of Tryptophan Metabolites The aryl hydrocarbon receptor (AhR) can be activated by various endogenous and exogenous polycyclic aromatic hydrocarbon ligands such as Trp metabolites . This AhR can sense a wide range of intestinal signals, maintaining homeostasis between the gut microbiota and host . After activation, a complex of inactive AhRs located in the cytoplasm with the AhR nuclear translocator protein (ARNT) is formed and translocated to the nucleus to control transcriptional activity. Notably, AhR interactions with other proteins are only triggered by specific AhR ligands. This indicates that the specific protein complexes may be induced by different AhR ligands. For AhR activation, indole, skatole, IA, tryptamine, IPyA and indole-3-acetamide (IAM) are the most effective, but IAA, IAID, IPA and ILA are less active . Additionally, pregnant X receptor (PXR) can also be recognized by Trp metabolites . The Trp metabolite indole and its derivatives through AhR and PXR contribute to anti-inflammatory activities . 3.3. Receptors of Bile Acid Metabolites The receptors of BAs and their metabolites include nuclear and membrane receptors, which have been reviewed by Biagioli et al. . These receptors include nuclear receptors such as farnesoid X receptor (FXR), liver-X-receptor (LXR), vitamin D receptor (VDR), PXR, retinoid related orphan receptor (RORgt), constitutive androstane receptor (CAR) and cell membrane receptors such as G-protein BA receptor 1 (GPBAR1) (or Takeda G protein-coupled receptor 5 (TGR5)), cholinergic receptor muscarinic 2 and 3 (CHRM2, CHRM3), sphingosine-1-phosphate receptor 2 (S1PR2) and MAS-related GPR family member X4 (MRGPRX4) . 4. Effects of Gut-Microbiota-Derived Metabolites on the Immune Cells Gut-microbiota-derived SCFAs, Trp and BA metabolites exert a critical role in maintaining gut and systemic homeostasis through inhibiting inflammatory immune cells and promoting the differentiation and function of immunosuppressive cells 4.1. Tolerogenic and Inflammatory Macrophages Macrophages (Macs) are heterogeneous. Their phenotypes and functions can be regulated by the surrounding microenvironments. These cells are generally divided into two kinds, inflammatory (i) and tolerogenic (t, immunosuppressive) macrophages (tMacs). IMacs are involved in inflammatory immune responses, whereas tMacs suppress inflammation and retain homeostasis by producing a large amount of IL-10 and TGF-b. In the resting intestine, mature resident (tolerogenic) ly6clow/-CX3CR1hiMHCIIhi Macs from inflammatory Ly6chigh monocytes/Macs reside either within the lamina propria (LP) or the muscle layer to maintain intestinal homeostasis . LP Macs can be further subdivided into mucosal and submucosal Macs . The intestinal epithelium and vasculature in the intestines are lined by Mucosal Macs . Gut-microbiota-derived metabolites such as SCFAs, Trp and BA metabolites can promote the differentiation from iMacs to tMacs . SCFAs. SCFAs such as acetate (C2), propionate (C3) and butyrate (C4) exert an important role in maintaining immune homeostasis. Lipopolysaccharide (LPS)-mediated proinflammatory cytokines such as IL-6 could be inhibited by SCFAs. SCFAs could significantly reduce the histone deacetylase (HDAC) mRNA expression in monocytes and Macs . SCFAs, especially butyrate, also negatively regulate the inflammatory signaling pathway mediated by NLRP3 (NOD-like receptor thermal protein domain associated protein 3) to inhibit the activation of Macs . In addition, butyrate but not acetate or propionate can reprogram Mac metabolism toward oxidative phosphorylation to lead to an anti-inflammatory tolerogenic phenotype . Trp metabolites. Trp metabolites (Trps) have an important role in the differentiation and function of Macs through the receptor AhR . AhR-deficient mice were more sensitive to LPS-induced lethal shock and produced higher amounts of tumor necrosis factor (TNF)a, interleukin (IL)-6 and IL-12. AhR was also required for Salmonella typhimurium-caused immunopathology in LPS tolerant mice . In vitro studies showed that Trps-mediated suppression of inflammatory responses occurred through suppressing histamine production in the macrophages . Through inhibiting LPS-induced SP1 (specificity protein 1) phosphorylation in macrophages, the AhR-SP1 complex represses histidine decarboxylase expression . SP1 can bind to GC box elements (5'-GGGCGG-3') in the promoter region and is particularly important to TATA-less genes involved in the immune response . It has also been found that AhR down-regulation in human disease is related to an abnormal interaction between SP1 and the AhR promoter . The activation of AhR also results in a mitigated inflammatory response by LPS through a Ras-related protein Rac1 (ras-related C3 botulinum toxin substrate 1) ubiquitination-dependent mechanism, which can attenuate AKT (protein kinase B) signaling . In addition, the Kyn downstream metabolite 3-HAA inhibits the LPS-mediated PI3K (phosphatidylinositol 3 kinase)/Akt (protein kinase B)/mTOR (mammalian target of rapamycin) and NF-kB (nuclear factor k gene binding) signaling pathways and decreases the production of pro-inflammatory cytokines in the macrophages . The Trp metabolite receptor AhR can also inhibit the proliferation of myeloid precursor cells , drive DC differentiation over Macs and suppress human CD34+ hematopoietic precursor cells to differentiate into monocytes and Langerhans cells . BA metabolites. BA metabolites (BAs) are essential to maintain a tolerogenic phenotype of Macs via the BA receptor TGR5 (GPBAR1) . TGR5 can inhibit the release of cytokines from Macs after exposure to LPS. LPS-induced inflammation in the liver could be accelerated in TGR5-deficient mice, whereas the suppressive effects of TGR5 agonist on inflammatory cytokines could be abolished . TGR5 can also block NLRP3 inflammasome-dependent inflammation . Indeed, the TGR5 ligands and secondary BAs DCA and LCA can function as endogenous inhibitors of NLRP3 activation by activating TGR5-cAMP (adenosine monophosphate)-PKA (protein kinase A)-dependent ubiquitination of NLRP3 . The elevated intracellular cAMP levels can induce the phosphorylation and the ubiquitination of NLRP3 to block NLRP3-dependent inflammation and NLRP3-related metabolic disorders. TGR5 activation also promotes macrophage polarization to tolerogenic-phenotype Macs . The hierarchy is LCA > DCA > CDCA > UDCA > CA for TGR5 activation . In addition, FXR is also essential to maintain a tolegeronic phenotype of Macs as demonstrated in FXR knockout mice , and it is an important negative regulator of NLRP3 by directly interacting with NLRP3 and caspase-1 . FXR is recruited to iNOS (nitric oxide synthase) and IL-1b promoters and stabilizes nuclear receptor corepressor 1 (NCOR1) complexes on the promoters of these genes . Several pro-inflammatory genes such as iNOS, TNFa and IL-1b are marked by NCoR1 in promoter regions, which are linked to an NF-kB responsive element. FXR also activates SOCS3 (suppressor of cytokine signaling 3), CYP450 (Cytochrome P450) and FGF19 (fibroblast growth factor 19) to inhibit inflammation and SHP (Src homology-2 containing protein tyrosine phosphatase) to inhibit NF-kB, AP-1 (activator protein-1) and NLRP3 . PXR, a nuclear receptor, also binds to LCA . PXR activation can decrease the expression of IL6, TNFa and IL8 . 4.2. Tolerogenic Dendritic Cells Dendritic cells (DCs) link the innate and adaptive immune responses. DCs are divided into monocyte DCs (moDCs), plasmacytoid DCs (pDCs) and conventional DCs (cDCs). The cDCs can be further divided into two subsets, cDC1 and cDC2. DCs are the most efficient antigen-presenting cells and are necessary for the effective activation of naive T cells. However, DCs can also acquire tolerogenic functions such as conventional CD11c+ DCs expressing perforin (perf-DCs) and CD103+ DCs, which participate in the central and peripheral tolerance and the resolution of immune responses. Although DCs play distinct roles in shaping T cell development, differentiation and function, tolerogenic DCs (tDCs) mainly contribute to Treg differentiation and homeostasis . SCFAs. The SCFAs butyrate and propionate inhibit the activation of bone-marrow-derived DCs (BMDC) via suppressing the LPS-mediated expression of co-stimulatory molecules such as CD40 and the production of cytokines such as IL-6 and IL-12p40 . Through modulating DCs, the SCFA butyrate also suppresses colonic inflammation and carcinogenesis . Trp metabolites. Trp-metabolite-mediated AhR activation induces tDCs. These tDCs can limit T cell effective responses and promote the generation of Tregs. This may be because of NF-kB activation controlled by AhR, such as NF-kB expression and NF-kB/AhR protein interactions . However, the molecular mechanisms involved are mostly unknown. Notably, AhR activation can indeed boost DCs to foster FoxP3+ Treg differentiation. BA metabolites. The secondary BA DCA suppresses the LPS-induced expression of pro-inflammatory genes such as IL-6 in DCs . TGR5-deficient mice could recover LPS-induced expression of pro-inflammatory genes. TGR5 activation was found to induce the differentiation of human monocytes into IL-12 and TNF-a hypo-producing DCs . Studies showed that BA receptor TGR5-mediated inhibition occurred through the repression of NF-kB by TGR5-cAMP-PKA (protein kinase A) signaling . In addition, the secondary BA derivative isoDCA can also limit FXR activity in DCs and confer upon them an anti-inflammatory phenotype . INT-747/obeticholic acid, which could activate FXR , greatly attenuated the differentiation of CD14+ monocytes into mature DCs . A reduced number of activated DCs in the colon of mice administered with INT-747/obeticholic acid was also observed. The activation of the BA receptor VDR also inhibited the production of inflammatory cytokines and the maturation of DCs . 4.3. Regulatory T Cells Regulatory T cells (Tregs) play key roles in maintaining immune homeostasis. The differentiation and function of Tregs can be regulated by gut-microbiota-derived metabolites such as SCFAs, Trps and BAs . Tregs express transcription factor forkhead box protein 3 (Foxp3) and differentiate in the thymus or the periphery. These cells are the main obstacles in successful immunotherapy and active vaccination. However, other T regulatory cells such as Foxp3 negative interleukin (IL)-10 producing type 1 regulatory T cells (Tr1 cells) also play an important role in homeostasis. SCFAs. SCFAs can regulate T cell function through G-protein coupled receptor (GPR) , are crucial in maintaining intestinal epithelium physiology and have a direct role in inducing Tregs in the gut. They can promote the naive T cells toward Tregs . Since SCFAs can be transported into the circulation, SCFAs also have wider systemic effects. Indeed, increased Foxp3+Tregs can be observed in mice provided with SCFAs . The main mechanisms for SCFA-mediated Tregs include the G-protein coupled receptors (GPCRs) GPR41, GPR43 and GPR109A on the target cell surface mediating signaling and the inhibition of histone deacetylases (HDACs) to regulate gene expression . The inhibition of HDAC activity can enhance gene transcription by increasing histone acetylation. Butyrate also upregulates histone H3 acetylation of Foxp3 to promote the differentiation of Tregs . In addition, SCFAs such as butyrate can also condition mouse and human DCs to promote the differentiation of Tregs. After exposure to butyrate, DCs facilitate Foxp3+Treg differentiation and inhibit interferon (IFN)-g-producing cells through indoleamine 2,3-dioxygenase 1 (IDO1) and aldehyde dehydrogenase 1A2 (Aldh1A2) . Notably, SCFAs also promote the production of IL-10 in Th1, Th17 and Treg cells . Trp metabolites. Indole and its derivatives from Trp can regulate the differentiation and function of Tregs . The transcription factor Foxp3's expression in Tregs can be promoted, whereas RORg (retineic-acid-receptor-related orphan nuclear receptor gamma) in Th17 cells is inhibited by Trp metabolites. The AhR ligands 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), 2-(1'H-indole-3'-carbonyl)-thiazole-4-carboxylic acid methyl ester (ITE) and 4-n-nonylphenol are linked not only to differentiation but also to the functions of Tregs in mice and humans . The AhR activated with ITE could suppress IBD and improve encephalomyelitis (EAE) symptoms . Notably, AhR in the Tregs of spleen and lymph nodes is lower than that in the intestinal Tregs . In addition, Kyn in the gut microbiota could promote differentiation of Tregs . Mechanically, Kyn metabolites work through direct transactivation and epigenetic modifications to support Treg differentiation . Indeed, 3-HAA promotes the generation of Foxp3+Treg cells via nuclear coactivator 7 (NCOA7) . The Trp metabolite receptor AhR also promotes the development of Tr1 cells . During Tr1 cell differentiation, AhR is physically associated with c-Maf to activate IL-10 and IL-21 promoters to promote the differentiation of Tr1 cells . AhR activation also promotes hypoxia inducible factor-1 (HIF1)-a degradation and takes control of Tr1 cell metabolism . In addition, AhR can initiate the differentiation of mucosal-homing Tim3+Lag3+Tr1 cells . BA metabolites. BA metabolites (BAs) modulate the differentiation and function of Tregs . The bile acid derivatives isoalloLCA and 3-oxoLCA can promote the differentiation of Tregs. Mechanically, these derivatives promote the generation of mitochondrial reactive oxygen species (mitoROS) . Indeed, for their energy production, Tregs mainly rely on oxidative phosphorylation (oxPhos) after exposure to BA derivatives. The mitochondrial activities also promote Treg generation . Nuclear receptor subfamily 4, group A, member 1 (NR4A1) is also required for the isoalloLCA-induced Treg cells . IsoalloLCA can increase the binding of NR4A1 at the Foxp3 locus to enhance the expression of the Foxp3 gene . The composition of the gut BA pool also modulates the colonic Tregs expressing RORgt . Decreased RORgt+Tregs could be observed in the colon while BA metabolic pathways were genetically abolished in individual gut symbionts, whereas rescuing the intestinal BA pool increased colonic RORg+Treg cells and meanwhile also ameliorated the host susceptibility to colitis. Notably, the stability of the lineage-determining transcription factors RORg and Foxp3 in Th17 and Treg cells can be regulated by post-transcriptional modifications. In addition, the BA receptor VDR's activation promotes the induction of Tregs and reduces Th17 cell production . IsoDCA also induces the generation of Foxp3+Tregs after reducing DC stimulatory properties by ablating FXR in DCs . 4.4. T Helper 17 Cells Differentiation of T helper (Th) 17 cells from naive T cells is related to professional antigen-presenting cells (APCs) and cytokines including IL-6, IL-21 and TGFb. However, the differentiation of these cells is also affected by gut microbiota metabolites. These Th17 cells produce interleukin 17A (IL-17A), interleukin 17F (IL-17F), interleukin 21 (IL-21) and interleukin 22 (IL-22) . SCFAs. SCFAs are crucial factors of the mucosal immune responses . The gut microbiota can influence the differentiation of Tregs and Th17 cells . The disequilibrium of SCFAs from the gut microbiota can damage the balance of Treg/Th17 . The SCFA butyrate also decreased the proliferation and reduced the cytokine production of Th1, Th17 and Th22 cells . The peroxisome proliferator-activated receptor gamma (PPARg) and reprogrammed energy metabolism are involved in SCFA-mediated function in these cells . Trp metabolites. Trp metabolites suppress Th1 and Th17 . AhR of Trp metabolites plays a key role in Th17 cell differentiation. Indeed, IAA can decrease Th17 cells through activating AhR, downregulating RORgt and STAT3 (signal transducer and activator of transcription 3) . However, studies also showed that 6-formylindolo(3,2-b) carbazole (FICZ), a Trp product, could promote T cells into Th17 cells . BAs metabolites. Th17 and Treg cell differentiation can be controlled by BA metabolites (BAs) . 3-oxoLCA and isoalloLCA can reduce Th17 cell differentiation and increased Tregs in mice . Th17 cell differentiation can be inhibited by 3-oxoLCA through blocking the function of RORgt and directly binding to RORgt . Similar to 3-oxoLCA, isoLCA also suppressed Th17 cell differentiation by inhibiting RORgt . RORgt is selectively expressed by Th17 and innate lymphoid cell group 3 (ILC3). It is a critical for these cells' differentiation in chronic inflammation and autoimmune diseases . Indeed, RORgt inhibition not only reduces the frequencies of Th17 cells but also provides therapeutic benefits in intestinal inflammation . 4.5. CD4+Th1 and Th2 Cells CD4+Th1 cells are mainly responsible for cell-mediated immunity and produce interferon (IFN)-g, IL-2 and TNF-a, whereas Th2 cells are involved in antibody production and produce IL-4, IL-5, IL-10 and IL-13 cytokines. Although T-bet and GATA binding protein 3 (GATA3) are master transcription factors for the differentiation of Th1 and Th2 cells, respectively, their differentiation and heterogeneity are usually determined by combinatorial transcription factors. SCFAs. DCs from mice treated with the SCFA propionate have an impaired ability to initiate Th2 cells . These DCs have a reduced expression of CD40, programmed cell death ligand 2 (PD-L2) and CD86. Notably, SCFAs can promote the microbiota's antigen-specific IL-10 production in Th1 cells through GPR43. Mechanistically, SCFAs upregulate transcription factor B lymphocyte-induced maturation protein 1 (Blimp-1). However, SCFAs also have the potential to induce inflammatory responses . SCFAs can induce Th1 and Th17 cells upon exposure to immunological challenges. A high concentration of butyrate also induces Th1 transcription factor T-bet expression. Trp metabolites. Many patients with cancer often show decreased plasma Trp levels in parallel with an elevated Th1 type immune activation marker. Oral Trp supplementation suppresses antigen-specific Th1 responses at subtoxic concentrations . Through IDO1-mediated Trp catabolism, synovial fibroblasts can also selectively suppress Th1 cell responses . BA metabolites. Upon exposure to BAs, CD4+ T cells can maintain gut homeostasis . Pols et al. revealed that unconjugated LCA inhibited the activation of primary human and mouse CD4+ Th1 cells to reduce TNFa and INFg production through a BA receptor VDR-dependent mechanism . A shift from Th1 to Th2 cells could be promoted by BA receptor VDR activation through c-Maf and GATA-3 . A decreased number of liver-infiltrating CD4+ Th1 cells is associated with a good response of patients with primary biliary cholangitis to UDCA treatment. In addition, PXR activation also inhibits T cell proliferation in both mouse and human T cells in vitro. However, CXCR5+CD4+ T follicular helper cells could be induced by BA metabolism to cause neuromyelitis optica spectrum disorder . 4.6. Regulatory B Cells Regulatory B (Breg) cells are immunosuppressive cells that support immunological tolerance. Breg cells have multiple subsets, including immature and mature B cells, which can express IL-10, IL-35 and/or TGF-b and surface molecules such as CD9, CD1d, CD21, CD23, CD24, CD5, CD138, TIM (T cell immunoglobulin and mucin domain-1) and/or PD-L1/L2. In addition, other Breg cell subsets have also been reported such as CD1dhighCD21highCD23+ MZ (marginal zone) precursor B cells, CD1dhighCD5+ CD1dhigh CD21highCD23IgMhighIgD-MZ B cells and CD25+CD69+ CD72highCD185-CD196+IgM+IgD+B cells. These cells suppress immunopathology through the production of IL-10, IL-35 and TGF-b cytokines. SCFAs. Rosser and colleagues recently showed that butyrate could divert Trp metabolism toward the serotonin pathway and the production of 5-hydroxyindole-3-acetic acid (5-HIAA) . 5-HIAA activates AhR in Bregs, mediating the suppressive effect in a rheumatoid arthritis model in vivo . The administration of SCFAs also improved rheumatoid arthritis (RA) symptoms and increased the Breg frequency . Trp metabolites. B cell differentiation, maturation and activation can be regulated by the Trp metabolite receptor AhR . AhR activation regulates the differentiation and function of IL-10-producing CD19+CD21highCD24highBregs . AhR-deficient mice develop exacerbated arthritis with significant reductions in IL-10-producing Bregs. Our study showed that in the presence of LPS, IAA by gut microbiota could activate the transcription factors PXR, CAR and NF-kB to induce the generation of IL-35+ Breg cells . Others also found that LPS increased the expression of p35 and Ebi3 in B cells isolated from mice . The transcription factor NF-kB promoted influenza A virus (IAV)-mediated IL-35 . 4.7. B Cells B cells play a key role in the responses to microbial infections and pathogen clearance. These B cells not only produce antibodies but also release a broad variety of cytokines. BA-metabolite-mediated VDR activation reduces the ongoing proliferation of B lymphocytes , induces activated B cell apoptosis and inhibits Ig production . However, SCFAs can also stimulate glycolysis in B cells via mTOR activation. SCFA-derived acetyl-CoA is crucial for plasma cell differentiation and antibody production . SCFAs also can promote the secretion of IgA by B cells . The activation of Trp metabolism is related to flavivirus-mediating B cell differentiation into antibody-secreting cells in humans . 4.8. Myeloid-Derived Suppressor Cells Myeloid-derived suppressor cells (MDSCs) are most commonly immunosuppressive cells during chronic inflammation, especially late-stage cancers. These cells consist of two large groups of cells termed granulocytic or polymorphonuclear (PMN)-MDSCs and monocytic (M)-MDSCs. In humans, the total MDSCs are characterized by HLA-DRlow/negLinlow/negCD33posCD11bpos. PMN-MDSCs are identified with negative CD14 or positive CD15, whereas M-MDSCs are identified with positive CD14 or negative CD15 . They use different mechanisms for immunosuppression. PMN-MDSCs mainly suppress T cell responses by producing ROS (reactive oxygen species), whereas M-MDSCs produce high amounts of NO (nitrogen oxide), Arg-1 and immunosuppressive cytokines such as IL-10, which suppress both antigen-specific and non-specific T cell responses . M-MDSCs have higher suppressive activity than G-MDSCs. Taurodeoxycholate (TDCA) can increase the number of PMN-MDSCs in the spleen of septic mice . 4.9. Innate Lymphoid Cells There are three different groups of innate lymphoid cells (ILCs), namely, ILC1s, ILC2s and ILC3s, but only ILC3s are IL-22 producers . IL-22 is crucial for the maintenance of intestinal epithelial cells (IECs) and the defense against pathogens . It belongs to an IL-10 family cytokine . The gut microbiota has profound effects on the differentiation and functions of ILCs. Trp metabolites. Trp metabolites play a critical role in the development of ILC3s. AhR activation is essential for IL-22 production in ILC3s through AhR ligands from the microbiota . Trp metabolites are involved in mucosal immunity through AhR modulation. An impaired AhR activity in AhR knockout mice was related to reducing ILC3 and aggravating inflammatory diseases . The disruption of gut-microbiota-related Trp metabolism results in reduced IL-22 in the intestinal tract, whereas the activation of AhR in ILC3 promotes IL-22 production, thereby modulating the intestinal immune response and protecting the function of the intestinal barrier. AhR also plays an important role in the differentiation of ILC3s . Especially in the early stage after birth, AhR ligands are required for the differentiation of IL-22-producing ILC3s . Mechanically, AhR not only participates in RORgt-mediated ILC3 development but also mediates Notch and c-Kit expression . Notably, reduced AhR signaling can cause alterations between ILC3 and ILC1 cellular populations. In addition, AhR can also cause IL-22 expression in the Th17 cells . 4.10. CD8+ T Cells Naive CD8+ T cells can produce a large number of effector cells to fight infections or tumors after antigen stimulation. SCFAs. The SCFAs butyrate and propionate regulate CD8+ T cell activation via inhibiting IL-12 production in DCs. However, microbiota-derived SCFAs can boost CD8+ T cell functions by modifying the cellular metabolism . The anti-tumor functions of cytotoxic T lymphocytes (CTLs) and chimeric antigen receptor (CAR) T cells can be significantly enhanced by pentanoate and butyrate . Through regulating mTOR activity and cellular metabolism, acetate also promotes IFN-g production in CD8+ T cells. Trp metabolites. Kyn can upregulate the expression of PD-1 in CD8+T cells through interacting with the ligand-activated AhR , which mediates immunosuppressive responses. 3-HAA from the Kyn pathway causes immune suppression by inducing apoptosis in T cells through glutathione depletion . However, Trp metabolites can promote CD8+T cells to induce apoptosis of co-cultured cancer cells, increase cancer-infiltrating CD8+T cells and suppress tumor growth of lung cancer in mice . BA metabolites. BA metabolites can disrupt intracellular calcium homeostasis, which is essential for NFAT (nuclear factor of activated T cells) signaling and T cell activation . 24-Norursodeoxycholic acid (NorUDCA) changes immunometabolism in CD8+ T cells and alleviates hepatic inflammation . It has strong immunomodulatory efficacy in CD8+T cells, which affect lymphoblastogenesis, expansion, glycolysis and target of rapamycin complex 1 (mTORC1) signaling. BA receptor VDR activation also reduces the ongoing proliferation of T lymphocytes . 4.11. Natural Killer Cells Natural killer (NK) cells, as a first line of defense against cancer, are powerful effectors of innate immunity. These cells can express an array of receptors to eliminate tumor cells. Kyn metabolites, particularly Kyn itself, can suppress the activity of NK cells and cause cell death via a ROS pathway in NK cells . These Kyn metabolites can prevent the cytokine-mediated upregulation of the specific triggering receptors responsible for NK-cell-mediated killing . 4.12. NKT Cells NKT cells, an unusual population of T cells, can recognize lipids presented by CD1d. Gut-microbiome-mediated BA metabolism regulates liver cancer via NKT cells . CXCL16 expression of liver sinusoidal endothelial cells regulated by BA can control the accumulation of NKT cells . The activation of the BA receptor FXR can result in a profound inhibition to produce a potent pro-inflammatory mediator osteopontin in NKT cells . 4.13. Neutrophils Neutrophils play a critical role in the host defense against infection. SCFA-mediated activation of GPR43 can induce the neutrophils to inflammatory sites and enhance their phagocytosis . However, pro-inflammatory cytokine production such as TNFa in neutrophils can be inhibited by SCFAs . SCFAs also affect neutrophil-mediated anti-HIV responses . Serum BAs in liver cirrhosis promote neutrophil dysfunction . Sphingosine-1-phosphate receptor (S1PR) can reduce neutrophil aggregation . In addition, the Trp metabolite indole suppresses neutrophil myeloperoxidase to diminish bystander tissue damage . 4.14. CD4+CD8aa+ Cells The intestinal epithelium contains a unique population of CD4+CD8aa+ T cells . These CD4+CD8aa+ T cells can promote gut tolerance to dietary antigens . They can be found in the intestine of mice colonized with L. reuteri. Through Trp-metabolite-mediated AhR activation, L. reuteri can reprogram CD4+ T cells into CD4+CD8aa+ cells in the gut . CD4+CD8aa+ IELs can resist apoptosis and upregulate IL-15 and IL-10 in a colitis model . 5. Gut-Microbiota-Derived Metabolites and Immune-Associated Disorders Gut-microbiota-derived SCFAs, Trp and BA metabolites have been widely related with intestinal and extra-intestinal disorders such as inflammatory bowel diseases (IBDs), chronic liver diseases, metabolic syndrome, diabetes and cancer . Gut-microbiota-derived metabolites play a key role in inflammatory bowel disease (IBD) . Metabolite disturbances including BAs and short-chain fatty acids (SCFAs) have been reported in patients with IBDs . Ursodeoxycholic acid reduces the severity of intestinal inflammation in a DSS-induced mouse model of colitis . Longitudinal analyses also demonstrated that certain metabolites such as tryptophan metabolites were decreased in coeliac disease . The indole metabolites are dysregulated in patients with active IBD and in mouse models of colitis, and the restoration of depleted indoles reduces disease severity . The metabolites from the gut microbiota can modulate the development and progression of non-alcoholic fatty liver disease (NAFLD) . Tryptophan-derived microbial metabolites activate the aryl hydrocarbon receptor in tumor-associated macrophages to suppress anti-tumor immunity . Interventional studies with certain bacterial strains such as Akkermansia muciniphila have shown effects on obesity-related parameters . The tryptophan-derived metabolite IAA induces the generation of IL-35+B cells through PXR and TLR4 to inhibit obesity in mice . Thus, the manipulation of the gut microbiota may impact the immune system and improve immune-mediated disorders. An increasing number of studies has reported the use of fecal microbiota transplantation (FMT) for the treatment of diseases such as metabolic syndrome, diabetes, multiple sclerosis, psoriasis, Crohn's disease, cancer and Parkinson's disease . Typically, the modulation of the gut microbiota with the FMT method has successfully cured patients with refractory immune-checkpoint-inhibitor-associated colitis . Notably, the composition of the gut microbiota in immunosuppressed patients such as allogeneic hematopoietic-cell transplantation is changed, which is characterized by a loss of diversity and domination by single taxa . However, a large body of evidence has also shown that the importance of the intestinal microbiota in immunosuppressed patients. Fecal microbiota transplantation (FMT) in immunocompromised cohorts can provide protection against bacterial translocation via the introduction of a diverse microbiome and restoration of epithelial defenses . Promoting microbial diversity via FMT is also likely to enhance natural barrier defenses, including anti-microbial peptides, tight junction assembly/integrity, mucus production and epithelial proliferation . In addition, exclusive enteral nutrition may also cultivate the presence of beneficial microbiota and improve BA metabolism, possibly influencing disease and immune activity . Several nutritional therapies have been designed not only to treat the nutritional deficiencies seen in children with active Crohn's disease (CD) but also to correct dysbiosis and reduce intestinal inflammation . Multi-donor FMT with an anti-inflammatory diet effectively induced deep remission in mild-moderate ulcerative colitis . 6. Conclusions and Perspectives The gut microbiota harbors trillions of microorganisms in the human digestive system. These microorganisms affect the gut and systemic immunity via their metabolites such as SCFAs, Trp and BA metabolites to maintain gut and systemic homeostasis. The alteration of the gut microbiota/metabolites can lead to the onset of many diseases ranging from gastrointestinal and metabolic conditions to neuropsychiatric diseases and cancers. The effects of gut microbiota metabolites on different immune cells have important consequences not only in the onset and development of diseases but also in the diagnosis and therapy of these diseases and predictions of clinical outcomes, prognosis and immunotherapy responses such as cancer immune checkpoint blockade. With the rapid development of recent techniques, more bacterial strains to produce the metabolites (including SCFAs, Trp and BA metabolites) remain to be identified. This will be beneficial for understanding different diseases and designing targeted strategies to control the production of the metabolites for the therapy of these diseases. However, several critical techniques need to be overcome to find more gut-microbiota-derived metabolites that are potentially related to diseases. (1) Discovery of new culture method(s) for gut microbiota. A key question for gut microbiota metabolites is whether gut microorganisms can be successfully cultured in vitro. The discovery of any new culture technique will be beneficial to the identification of gut microbiota metabolites. (2) Improvement of the metabolite analyses. For currently targeted metabolomics, the restricted standard samples have limited application, whereas for untargeted metabolomics, it is easy to produce "false positive" data. (3) Synthesis of gut microbiota metabolites. Some metabolites from the gut microbiota need to be synthesized for their functions and application. (4) Determination of immune cell subset function. With the development of single-cell sequencing techniques, more immune cell subpopulations related to the gut microbiota or metabolites will be identified. However, the functional potential of these immune cell subsets remains to be determined. (5) Establishment of new animal models. Some gut microbiota metabolites may exert their function through new mechanism(s), including receptor, signal pathway, genetic and epigenetic modification and metabolism. All of these need new animal models to explain how the metabolites exert their effects on the immune cells and/or diseases. Author Contributions J.W., N.Z., X.S. and Y.G. made the figures and wrote the original manuscript. R.Y. improved and wrote the final manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement All data generated or analyzed during this study are included in this published article. Conflicts of Interest The authors have no conflict of interest to disclose. Figure 1 The gut microbiota maintains the homeostasis of the gut and systemic immune system through the metabolites. Metabolites from the gut microbiota such as short-chain fatty acids (SCFAs), tryptophan metabolites (Trps), and bile acid metabolites (BAs) promote the differentiation and function of immune-suppressive cells and inhibit the inflammatory cells. DC, dendritic cell; iMac, inflammatory macrophage; Th1, T helper 1; Th2, T helper 2; Th17, T helper 17; NK, natural killer cell; NKT, natural killer T cell; MDSC, myeloid-derived suppressor cell; tMac, tolerogenic macrophage; tDC, tolerogenic dendritic cell; Treg, regulatory T cells; Tr1, type 1 regulatory T cells; Breg, regulatory B cell; ILC3, innate lymphoid cell 3; CD8aa, CD4+CD8aa+ intestinal intraepithelial lymphocyte. Figure 2 Regulation of gut-microbiota-derived metabolites in different immune cells. Gut-microbiota-derived metabolites such as SCFAs, Trp and BA metabolites can promote differentiation and function of immune-suppressive cells (such as tolerogenic macrophages (tMacs), tolerogenic dendritic cells (tDCs), myeloid-derived suppressor cells (MDSCs), T regulatory Foxp3+ cells (Treg), type 1 regulatory T cells (Tr1), B regulatory cells (Breg), innate lymphoid cells (ILCs) and CD4+CD8+aa cells), and inhibit inflammatory cells (such as CD4+T helper (Th1), CD4+Th2, CD4+Th17, CD8, B cells, natural killer (NK) cells, NKT cells and neutrophils). Figure 3 Gut-microbiota-derived metabolites promote the differentiation and function of tolerogenic macrophages through the receptors expressed in the macrophages such as short-chain fatty acids (SCFAs) through membrane receptors such as GPR43, tryptophan metabolites (Trps) through the AhR nuclear receptor and bile acid metabolites (BAs) through the TGR5 membrane receptor and/or FXR nuclear receptor. iMac, inflammatory macrophages; tMacs, tolerogenic macrophages; TGR5, Takeda G protein-coupled receptor 5; FXR, farnesoid X receptor; PXR, pregnane X receptor; NCOR1, nuclear receptor corepressor 1; cAMP, adenosine monophosphate; PKA, protein kinase A; SOCS3, suppressor of cytokine signaling 3; CYP450, cytochrome P450; FGF19, fibroblast growth factor 19; NLRP3, NOD-like receptor thermal protein domain associated protein 3; GPR43, G-protein coupled receptor 43; HDAC, histone deacetylase; NF-kB, nuclear factor-kappa B; PI3K, phosphatidylinositol 3 kinase; Akt, protein kinase B; mTOR, mammalian target of rapamycin; TLR4, Toll-like receptor 4; 3-HAA, 3-hydroxyanthranilic acid; SP1, specificity protein 1; His, histamine; AhR, aryl hydrocarbon receptor; Rac1, ras-related C3 botulinum toxin substrate 1; mIL-1b, mature interleukin -1b; TNFa, tumor necrosis factor a. Figure 4 Gut-microbiota-derived metabolites promote differentiation of Treg, Tr1 and RORgt+ Treg cells. SCFAs, short-chain fatty acids; Trps, tryptophan metabolites; BAs, bile acid metabolites; GPR43, G-protein coupled receptor 43; HDAC, histone deacetylase; Foxp3, forkhead box protein p3; IDO, indoleamine 2,3-dioxygenase 1; Aldh1A2, aldehyde dehydrogenase 1A2; AhR, aryl hydrocarbon receptor; 3-HAA, 3-hydroxyanthranilic acid; Kyn, kynurenine; mitoROS, mitochondrial reactive oxygen species; NR4A1, nuclear receptor subfamily 4, group A, member 1; RORgt, retinoid-related orphan receptor-gt; VDR, vitamin D receptor; FXR, farnesoid X receptor; LCA, lithocholic acid; DCA, deoxycholic acid; DC, dendritic cells; Tr1, type 1 regulatory T cells. cells-12-00793-t001_Table 1 Table 1 Gut microbiota species and short-chain fatty acids. SCFAs Biosynthesis Bacterial Species References Acetate (C2) Via acetyl-CoA pathway Via Wood-Ljungdahl pathway Akkermansia muciniphila, Bacteroides spp., Bifidobacterium spp., Prevotella spp., Ruminococcus spp Blautia hydrogenotrophica, Clostridium spp., Streptococcus spp. Popionate (C3) From succinate pathway From acrylate pathway From propanediol pathway Bacteroides spp., Phascolarctobacterium succinatutens, Dialister spp., Veillonella spp., Roseburia spp., Firmicutes, Roseburia inulinivorans, Ruminucocus spp., Clostridium spp., Eubacterium spp., Coprococcus spp., and Akkermansia muciniphila, Megasphaera elsdenii, Coprococcus catus, Clostridiales bacterium. Coproccus catus and Clostridium spp. Salmonella spp., Roseburia inulinivorans, Ruminococcus obeum, Eubacterium halli Butyrate (C4) From butyryl-CoA acetate Co-A transferase pathway From butyrate kinase pathwayFrom lactate and acetate Anaerostipes spp., Coprococcus catus, Eubacterium rectale, Eubacterium hallii, Faecalibacterium prausnitzii, Roseburia spp., Roseburia intestinalis, Roseburia insulinivorans, Clostridiales bacterium, Anaerostripes spp, Coprococcu spp., Costridium symbiosum and Faecalibacterium prasnitzii. Coprococcus comes and Coprococcus eutactus. Eubacterium hallii and Anaerostipes spp cells-12-00793-t002_Table 2 Table 2 Gut microbiota species and tryptophan metabolites. Metabolite Biosynthesis Bacterial Species References Indole Form Trp metabolism by tryptophanase Clostridium limosum, Bacteroides ovatus, Enterococcus faecalis and Escheichia coli IAA From Trp metabolism through the oxidative and reductive pathways by tryptophan 2-monooxygenase or acyl-CoA dehydrogenase Clostridium sporogenes Clostridium bartlettii and Bifidobacterium spp. IPA From Trp metabolism through the oxidative and reductive pathways by tryptophan 2-monooxygenase or acyl-CoA dehydrogenase and via phenyllactate dehydratae and acyl-CoA dehydrogenase Clostridium sporogenes Clostridium bartlettii and Bifidobacterium spp. and Peptostreptococcus spp IA From Trp metabolism via phenyllactate dehydratae and acyl-CoA dehydrogenase Peptostreptococcus spp. Skatole From Trp metabolism by decarboxylation of IAA Bacteroides spp. and Clostridium spp. IA1d From Trp metabolism via an aromatic amino acid aminotransferase (ArAT) and indolelactic acid dehydrogenase (ILDH) Lactobacillus johnsonii, L. reuteri, L. acidophilus and L. murinus Tryptamine From Trp metabolism via a Trp decarboxylase enzyme Ruminococcus gnavus and Clostridium sporogenes. 3-hydroxyanthranilic acid (3-HAA) From Trp metabolism via eukaryotic Kyn pathway Pseudomonas, Burkholderia, Stenotrophomonas, Xanthomonas, Shewanella, and Bacillus cells-12-00793-t003_Table 3 Table 3 Gut microbiota species and bile acid metabolites. Bile Acids (BAs) Biosynthesis Bacterial Species References Conjugated BAs From primary BAs to conjugate with other amino acids Clostridium bolteae, Bacteriodetes Bacteroides vulgatus, Firmicutes Lactobcillus rumini, Actinobacteria Hungatella hathewayi, Bacterorides vulgatus, Lactobacillus ruminis, Holdemania filiformis, Clostridium scindens Deconjugated BAs Via deconjugating by bile salt hydrolases (BSHs) Lactobacillus spp., Clostridium spp., Bifidobacterium spp., Enterococcus spp., and Bacteroides spp. Secondary BAs (DCA, LCA) From deconjugated BAs through deconjugation, dehydroxylation, oxidation and epimerization Clostridium clusters XIVa, IV, XI, C. scindens, C. hylemonae and C. perfringens, Blautia producta, Eggerthella lenta, Clostridium scindens. 3-oxoLCA and isoLCA Convert LCA to 3-oxoLCA and isoLCA Adlercreutzia, Bifidobacterium, Enterocloster, Clostridium, Collinsella, Eggerthella, Gordonibacter, Monoglobus, Peptoniphilus, Phocea, Raoultibacter, and Mediterraneibacte Ursodeoxycholic acid (UDCA) Conversion of 7-oxo-LCA Clostridium absonum, Stenotrophomonas maltophilia, Ruminococcus gnavus and Collinsella aerofaciens UDCA Conversion of 7a-epimerization Clostridium baratii Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000531 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050737 cells-12-00737 Article Twenty Novel MicroRNAs in the Aqueous Humor of Pseudoexfoliation Glaucoma Patients Czop Marcin Conceptualization Methodology Software Formal analysis Investigation Data curation Writing - original draft Writing - review & editing Visualization 1*+ Gasinska Karolina Conceptualization Methodology Software Formal analysis Investigation Writing - original draft Writing - review & editing 2+ Kosior-Jarecka Ewa Conceptualization Methodology Investigation Writing - review & editing 2 Wrobel-Dudzinska Dominika Conceptualization Methodology Investigation Writing - review & editing 2 Kocki Janusz Conceptualization Investigation Writing - review & editing Supervision 1++ Zarnowski Tomasz Investigation Writing - review & editing Supervision 2++ Larrivee Bruno Academic Editor Liu Yongqing Academic Editor 1 Department of Clinical Genetics, Medical University of Lublin, 20080 Lublin, Poland 2 Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin, 20079 Lublin, Poland * Correspondence: [email protected] + These authors contributed equally to this work. ++ These authors contributed equally to this work. 24 2 2023 3 2023 12 5 73708 2 2023 22 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The microRNAs (miRNAs) are short non-coding RNAs (19-25 nt) that regulate the level of gene expression at the post-transcriptional stage. Altered miRNAs expression can lead to the development of various diseases, e.g., pseudoexfoliation glaucoma (PEXG). In this study, we assessed the levels of miRNA expression in the aqueous humor of PEXG patients using the expression microarray method. Twenty new miRNA molecules have been selected as having the potential to be associated with the development or progression of PEXG. Ten miRNAs were downregulated in PEXG (hsa-miR-95-5p, hsa-miR-515-3p, hsa-mir-802, hsa-miR-1205, hsa-miR-3660, hsa-mir-3683, hsa -mir-3936, hsa-miR-4774-5p, hsa-miR-6509-3p, hsa-miR-7843-3p) and ten miRNAs were upregulated in PEXG (hsa-miR-202 -3p, hsa-miR-3622a-3p, hsa-mir-4329, hsa-miR-4524a-3p, hsa-miR-4655-5p, hsa-mir-6071, hsa-mir-6723-5p, hsa-miR-6847-5p, hsa-miR-8074, and hsa-miR-8083). Functional analysis and enrichment analysis showed that the mechanisms that can be regulated by these miRNAs are: extracellular matrix (ECM) imbalance, cell apoptosis (possibly retinal ganglion cells (RGCs)), autophagy, and elevated calcium cation levels. Nevertheless, the exact molecular basis of PEXG is unknown and further research is required on this topic. miRNA aqueous humor pseudoexfoliation glaucoma PEXG glaucoma pseudoexfoliation syndrome PEX This research received no external funding. pmc1. Introduction Glaucoma is a group of multifactorial eye diseases that result in progressive irreversible damage to the optic nerve and cause vision loss, and is considered the second leading cause of blindness in the world . The basic process in the pathophysiology of glaucoma is the loss of retinal ganglion cells (RGCs) and their axons, which leads to changes in the morphology of the optic disc and consequently to visual field defects. The main risk factor for glaucoma is increased intraocular pressure (IOP), caused by an imbalance between the production and outflow of aqueous humor (AH) from the anterior chamber . The most important outflow pathway is trabecular meshwork (TM), which consists of trabecular cells surrounded by the extracellular matrix (ECM). Dysfunction in the normal homeostatic process leads to increased outflow resistance and elevated IOP . Lowering IOP is the only treatment that prevents the progression of vision loss . Pseudoexfoliation glaucoma (PEXG) is a type of secondary open-angle glaucoma, developing usually over 50 years of age in the course of pseudoexfoliation syndrome (PEX). The prognosis is worse than for primary open-angle glaucoma (POAG) due to higher IOP values and greater fluctuations. PEX was first described in 1917 by Finnish ophthalmologist, John Linberg . It's a chronic, age-related systemic disorder, with variable prevalence among men and women in different studies . Pathognomonic eye symptoms are gray-white deposits in the anterior segment of the eyeball (corneal endothelium, trabecular meshwork, pupillary margin, iris pigment epithelium, dilator muscle of the iris, iris blood vessels, ciliary epithelium, lens epithelium, lens capsule, zonules) and periorbital tissues (conjunctiva, Tenon's capsule, orbital septa, extraocular muscles) . PEX material can also be found in many internal organs (heart, lungs, liver, kidneys, gallbladder, blood vessels, cerebral meninges) and skin . The deposits are the result of increased production or reduced turnover of ECM . They are composed of elastic fibers (elastin, tropoelastin, amyloid P, fibrillin-1, fibulin-2, vitronectin, fibronectin, lysyl oxidase, clusterin, LTBP-1, LTBP-2, and other proteins) and noncollagenous basement membrane materials (laminin) which form fibrils. They are coated with glycosaminoglycans (heparan sulfate, chondroitin sulfate, dermatan sulfate, and hyaluronic acid) . Mechanisms leading to the development of PEX may include oxidative stress, hypoperfusion, and hypoxia . Previous studies revealed many genes that can be related to PEX (APOE, CACNA1A, CLU, CNTNAP2, FBLN5, GST, LOXL1, MMP1, MMP3, TNF, TMEM136) by participating in the formation of PEX material, regulation of trabecular cells and ECM proteins . Gene expression is a complex process in which microRNAs (miRNAs) are involved. Many miRNAs show a tissue-specific expression pattern and can be identified in eye tissues and fluids, but the role of miRNAs in glaucoma and PEXG is not well understood . MiRNAs are short non-coding RNAs (19-25 nt) that regulate the level of protein expression at the post-transcriptional level. These molecules are responsible for the regulation of many physiological cellular processes, including division, cell differentiation, and regeneration, but also for many pathological processes such as neoplastic transformation. MiRNAs are found both in the cell and in extracellular fluids, i.e., plasma, urine, and aqueous humor . MiRNAs are transcribed in a similar way to protein genes. The first step in the expression of a gene encoding miRNA is the synthesis of primary miRNA (several hundred nucleotides long), which are then modified in the nucleus at both ends of the RNA. The next stage of miRNA maturation takes place in the cytoplasm and, as a consequence, a pre-miRNA of about 70 nucleotides is formed, followed by the production of mature micro RNA. The functioning of micro RNA is closely related to the RNA-induced silencing complex (RISC). Both molecules linked together to interact with the target mRNA through partial complementarity of the sequence of one of the miRNA strands, leading to degradation of the target mRNA through the activity of the RISC complex. By analyzing the level of miRNA expression, it is possible to draw conclusions about the pathomechanism of the studied diseases and to use them as biomarkers of these diseases . The most important features of biomarkers are: specificity for the disease entity, the possibility of quick, easy, and safe determination, and the possibility of obtaining accurate results . The aim of the study was to assess the levels of miRNA expression in a group of patients with PEXG and to look for mechanisms caused by altered expression of miRNA that may be related to this disease. 2. Materials and Methods 2.1. Study Groups Eighteen western descent patients underwent routine cataract surgery at the Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin (Poland) (nine PEXG and nine age-matched control patients). Prior to the surgery, all of the patients underwent the ophthalmic examination including best-corrected visual acuity (BCVA) assessed with Snellen charts, an IOP test measured by Goldmann applanation tonometry (GAT), gonioscopy, a slit-lamp examination, indirect ophthalmoscopy after pupil dilation with a stereoscopic optic nerve head assessment, optical coherence tomography (Carl Zeiss Cirrus HD-OCT 5000), and standard automated perimetry (SAP) (24-2 strategy using the Humphrey perimeter). Inclusion criteria in the study group:(1) Incipient senile cataract: cloudy area in the lens that causes decreased vision. (2) PEX syndrome: typical deposits of white powdery material observed along the pupillary margin and on the peripheral lens capsule. (3) Glaucomatous optic neuropathy: elevated IOP of greater than 21 mmHg, documented in medical history; open-angle grade III/IV according to Schaffer's classification; glaucomatous optic nerve head damage (excavation, neuroretinal rim thinning or notching, and localized or diffuse retinal nerve fiber layer [RNFL] defect); and glaucomatous defect in SAP in at least two consecutive tests, with three reliability indices better than 15% (results were considered abnormal if the Glaucoma Hemifield Test result was outside normal limits and at least three contiguous points were present within the same hemifield on the pattern deviation [PD] plot at p < 1%, with at least 1 point at p < 0.5%). (4) Advanced stages of PEXG: severe visual field loss with MD in visual field test > -18.0 dB. Inclusion criteria in the control group:(1) Incipient senile cataract: cloudy area in the lens that causes decreased vision. (2) No clinical signs of glaucoma, nor PEX. (3) Normal IOP: from 10 mmHg to 21 mmHg. In both groups, other causes of RNFL thinning (i.e., myopia, optic disc anomalies, ischemic optic neuropathy, optic neuritis, hereditary optic neuropathy, traumatic optic neuropathy, multiple sclerosis, and degenerative diseases such as Alzheimer's and Parkinson's disease) were excluded. Moreover, all of the participants had no previous intraocular surgeries, no other systemic or ocular diseases known to affect the visual field (e.g., pituitary lesions, demyelinating diseases, diabetes mellitus, etc.), and no previous eye or head trauma in their medical history. The patients' demographic and clinical data are presented in Table 1. 2.2. Aqueous Humor Approximately 100 mL of AH were obtained from the eye's anterior chamber at the beginning of the cataract surgery with special care to avoid contamination with blood or tears. 2.3. RNA Isolation The total RNA was isolated from the AH samples using an miRNeasy Serum/Plasma Kit (Qiagen, Valencia, CA, USA) according to the manufacturer's instructions. The isolated RNA was stored at -80 degC for further analysis. The RNA concentration was determined by using a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). In addition, RNA analysis was performed using an Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA) and a Pico RNA Kit according to the manufacturer's protocol. 2.4. The miRNA Profiling A microarray system (GeneChip miRNA 4.0 Array chip, Affymetrix, Santa Carla, CA, USA) was used to determine the miRNA expression profiles. The RNA preparation and hybridization were performed according to the manufacturer's protocol, with one modification to extend the hybridization time to 42 h. The gene chips were scanned with an Affymetrix GeneChip Scanner 3000 (Affymetrix, Santa Carla, CA, USA). The raw data, in a CEL format, were analyzed as log2-transformed intensities using the Affymetrix Transcriptome Analysis Console (TAC), following the software's guidelines to determine differentially expressed genes (DEGs) between the PEXG and control patients. The miRNAs that showed at least a one-fold difference between the control and PEXG groups, with a p-value of less than 0.01, were considered statistically significant and differentially expressed. 2.5. Enrichment Analysis The functional analysis of selected miRNA was performed using the Diana mirPATH v3.0 (accessed on 2 September 2022)) . The visualization of the regulatory network with obtained interactions was carried out by using Cytoscape v3.9.1 software (accessed on 2 September 2022)) . The analysis of the interactions of the selected miRNAs with genes was carried out in an R environment (version 4.1.2, (accessed on 1 December 2021)) using the multiMiR 1.16.0 package (accessed on 2 September 2022)) . The enrichment analysis was performed using the mirNET database (accessed on 2 September 2022)), where a list of selected miRNAs and a list of genes with which they interact were introduced . Terms of the Kyoto Encyclopedia of Genes and Genomes (KEGG), REACTOME, and Gene Ontology (GO) categories were searched for in PEX-related pathways. The plot visualizing the enrichment analysis was generated using the ggplot2 3.3.0 package in the R environment. 2.6. PPI Network and Subnetwork Construction Cytoscape was also used to perform protein-protein interactions (PPI). StringApp v2.0 (accessed on 5 January 2023)) was used for this purpose, which uses the Search Tool for the Retrieval of Interacting Genes (STRING). Molecular Complex Detection v2.0.2 (MCODE) (accessed on 7 January 2023)) and cytoHubba v0.1 (accessed on 7 January 2023)) plugins were then used to create clusters and extracting hub genes in a PPI network. 2.7. Statistical Analysis Results at p < 0.05 were considered statistically significant. The following software was used: GraphPad Prism 9 (Graph Pad Software, San Diego, CA, USA) and Statistica 13.3 (StatSoft, Krakow, Poland). The analyzes included the Shapiro-Wilk test (to assess the compliance of the examined variables with the normal distribution), the student's , and ROC curves (area under the curve (AUC) were calculated) for variables on a quantitative scale (data presented as an average). Data on a qualitative scale are presented as numbers and percentages and were analyzed using the Chi^2 test. 3. Results Analysis comparing the expression level of miRNAs using expression microarrays in the PEXG group compared to the cataract group showed 20 miRNAs as DEG's. Ten miRNAs were downregulated in PEXG (hsa-miR-95-5p, hsa-miR-515-3p, hsa-mir-802, hsa-miR-1205, hsa-miR-3660, hsa-mir-3683, hsa -mir-3936, hsa-miR-4774-5p, hsa-miR-6509-3p, and hsa-miR-7843-3p) and ten miRNAs were upregulated in PEXG (hsa-miR-202-3p, hsa-miR-3622a-3p, hsa-mir-4329, hsa-miR-4524a-3p, hsa-miR-4655-5p, hsa-mir-6071, hsa-mir-6723-5p, hsa-miR-6847-5p, hsa-miR-8074, and hsa-miR-8083) . In the group of DEG's miRNAs whose expression was lower in PEXG compared to the group (p < 0.01; AUC > 0.852; p < 0.01), a mean reduction in the level of PEXG expression was found at the level of 29.31% for hsa-miR-95-5p, 36.86% for hsa-miR-515-3p, 29.13% for hsa-mir-802, 28.35% for hsa-miR-1205, 13.15% for hsa-miR-3660, 43.64% for hsa-mir-3683, 42.14% for hsa-mir-3936, 14.35% for hsa-miR-4774-5p, 22.13% for hsa-miR-6509-3p, and 27, 37% for hsa-miR-7843-3p. In the group of DEG's miRNAs whose expression was higher in PEXG compared to the group (p < 0.01; AUC > 0.840; p < 0.01), a mean increase in the level of PEXG expression was found at the level of 28.73% for hsa-miR-202-3p, 29.65% for hsa-miR-3622a-3p, 20.05% for hsa-mir-4329, 21.64 for hsa-miR-4524a-3p, 34.06% for hsa-miR-4655 -5p, 23.50% for hsa-mir-6071, 24.61% for hsa-mir-6723-5p, 24.30% for hsa-miR-6847-5p, 21.57% for hsa-miR-8074, and 23.06% for hsa-miR-8083. Using the DIANA miRPath v3.0 database, a functional analysis of each of the selected miRNAs was performed (the analysis was performed separately for miRNAs with reduced and increased expression in PEXG). Next, networks were constructed visualizing possible functional relationships between the selected miRNAs . The functional network for downregulated miRNA functionally linked together nine miRNAs (leaving one type of miRNA without functional linkage--hsa-miR-3683). The terms with the most associations between the selected miRNAs were: "Ion binding", "organelle", "biosynthetic process", "cellular nitrogen compound metabolic process", "molecular function" and "molecular function". Functional network for upregulated miRNA functionally linked eight miRNAs (leaving two types of miRNAs (has-miR-6723-5p, and hsa-miR-4655-5p) without functional links between other miRNAs and with each other). The terms that obtained the most connections between the selected miRNAs were: "Ion binding", "organelle", "biosynthetic process", "cellular nitrogen compound metabolic process", "steroid hormone biosynthesis" and "gene expression". The next step was to perform an enrichment analysis to evaluate the biological processes regulated by the selected miRNAs and interacted genes using the mirNET database. Five categories were selected: KEGG (Kyoto Encyclopedia of Genes and Genomes), GO: Biological Processing (GO:BP), GO:Cellular Compartment (GO:CC), GO: Molecular Function (GO:MF), and Reactome. Genes indicated as targets of the expressed miRNAs were associated with intracellular and extracellular structures in addition to various processes. The top 10 terms for each category that may be potentially related to glaucoma and/or PEX are presented in Figure 5 and Figure 6, separately for downregulated and upregulated miRNAs in PEXG. Within the group of downregulated miRNAs, the most frequent terms are related to the regulation of transcription and translation, internal cellular transport ("trans-Golgi network transport vesicle", "endocytosis"), and signal transduction . In the upregulated miRNA group, the most frequently repeated terms are related to the regulation of transcription and translation, the regulation of the cell cycle, and the activity of cations (mainly calcium and zinc) . A PPI network of the genes regulated by selected miRNAs were constructed and clustering analysis was performed based on these PPI networks. In total, six clusters (sub-networks) were created for each PPI network of the genes regulated by downregulated miRNAs . Clusters I and IV are functionally related to chromatin organization and epigenetic regulation of gene expression, moreover, the key genes in them are the EZH2 gene (in cluster I) and BAZ1B (in cluster IV). Cluster II is functionally related to nuclear chromosome segregation and cellular response to DNA damage (the key gene: TIMELESS). Cluster III is functionally related to the voltage-gated calcium channel complex and MAPK signaling pathway (the key gene: CACNA2D1). Cluster V is functionally related to protein transport (the key gene: RAB7A). Cluster VI is functionally related to ubiquitinization (the key gene: UBE2D1). In total, six clusters (sub-networks) were created for each PPI network of the genes regulated by upregulated miRNAs . Cluster VII is functionally related to cytokine-cytokine receptor interaction and cell-cell adhesion (the key gene: IL10). Cluster VIII is functionally related to the activity of RNA polymerases II and III (the key gene: PLR2D). Cluster IX is functionally related to ubiquitinization (the key gene: PHC1). Cluster X is functionally related to L-type voltage-gated calcium channel complex (the key gene: CACNA1G). Cluster XI is functionally related to the regulation to the jnk cascade (the key gene: AXIN1). Cluster XII is functionally related to Rho GTPases activate ROCKs and phospholipase D signaling pathway (the key gene: RHOA). The hub genes identified using the cytoHubba app included the EZH2, H2AFX in hub I, CACNA1D in hub IIa, and MYC in hub IIb . Enrichment analysis for these networks indicated that hub I is related to generic transcription pathway and cellular responses to stress, hub IIa is related to voltage-gated channel activity and MAPK signaling pathway, hub IIb is related to cellular senescence and Wnt, Hippo, JAK-STAT signaling pathways (Table 6). 4. Discussion MiRNA molecules are found both inside the cell and in extracellular fluids. The miRNA in the AH may be derived from blood plasma and may be secreted by intraocular cells. These molecules have been shown to be of great importance in processes such as retinal homeostasis and its development . Current knowledge about the pathological mechanisms of PEXG is still unknown. Many studies suggest the role of non-coding RNAs, which, through altered expression levels, may be associated with the development of PEXG. The role of miRNAs and snoRNA is mainly suggested. Current literature suggests a role for certain miRNAs in the pathogenesis of PEXG. These are hsa-miR-671, hsa-miR-374a-5p, hsa-miR-1307-5p, hsa-miR-708-5p , and hsa-miR-30d-5p, hsa-miR-320a, -3156-5p, hsa-miR-4458, hsa-miR-6717-5p, hsa-miR-6728-5p, hsa-miR-6834-5p, hsa-miR-6864-5p, hsa-miR-, hsa-miR-877-3p, hsa-miR-548e-3p, and hsa-miR-6777-5p . The main mechanisms associated with the altered expression of these miRNAs is cell apoptosis by suppressing the Wnt3a/b-catenin pathway and the PI3K/AKT pathway and the TGF-beta signaling pathway . In our work, we examined the level of miRNA expression in a group of patients with PEXG and cataracts. After selecting the 20 DEGs of miRNAs (10 upregulated and 10 downregulated), we performed an enrichment and functional analysis. One of the pathological mechanisms related to PEX contains too high of a concentration of calcium cations, which is directly related to the activity of the channels for these cations. Currently, three types of calcium channels are cited, i.e., CACNA1A , CACNB3 , and CACNB4 . The calcium channel is composed of subunits, of which the a subunit forms a transmembrane channel, while the remaining subunits (b and a2/d) perform regulatory functions. Additionally, in some channels, there may be a g subunit. The calcium channels are divided into three subfamilies, i.e., CaV1, CaV2, and CaV3. The activity of the CaV1 subfamily channels are responsible for the initiation of contraction and regulates gene expression and transmission in synapses. The CaV2 subfamily channels are associated with synaptic transmission, while the CaV3 subfamily channels are associated with the production of action potentials in myocytes and neurons. The CaV1.4 transporter has been shown to be present in the retinal cell membranes of the eye and its activity is related to visual signaling . The results of functional analysis in our study showed that hsa-miR-8074 influences the transport of calcium cations across biological membranes through the regulation of the ATP2B2 gene. Moreover, we found that the voltage-gated calcium channel activity is being regulated by the genes targeted by selected miRNAs. Additionally, the Wnt signaling pathway is regulated by the genes targeted by selected miRNAs, where one of the signaling pathways is the Wnt/Ca2 + pathway, the activity of which is related to G proteins and phospholipases. An important regulatory structure of the IOP is HTM (human trabecular meshwork), which is made up of trabecular cells surrounded by the ECM. HTM is responsible for the outflow of AH--in a situation of difficult outflow, the IOP increases . The literature provides two pathways (TGFb1 and TGFb2), in which the changes lead to an imbalance in the eye's ECM and, consequently, to an increase in IOP . Among the results of the functional analysis in our work, we obtained the term "ECM receptor interactions" for four miRNAs that are regulated by genes: hsa-mir-802 (COL5A1, LAMC1, FN1, CD47), hsa-mir-3660 (LAMA3), hsa-mir -3662a-3p (ITGB8, SV2B, COL24A1, COL4A6, TNR), and hsa-miR-4774-5p (COL11A1, COL24A1). In addition, proteins are a very important element of the ECM. Disruption of protein metabolism (synthesis, post-translational modification, or transport) may lead to the development of PEX . Functional analysis of selected miRNAs showed that a relatively large number of these miRNAs influence genes related to protein metabolism. The process of protein modification in the cell is regulated by genes whose expression is influenced by six out of twenty selected miRNAs (hsa-miR-95-5p, hsa-miR-1205, hsa-miR-3660, hsa-miR-515-3p, and -6071,22-3p). In addition, subsequent miRNAs affect the expression level of genes related to protein metabolism, i.e., "protein complex" (hsa-miR-4329, hsa-miR-6071, hsa-miR-1205, and hsa-miR-3660), "cytoskeletar protein binding" (hsa-miR-6847-5p, 1205), "post-translational protein modification" (hsa-miR-7843-3p), "endoplasmic reticulum-Golgi intermediate compartment" (has-miR-802), and "cytoplasmic sequestering of protein "(Hsa-miR-4655-5p). Moreover, hsa-miR6723-5p regulates the expression level of the UBE2H gene related to ubiquitin-mediated proteolis. Among the enriched functional terms of genes targeted by selected miRNAs in AH in PEXG patients, it is worth mentioning the "trans-Golgi network transport vesicle" as a process that influences protein transport. In addition, many times the results of this analysis were terms related to the process of protein biosynthesis ("positive regulation of translation", "regulation of translation") and transcription ("negative regulation of transcription from RNA polymerase II promoter", "negative regulation of transcription, "). In a previous work, we suggested that some snoRNA molecules are related to PEXG . One of the terms obtained in enrichment analysis is "spliceosomal complex" which may suggest that the selected miRNAs may also be responsible for this process. The mechanisms discussed above largely explained where the elevated IOP comes from. Elevated IOP results in RGC apoptosis and, furthermore, optic nerve degeneration which is often observed in late PEXG . Another mechanism that can lead to IOP increase and cell death in glaucoma is oxidative stress . The hsa-miR-802 molecule by regulating the expression of MCL1, PPP2CB, and SOD2 genes influences the processes taking place in the mitochondria during apoptosis. Among the enriched functional terms of genes targeted by selected miRNAs in AH in PEXG patients, it is worth mentioning "G0 and early G1" and "G2/M transition of the mitotic cell cycle". In addition, "AKT phosphorylates targets in the cytosol" and "PI3K/AKT activation" are terms that suggest that selected miRNAs may regulate the survival of ocular neurons and thus may lead to optic nerve degeneration. The role of the PI3K/Akt pathway was previously mentioned . Hsa-miR-802 shows an increased expression in primary human umbilical vein endothelial cells (HUVECs) in response to induced hypoxia . As above, hsa-miR-202-3p is one of the miRNAs whose expression levels have been altered in lung adenocarcinoma A549 cells by hypoxia . Additionally, a correlation between the risk of developing normal-tension glaucoma (NTG) and the level of retinol in the blood serum was demonstrated . Moreover, another group of scientists reports that retinoic acid (a retinol derivative) lowers the expression level of the gene which codes the small heat shock protein B8 (HSPB8) , which is a chaperone protein functionally related to chaperone-assisted selective autophagy (CASA) . One of the miRNA molecules selected as DEGs in our work, hsa-miR-6509-3p regulates the expression level of the HSPB8 gene. The above data may suggest a potential influence of the autophagy process in the development of PEXG. The results of the PPI analysis suggest and confirm that a very important mechanism of PEXG may be disturbances in the transport of calcium cations in the eye. One of the hub genes that have been selected is the CACNA1D gene. Our research had some limitations. First, the study groups were small, consisting of nine patients each. A study involving a larger group of patients is needed to confirm the results. Furthermore, PEXG patients had advanced neuropathy, which suggests that miRNA molecules may be the result of the pathological process and not a causative factor. However, we precluded that the same stage of the disease within the group would enable more unique results. Since the advanced stages of PEXG, comparison of miRNAs in the early stages of PEXG is needed. In addition, all enrolled patients were diagnosed with senile cataracts. Therefore, the impact of cataracts on the expression of miRNA in the PEXG group should be taken into consideration, but in the studied group all patients also had similar stages of cataracts. However, it is ethically impossible to collect aqueous humor in healthy eyes due to the invasive nature of the procedure. Until now, the scientific literature has not provided such information, which means that this is the first time we are doing it. These mechanisms are possible, but their role in the pathogenesis of PEXG/PEX must be carefully studied. 5. Conclusions Our results suggest 20 new miRNAs whose altered expression in the aqueous humor may have an influence on the pathomechanisms of PEXG. Functional and enrichment analysis confirms the mechanisms, such as high levels of calcium cations, ECM imbalance, apoptosis of RGC cells, and the optic nerve damage or autophagy as possible causes of PEXG. Moreover, the PPI analysis suggests that CACNA1D, EZH2, and MYC may be hub genes for PEXG. However, confirmation of these conclusions requires further study. Author Contributions Conceptualization, K.G., M.C., E.K.-J., J.K. and D.W.-D.; methodology, K.G., M.C., E.K.-J. and D.W.-D.; software, K.G. and M.C.; formal analysis, K.G. and M.C.; investigation, K.G., M.C., E.K.-J., D.W.-D., J.K. and T.Z.; data curation, K.G. and M.C.; writing--original draft preparation, K.G. and M.C.; writing--review and editing, K.G., M.C., E.K.-J., D.W.-D., J.K. and T.Z.; supervision, J.K. and T.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Bioethics Committee of the Medical University of Lublin (KE-0254/107/2020, 28 May 2020). Informed Consent Statement Informed consent was obtained from all of the subjects involved in the study. Data Availability Statement All data generated or analyzed during this study are included in this published article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Lower miRNA expression in the PEXG group compared to the cataract group. Data are shown as mean [log2]. Figure 2 Higher miRNA expression in the PEXG group compared to the cataract group. Data are shown as mean [log2]. Figure 3 Functional network performed using selected downregulated miRNAs in PEXG. The network is made up of the 10 most statistically significant for each miRNA. Analysis made using DIANA-miRPath v3.0. Figure 4 Functional network performed using selected upregulated miRNAs in PEXG. The network is made up of the 10 most statistically significant for each miRNA. Analysis made using DIANA-miRPath v3.0. Figure 5 Top 10 terms of the Gene Ontology (GO): Biological Processing (GO:BP), GO: Cellular Compartment (GO:CC), Molecular Function (GO:MF), REACTOME and KEGG (Kyoto Encyclopedia of Genes and Genomes) categories, revealed for /or pseudoexfoliation syndrome (PEX)-associated genes targeted by downregulated miRNAs found in the current study in the aqueous humor (AH) of patients with PEXG and age-matched controls. p-value--EASE score for enrichment adjusted by the Benjamini correction for multiple-hypothesis testing. The number in brackets following the names of terms indicates the number of associated genes. The plot was generated using the ggplot2 3.3.0 package in the R environment. Figure 6 Top 10 terms of the Gene Ontology (GO): Biological Processing (GO:BP), GO: Cellular Compartment (GO:CC), Molecular Function (GO:MF), REACTOME, and KEGG (Kyoto Encyclopedia of Genes and Genomes) categories, revealed for /or pseudoexfoliation syndrome (PEX)-associated genes targeted by upregulated miRNAs found in the current study in the aqueous humor (AH) of patients with PEXG and age-matched controls. p-value--EASE score for enrichment adjusted by the Benjamini correction for multiple-hypothesis testing. The number in brackets following the names of terms indicates the number of associated genes. The plot was generated using the ggplot2 3.3.0 package in an R environment. Figure 7 Results of protein-protein interaction analysis. The 6 top-scored clusters separated from the PPI network of the genes regulated by downregulated miRNAs found in the current study. The PPI hub gene module (g). Figure 8 Results of protein-protein interaction analysis. The six top-scored clusters separated from PPI network of the genes regulated by upregulated miRNAs found in the current study. Figure 9 The PPI hub gene modules from PPI networks of the genes regulated by downregulated (Hub I) and upregulated miRNAs (Hubs IIa, IIb). cells-12-00737-t001_Table 1 Table 1 Demographic and clinical characteristics of the study groups. PEXG N = 9 Cataract N = 9 p-Value Age (mean +- SD) 77.56 +- 6.54 76.00 +- 6.95 0.6314 ^ Gender (N, %) Male 8 (88, 89%) 8 (88, 89%) 0.7647 # Female 1 (11, 11%) 1 (11, 11%) BCVA 0.19 +- 0.17 0.42 +- 0.12 0.0047 ^ MAX IOP 30.44 +- 13.1 15.67 +- 2.12 0.0042 ^ C/D 0.91 +- 0.07 0.29 +- 0.15 <0.0001 ^ RNFL 61.22 +- 5.12 93.8 +- 5.61 0.0005 ^ MD -22.55 +- 4.77 -0.03 +- 0.98 <0.0001 ^ #--chi2 test; ^--Student's t-test; BCVA--best-corrected visual acuity; C/D--cup/disc; IOP--intraocular pressure; MD--mean deviation; PEXG--pseudoexfoliation glaucoma; RNFL--retinal nerve fiber layer; and SD--standard deviation. cells-12-00737-t002_Table 2 Table 2 10 miRNA downregulated in the PEXG group compared to the cataract group [log2]. miRNA Group n Mean SD Fold Change p Value AUC AUC p Value hsa-miR-95-5p Cataract 9 1.284 0.206 -1.25 0.0037 0.877 0.0071 PEXG 9 0.993 0.155 hsa-miR-515-3p Cataract 9 1.474 0.291 -1.25 0.0060 0.889 0.0054 PEXG 9 1.093 0.213 hsa-mir-802 Cataract 9 1.248 0.179 -1.20 0.0009 0.951 0.0013 PEXG 9 0.974 0.091 hsa-miR-1205 Cataract 9 1.390 0.232 -1.26 0.0046 0.858 0.0104 PEXG 9 1.083 0.156 hsa-miR-3660 Cataract 9 1.334 0.099 -1.08 0.0071 0.907 0.0036 PEXG 9 1.179 0.114 hsa-mir-3683 Cataract 9 1.254 0.229 -1.30 0.0008 0.914 0.0031 PEXG 9 0.873 0.153 hsa-mir-3936 Cataract 9 1.464 0.311 -1.29 0.0020 0.926 0.0023 PEXG 9 1.030 0.169 hsa-miR-4774-5p Cataract 9 1.347 0.074 -1.13 0.0026 0.883 0.0062 PEXG 9 1.178 0.121 hsa-miR-6509-3p Cataract 9 1.457 0.187 -1.21 0.0060 0.852 0.0118 PEXG 9 1.193 0.165 hsa-miR-7843-3p Cataract 9 1.373 0.244 -1.22 0.0066 0.895 0.0047 PEXG 9 1.078 0.145 AUC--area under curve. cells-12-00737-t003_Table 3 Table 3 10 miRNA upregulated in the PEXG group compared to the cataract group [log2]. miRNA Group N Mean SD Fold Change p Value AUC AUC p Value hsa-miR-202-3p Cataract 9 1.131 0.199 1.43 0.0088 0.877 0.0071 PEXG 9 1.587 0.412 hsa-miR-3622a-3p Cataract 9 1.580 0.370 1.55 0.0084 0.840 0.0152 PEXG 9 2.246 0.552 hsa-mir-4329 Cataract 9 1.296 0.158 1.25 0.0012 0.901 0.0041 PEXG 9 1.621 0.191 hsa-miR-4524a-3p Cataract 9 0.938 0.223 1.18 0.0069 0.840 0.0152 PEXG 9 1.197 0.114 hsa-miR-4655-5p Cataract 9 1.218 0.242 2.17 0.0088 0.852 0.0118 PEXG 9 1.847 0.584 hsa-mir-6071 Cataract 9 1.068 0.137 1.23 0.0037 0.926 0.0023 PEXG 9 1.396 0.255 hsa-mir-6723-5p Cataract 9 1.066 0.131 1.25 0.0026 0.889 0.0054 PEXG 9 1.414 0.263 hsa-miR-6847-5p Cataract 9 1.168 0.128 1.24 0.0025 0.920 0.0027 PEXG 9 1.543 0.288 hsa-miR-8074 Cataract 9 1.236 0.211 1.16 0.0070 0.846 0.0134 PEXG 9 1.576 0.254 hsa-miR-8083 Cataract 9 0.951 0.222 1.20 0.0040 0.883 0.0062 PEXG 9 1.236 0.123 AUC--area under curve. cells-12-00737-t004_Table 4 Table 4 Enrichment analysis of the six top-scored clusters separated from the PPI network of the genes regulated by downregulated miRNAs found in the current study. Cluster Category Term p Value Genes I GO BP Chromatin organization 5.00 x 10-4 EPC1, SETD7, SUZ12, EZH2, BCOR, AEBP2, TET3, PHF19 GO BP Negative regulation of gene expression, epigenetic 0.0012 EPC1, SUZ12, EZH2, AEBP2, PHF19 II GO BP Nuclear chromosome segregation 2.70 x 10-4 NIPBL, PDS5B, SMC1A, SYCP1, STAG1, DDX11 GO BP Cellular response to DNA damage stimulus 0.0023 NIPBL, CLOCK, PDS5B, SMC1A, SYCP1, DDX11, TIMELESS III KEGG MAPK signaling pathway 5.60 x 10-4 RASGRP2, CACNA2D1, CACNA1A, CACNA1E GO:CC Voltage-gated calcium channel complex 0.0053 CACNA2D1, CACNA1A, CACNA1E IV GO:BP Chromatin organization 0.0012 BPTF, CECR2, BAZ1B, HIST1H2BK, SMARCA1, DEK, H2AFX Reactome B-WICH complex positively regulates rRNA expression 0.0042 BAZ1B, HIST1H2BK, DEK, H2AFX V Reactome RAB GEFs exchange GTP for GDP on RABs 0.0135 RAB7A, RAB5B, RAB14 GO:BP Protein transport 0.0260 RAB7A, RAB5B, STX16, RAB14, PLEKHM1, TBC1D30 VI GO:MF Ubiquitin-protein transferase activity 5.60 x 10-4 RNF38, UBE2B, UBA7, UBE2H, UBE2D1, UBE2W Reactome Antigen processing: Ubiquitination & Proteasome degradation 0.0013 UBE2B, UBA7, UBE2H, UBE2D1, UBE2W cells-12-00737-t005_Table 5 Table 5 Enrichment analysis of the six top-scored clusters separated from the PPI network of the genes regulated by upregulated miRNAs found in the current study. Cluster Category Term p Value Genes VII KEGG Cytokine-cytokine receptor interaction 4.03 x 10-14 IFNG, TNFSF9, IL11, TNFSF4, TNFSF12, CXCL5, IL16, CD40LG, TNFRSF1B, IL10 GO:BP Positive regulation of cell-cell adhesion 8.60 x 10-5 IFNG, TNFSF9, TNFSF4, ICOS, CD40LG, IL10 VIII GO:CC RNA polymerase II, holoenzyme 2.90 x 10-6 POLR2D, TAF5, RPRD1B, GTF2F1, POLR2F Reactome RNA Polymerase III Abortive Additionally, Retractive Initiation 4.94 x 10-6 POU2F1, NFIB, NFIX, POLR3G, POLR2F IX Reactome Regulation of PTEN gene transcription 8.30 x 10-4 PHC2, CBX2, CBX6, PHC1 GO:BP Histone ubiquitination 0.021 PCGF3, RYBP, PHC1 X GO:CC Voltage-gated calcium channel complex 1.29 x 10-17 CACNG8, CACNA1D, CACNA1G, CACNA1E, CACNA1B, CACNA2D2, CACNA2D3, CACNB4 GO:CC L-type voltage-gated calcium channel complex 0.0021 CACNG8, CACNA1D XI KEGG Basal cell carcinoma 7.70 x 10-4 WNT16, AXIN1, FZD9 GO:BP Regulation of jnk cascade 0.0119 WNT16, AXIN1, AIDA, VANGL2 XII Reactome RHO GTPases Activate ROCKs 5.88 x 10-5 ROCK1, RHOA, PPP1R12B KEGG Phospholipase D signaling pathway 0.0283 RHOA, LPAR2 cells-12-00737-t006_Table 6 Table 6 Enrichment analysis of the hub gene module from the PPI network of the genes regulated by downregulated and upregulated miRNAs. Hub Category Term p Value Genes I Reactome Generic Transcription Pathway 9.79 x 10-7 CDKN1B, MDM2, CCND2, EZH2, HIST1H2BK, AGO1, BCL2L11, CDKN1A, H2AFX, VEGFA I Reactome Cellular responses to stress 9.79 x 10-7 CDKN1B, MDM2, EZH2, HIST1H2BK, AGO1, CDKN1A, H2AFX, VEGFA I Reactome Cellular Senescence 9.79 x 10-7 CDKN1B, MDM2, EZH2, HIST1H2BK, AGO1, CDKN1A, H2AFX I KEGG MicroRNAs in cancer 1.55 x 10-6 CDKN1B, MDM2, CCND2, EZH2, BCL2L11, CDKN1A, VEGFA IIa GO:CC Voltage-gated calcium channel complex 9.03 x 10-14 CACNG8, CACNA1D, CACNB2, CACNA1E, CACNA1B, CACNA2D2, CACNA2D3, CACNB4 IIa GO:MF Voltage-gated calcium channel activity 3.10 x 10-13 CACNG8, CACNA1D, CACNB2, CACNA1E, CACNA1B, CACNA2D2, CACNA2D3, CACNB4 IIa KEGG MAPK signaling pathway 1.92 x 10-10 CACNG8, CACNA1D, CACNB2, CACNA1E, CACNA1B, CACNA2D2, CACNA2D3, CACNB4 IIa Reactome Presynaptic depolarization and calcium channel opening 4.50 x 10-9 CACNB2, CACNA1E, CACNA1B, CACNA2D2, CACNA2D3, CACNB4 IIb KEGG Cellular senescence 0.0091 CCND1, MYC IIb KEGG Wnt signaling pathway 0.0091 IIb KEGG Hippo signaling pathway 0.0091 IIb KEGG JAK-STAT signaling pathway 0.0091 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000532 | Pancreatic cancer remains one of the most challenging malignancies to date and is associated with poor survival. Cancer-associated fibroblasts (CAFs) are key stromal cells in the tumor microenvironment (TME) that play a crucial role in tumor progression in pancreatic cancer. Thus, uncovering the key genes involved in CAF progression and determining their prognostic value is critically important. Herein, we report our discoveries in this research area. Analysis of The Cancer Genome Atlas (TCGA) dataset and investigation of our clinical tissue samples indicated that COL12A1 expression was aberrantly highly expressed in pancreatic cancer. Survival and COX regression analyses revealed the significant clinical prognostic value of COL12A1 expression in pancreatic cancer. COL12A1 was mainly expressed in CAFs but not in tumor cells. This was verified with our PCR analysis in cancer cells and CAFs. The knocking down of COL12A1 decreased the proliferation and migration of CAFs and down-regulated the expression of CAF activation markers actin alpha 2 (ACTA2), fibroblast activation protein (FAP), and fibroblast-specific protein 1 (FSP1). Meanwhile, the interleukin 6 (IL6), CXC chemokine Ligand-5 (CXCL5), and CXC chemokine Ligand-10 (CXCL10) expressions were inhibited, and the cancer-promoting effect was reversed by COL12A1 knockdown. Therefore, we demonstrated the potential prognostic and target therapy value of COL12A1 expression in pancreatic cancer and elucidated the molecular mechanism underlying its role in CAFs. The findings of this study might provide new opportunities for TME-targeted therapies in pancreatic cancer. pancreatic cancer cancer-associated fibroblasts COL12A1 TCGA prognosis Education of Jiangsu Province2018K256C National Natural Science Foundation of China82002490 Education of Jiangsu Province (grant number: 2018K256C). National Natural Science Foundation of China (grant number: 82002490). pmc1. Background Pancreatic ductal adenocarcinoma (PDAC) is difficult to treat and has a 5-year survival rate of less than 5% . As the early diagnosis of pancreatic cancer is difficult, 80% of patients are diagnosed in the advanced stage of the disease or have locally invasive tumors. Only 20% of patients have the opportunity for curative resection. These patients have an overall 5-year survival rate of 10-25% . Moreover, local recurrence or distant metastasis is common, even in patients who have undergone surgery. In such cases, adjuvant therapy consisting of chemotherapy and/or radiation therapy is necessary. However, the outcomes of combined chemotherapy and radiotherapy remain poor . Therefore, the identification of molecular prognostic biomarkers and targeted molecular therapies are essential to improve the outcomes of PDAC patients. The extracellular matrix (ECM) performs a crucial role in tumor progression invasion and chemo-resistance in pancreatic cancer . The most abundant protein component in the ECM is collagen, which can directly bind to the cancer cell receptors discoidin domain receptor 1 (DDR1) and discoidin domain receptor 2 (DDR2), regulate immune cell infiltration, and TGFb expression indirectly associated with the cancer cell to induce tumor growth and metastasis . Thirty-two types of collagens have been identified in ECM . The different types of collagens expressed in PDAC have critical roles in cancer genesis and progression. Even some types of collagens have a prognosis value for PDAC patients as confirmed with serum, tissues, or bioinformatic analyses . COL12A1, a member of the major collagen family of Fibril-Associated Collagens (FACIT) collagens, assumes a key role in tumor growth . High COL12A1 expression has been correlated with poor survival and cancer metastasis in gastric cancer and colon cancer . Bioinformatic analysis indicated COL12A1 has a prognosis effect in pancreatic cancer , but the mechanism underlying the effect of COL12A1 in PDAC progression is still unelucidated. In this study, using the Gene Expression Omnibus (GEO) dataset, we found the pathway of differentially expressed genes (DEGs) that mainly focuses on the ECM receptor interaction and collagen catabolic process. The collagen family was focused on finding the key genes associated with pancreatic cancer progression. Analysis of the TCGA dataset implied that COL12A1 has an important role in pancreatic cancer prognosis. CAFs that expressed COL12A1 make a crucial contribution to PDAC genesis and progression. This was explored with bioinformatic analysis and validated using in vitro and in vivo experiments. The findings of this study might provide new opportunities for TME-targeted therapies in pancreatic cancer. 2. Methods 2.1. Data Collection RNA sequencing and the related clinical data of TCGA and Genotype-Tissue Expression (GTEx) were downloaded from the UCSC XENA website accessed on 5 December 2021). GSE16515, GSE15471, GSE60979, GSE62452, GSE71989, and GSE91035 gene expression profiles were retrieved from the GEO database accessed on 5 December 2021) in microarray platform (GLP570). These data were analyzed using the Affymetrix Human Genome U133 Plus 2.0 Array (transcript (gene) version; Santa Clara, CA, USA). 2.2. Identification of DEGs After downloading the datasets for GSE16515, GSE15471, GSE60979, GSE62452, GSE71989, and GSE91035, the GEO2R online tool was used to identify DEGs. Tumor and normal tissues were selected to evaluate gene expression. The threshold value for the screening of DEGs was p < 0.05 and |log fold-change| > 1. The Online Venn diagram tool was used to visualize the DEGs in the six data sets. 2.3. GO Enrichment and KEGG Pathway Analysis of DEGs The DAVID online tool version 6.8, accessed on 19 December 2019) was used to check gene function (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. GO describes genes in terms of their biological process (BP), molecular function (MF), and cellular component (CC) . The KEGG pathway was used to check the indicated genes, including their reference pathways . p < 0.05 was considered to indicate statistical significance. 2.4. Expression Analysis GEPIA accessed on 19 December 2019) is an interactive web server for analyzing the RNA sequencing expression data of 9736 tumors and 8587 normal samples from the TCGA and GTEx projects. The GEPIA expression module was used to visualize mRNA expression in TCGA combined with GTEx. The Oncomine database, the largest oncogene chip database, was used to demonstrate the COL12A1 mRNA expression level difference between tumors and normal tissues. Additionally, we used the R package "ggplot2" to explore the relationship between COL12A1 mRNA expression and clinical parameters in TCGA. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset was used for COL12A1 protein expression analysis. The Human Protein Atlas (HPA) database accessed on 19 December 2019) is designed to map all the human proteins in cells, tissues, and cancers. It was used to demonstrate the differential expression of COL12A1 protein using immunohistochemistry staining in normal and cancer tissues. Tumor Immune Single-cell Hub (TISCH) is a scRNA-seq database accessed on 21 May 2022) focusing on TME. In the "dataset" and "gene" modules, we visualized the expression levels of COL12A1 at the single-cell level in the pancreatic cancer RA001160 and GSE111672 datasets. 2.5. Survival, Prognosis, and Diagnostic Value Analysis We evaluated the association of COL12A1 expression with overall survival (OS) using the GEPIA survival module. In addition, the R packages "survminer" and "survival" were used to visualize the COL12A1 expression, Disease Specific Survival (DSS), and Progress Free Interval (PFI). The log-rank test was used to compare differences in survival between the low and high levels of COL12A1 groups using the R package "ggrisk". The R package "timeROC" was used to compare the predictive accuracy of COL12A1 mRNA. We established a nomogram combining COL12A1 expression and key clinical factors to predict the 1-, 3-, and 5-year survival of pancreatic cancer patients using the R packages "rms" and "survival". Additionally, we conducted a calibration analysis to check the nomogram. 2.6. Gene Mutation and Methylation Analysis Mutation analysis was performed on the cBioportal online web accessed on 21 May 2022). Gene methylation analysis was performed on GSCA: Gene Set Cancer Analysis online web accessed on 21 May 2022) and UALCAN. 2.7. Functional Enrichment Analysis To explore the abnormal changes in downstream pathways caused by the enhanced expression of COL12A1, we identified DEGs between pancreatic cancer samples with COL12A1 high and low mRNA expression based on the TCGA data using the R packages "DESeq2" and "ggplot2". To further clarify the potential mechanisms of COL12A1 in pancreatic cancer progression, GO and KEGG enrichment was performed to predict the functions and pathways of the COL12A1-related DEGs using the R package "clusterProfiler". In addition, we analyzed some important pathways involved in cancer using the R package "GSVA", choosing parameter as method = 'ssGSEA'. The correlation between genes and pathway scores was analyzed using Spearman correlation. 2.8. Cell Infiltration Analysis Tumor Immune Estimation Resource (TIMER) is a comprehensive resource for the systematical analysis of immune infiltrates across diverse cancer types accessed on 1 April 2022). CAFs play a key role in the development and maintenance of the stromal cancer compartment, mediating an increase in the synthesis of the extracellular matrix . To explore the correlation between COL12A1 expression and cancer-associated fibroblast (CAF) infiltrates, we applied the immune gene module and selected the CAFs for analysis. The correlation between COL12A1 expression and the cell markers of CAFs was also analyzed. 2.9. Cell Lines, Patients, and Specimens PANC-1, BxPC-3, CFPAC-1, PATU-8988, ASPC-1, and MIA PaCa-2 were obtained from Procell. PANC-1, PATU-8988, and HPDE6-C7 were cultured with DMEM (Gibco) supplemented with 10% FBS (Gibco) and 1% penicillin-streptomycin (Gibco). ASPC-1 was cultured with RPMI-1640 (Gibco) supplemented with 10% FBS (Gibco) and 1% penicillin-streptomycin (Gibco). CFPAC-1 was cultured with IMDM (Gibco) supplemented with 10% FBS (Gibco) and 1% penicillin-streptomycin (Gibco). MIA PaCa-2 cells were cultured with DMEM (Gibco) supplemented with 10% FBS (Gibco), 5% HS (Gibco), and 1% penicillin-streptomycin (Gibco). To measure COL12A1 expression, 31 pairs of fresh pancreatic cancer tissues and matched para-cancer tissues were obtained between November 2019 and November 2021 at the Affiliated Hospital of Nantong University. The study protocol was approved by the Human Ethics Review Committees of Affiliated Hospital of Nantong University (approval no. 2019-L034). 2.10. Culture and Transfection of CAFs CAFs were isolated from fresh pancreatic cancer tissues following the method described by Bachem et al. . Pancreatic cancer tissues were obtained surgically and cut into small pieces and cultured in DMEM (Gibco) plus 10% FBS (Gibco) and 1% penicillin-streptomycin (Gibco) in T25 flasks. The medium was changed every three days. After 7-10 days, CAFs migrated out of the tissues. The cells were maintained in a humidified incubator at 37 degC in an atmosphere of 5% CO2. All resected tissues were postoperatively diagnosed with pancreatic cancer. All patients provided written informed consent, and the Ethics Committee of the Affiliated Hospital of Nantong University approved this study. CAFs were identified by the detection of the CAF-specific markers ACTA2, FAP, and FSP1 with immunofluorescence. CAFs at the logarithmic growth phase were digested and seeded into a 6-well plate. When cell confluence reached 60-70%, CAFs were transfected with siRNA NC and siRNA COL12A1 (GCAAUAAACACCUUCCCUUTT) using Lipofectamine 2000 reagents. 2.11. RNA Extraction and Quantitative Real-Time PCR Total RNA was extracted from cells or tissues using Trizol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's protocol. The extracted RNA was reverse transcribed into complementary DNA (cDNA) following the instructions of the Reverse Transcription Kit (Takara, Kusatsu, Japan). Thereafter, the cDNA was subjected to real-time PCR using the SYBR Green PCR kit (Takara, Kusatsu, Japan) and the Step One instrument (Applied Biosystems, Carlsbad, CA, USA). The primers used in the study were provided in Table 1. 2.12. EdU, Wound Healing, Transwell, and Clone Formation Assay For the EdU assay, CAFs were seeded into a 24-well plate. Each well was incubated with EdU medium for 3 h and then fixed with 4% paraformaldehyde. The cells were further incubated with EdU regent in the dark for 30 min. Finally, cells were incubated with Hoechst 3334 for 10 min. Cells stained with EdU and with Hoechst 33342 were counted. EdU positive rate (%) = the number of EdU cells/the number of total cells x 100%. For the wound healing assay, CAFs were seeded in 12-well plates. When the confluent monolayer was formed, the cells were starched with a sterile 200 mLpipette tip to create a wound gap. The medium was replaced with an FBS-free medium and cultured for another 24 h. For the transwell assay, an 8 mm transwell chamber (Corning, kennebunk, ME, USA) was used. A CAF suspension (100 mL, 4 x 104 cells) was added to the upper chamber and a medium containing 10% FBS was added to the lower chamber. After incubation at 37 degC for 18 h, the cells were fixed with 4% paraformaldehyde and stained with crystal violet. Eight fields of view were randomly selected, and the cell number was counted under the microscope. For the clone formation assay, the conditional medium of CAFs transfected with siNC and siCOL12A1 was collected, respectively. Pancreatic cancer cells PANC-1 were seeded into 12-well plates at a density of 500 cells/well with different conditional medium. Finally, the cells were fixed with 4% paraformaldehyde and stained with crystal violet. The number of colonies in each well was counted. 2.13. Western Blotting and Immunofluorescence For western blotting, total proteins were extracted from cells using radioimmunoprecipitation assay lysis buffer (SolarBio Science & Technology Co., Ltd., Beijing, China). Protein concentration was quantified using a bicinchoninic acid (BCA) kit (Beyotime Biotechnology, Nantong, China). The protein was separated using polyacrylamide gel electrophoresis and electrotransferred onto polyvinylidene fluoride (PVDF) membranes using the wet transfer method. The membrane was blocked with NcmBlot blocking buffer (New cell & Molecular Biotech Co., Ltd., Suzhou, China) for 10 min and incubated with primary antibodies against ACTA2 (1:1000, Servicebio, Wuhan, China), FAP (1:500, Beyotime Biotechnology, Nantong, China), and FSP (1:1000, Peoteintech, Wuhan, China) at 4 degC overnight. Next, the membrane was incubated with horseradish peroxidase (HRP)-labeled goat anti-rabbit IgG (1:10,000, Biosharp, Hefei, China) at room temperature for 1 h and then developed. For immunofluorescence, cells were seeded onto slides and fixed with 4% paraformaldehyde. Then, they were incubated with primary antibody against ACTA2 at 4 degC overnight. Next, cells were incubated with a secondary antibody goat anti-rabbit Alexa Fluor 488 IgG (1:200, Servicebio, Wuhan, China) at room temperature for 1 h in the dark. Finally, the cells were stained with Hoechst 33342. The slides were visualized under a confocal microscope. 2.14. Statistical Analysis We performed univariate Cox proportional hazard analysis to identify hub genes significantly related to patient survival (p < 0.05). Genes that significantly correlated with patient survival in univariate analysis were included in multivariate Cox regression analysis. All data were statistically analyzed using GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, USA), and all experiments were independently repeated at least thrice. Measurement data were expressed as mean +- standard deviation (SD). Two groups of data were compared using an independent sample test-test. A value of p < 0.05 was regarded as statistically significant. 3. Results 3.1. DEGs Were Identified in Pancreatic Cancer Six datasets, namely GSE16515, GSE15471, GSE60979, GSE62452, GSE71989, and GSE91035, were obtained from the National Center for Biotechnology Information GEO database, which contains data for pancreatic cancer and normal tissue samples. A total of 1769 DEGs in GSE15471, 1277 DEGs in GSE16515, 2029 DEGs in GSE60979, 294 DEGs in GSE62452, 1966 DEGs in GSE71989, and 3020 DEGs in GSE91035 were identified using the criteria p < 0.05 and |log fold-change| > 1 . The Venn diagram shows that 123 genes were regulated . 3.2. Enrichment Analysis of DEGs The DAVID online tool was used to analyze the biological function of overlapping DEGs. GO in terms of BP, CC, and MF of overlapping DEGs among the regulated genes were analyzed. The most extensive BP enrichment was observed during extracellular matrix organization and collagen fibril organization; CC enrichment was the highest in the extracellular space and extracellular region; MF enrichment was the highest in extracellular matrix structural constituents and calcium ion binding. The investigation of the signaling pathway of the overlapping DEGs revealed that the protein digestion, absorption, and ECM-receptor interaction were the most important KEGG pathways . 3.3. Identification of the Key Gene, COL12A1 We collected the genes common for DEGs and collagen family genes. The Venn diagram shows that six collagen genes, COL1A1, COL3A1, COL5A2, COL8A1, COL10A1, and COL12A1, were identified between 123 DEGs and 32 collagen genes . The TCGA and GETx datasets indicated that COL1A1, COL3A1, COL5A2, COL8A1, COL10A1, and COL12A1 genes were expressed much higher in tumor tissues than in the normal ones . The survival rate was much worse for patients with high COL12A1 expression than that in patients with low expression. However, this is not the case for COL1A1, COL3A1, COL5A2, COL8A1, and COL10A1 . 3.4. Verification That COL12A1 Expression Was Much Higher in Tumor Tissues Than in Para-Cancer Tissues The Oncomine online tool indicated a higher COL12A1 expression in tumor tissues than that in normal tissues . COL12A1 expression was much higher in cancer tissue than in para-cancer tissue as indicated by the qPCR results . CPTAC and HPA indicated that the protein level of COL12A1 was significantly higher in tumor tissues than in normal tissues . 3.5. Clinical Characteristics of COL12A1 Much higher COL12A1 expression was observed in stages III/IV than in stages I/II . The expression of COL12A1 was significantly associated with the T stage, higher in T3/4 than that in T1/2 , but not in the N and M stages . In histologic grades, II/III/IV, much higher COL12A1 expression was observed than that in grade I (histologic grade in TCGA means the numeric value to express the degree of abnormality of cancer cells; it is a measure of differentiation and aggressiveness). High COL12A1 expression was positively correlated with a worse prognosis . The COL12A1 expression was much higher in dead patients than in alive people . The ROC curve indicated that COL12A1 might be a predictor for the survival rate of pancreatic cancer patients. The area under the curve was 0.579 for 1-year survival, 0.603 for 2-year survival, and 0.669 for 3-year survival . Moreover, based on the TCGA dataset, the progression-free interval (PFS) was much worse for patients with high COL12A1 expression than that for those with low expression (HR = 1.54, 1.04-2.29, p = 0.031) . The disease-specific survival (DSS) was much longer in low-COL12A1 expression patients than that in high-expression ones (HR = 1.98, 1.23-3.19, p = 0.005) . Univariable and multivariable cox regression analyses showed that the COL12A1 expression level was an independent determinant to predict the outcome of pancreatic cancer patients. . COL12A1 expression was combined with age, gender, and the T and N stages to build a nomogram for OS prediction . The nomogram is predictive of the OS for pancreatic cancer patients and demonstrates comparatively high accuracy, as shown by the calibration curves . 3.6. Genetic Alterations and Mechanism of Hub Gene Regulation We investigated the complex molecular properties of COL12A1 in PDAC tissues. The TCGA dataset was used to analyze genetic alterations, which were found to be 1.6% for COL12A1 in PDAC tissues. The COL12A1 methylation was negatively correlated to the COL12A1 mRNA expression in PDAC patients. However, the expression of methylated COL12A1 expression was much higher in tumor tissue than in normal tissue in the pancreas. In the pancreatic cancer tissues with P53 and KRAS mutation, COL12A1 expression is much higher than that in the wild-type pancreatic cancer tissues, as shown in Figure S2A-F. 3.7. COL12A1 Is Mainly Expressed in CAF and Correlated with Fibroblast Activation Protein Expression TISCH checking indicated that COL12A1 is primarily expressed in cancer-associated fibroblasts but not in tumor cancer cells or other immune cells in TME for pancreatic cancer . The expression of COL12A1 was significantly higher in CAF than in tumor cells as evidenced using qPCR . The different methods indicated COL12A1 was crucially related to cancer-associated fibroblast infiltration. Furthermore, COL12A1 expression correlated with the expression of the genes associated with fibroblast activation . 3.8. The Enrichment Function for COL12A1 COL12A1 co-expression networks were studied using the TCGA database to verify the potential function of COL12A1 in tumor tissues. A total of 616 genes were significantly upregulated to COL12A1, and 1586 genes were significantly downregulated to COL12A1 . LRRC53, TCP11X2, FGL1, C6orf58, and CALY represented the genes downregulated with COL12A1 expression. Conversely, EPYC, MAB21L2, CASP14, COL11A1, and APELA represented the genes upregulated with COL12A1 expression . The most enriched BP, CC, and MF were the extracellular matrix structural constituents, collagen-containing extracellular matrix, and extracellular matrix organization. The investigation of the signaling pathway of the overlapping DEGs revealed that the PI3K/AKT pathway was the most important KEGG pathway . Further, the pathway correlation results indicated that COL12A1 expression correlated with collagen formation, ECM-related genes, the TGF-b pathway, and the inflammation signature . Finally, CO112A1 expression was positively correlated with 27 out of 41 chemokines . 3.9. Knockdown of COL12A1 Reversed the Phenotype of CAFs, Inhibited Chemokines Expression, and Reversed the Promoting Effect on Pancreatic Cancer Cells We used a small interfering RNA (siRNA) to knock down COL12A1 in CAFs and explored the potential bio-function. COL12A1 mRNA expression was significantly downregulated in CAFs transfected with siCOL12A1 compared with siNC . The findings from the EDU assay indicated that COL12A1 knockdown inhibited the proliferation ability of CAFs . Transwell migration and wound healing activities were compromised after COL12A1 knockdown . In addition, the immunofluorescence intensity of ACTA2 and the number of ACTA2 fibers were reduced after COL12A1 knockdown in CAFs . The western blot demonstrated that COL12A1 knockdown can decrease the protein level of ACTA2, FAP, and FSP . Moreover, we observed a decrease in IL6, CXCL5, and CXCL10 expression in siCOL12A1 CAFs compared to that that in the siNC groups . Importantly, the culture medium of CAFs treated with siNC or siCOL12A1 was collected. The two kinds of conditional medium were added into pancreatic cancer cell PANC-1. The colony formation assay results implied that COL12A1 knockdown reversed the promoting effect of CAF on PANC-1 cells . 4. Discussion The occurrence and development of the solid tumor are accompanied by the connective tissue hyperplasia reaction and the deposition and remodeling of the tumor matrix, which can lead to significant changes in the tumor microenvironment . The change in cell polarity and loosening of the adhesion between cells in the tumor environment occurred through alterations in the composition and accumulation mode of the extracellular matrix, resulting in the promotion of tumor growth, invasion, and metastasis . Abnormal extracellular matrix (ECM), as a major component of PDAC stroma, regulated malignant cell behavior, and induced tumor formation and progression . In this study, 123 DEGs were selected in pancreatic cancer from 6 GEO datasets. For enrichment analysis of the overlapping 123 DEGs, the extracellular matrix structural constituent exhibited the most enrichment for molecular function, the extracellular matrix organization was one of the most enriched of the biological processes, and the extracellular space and the extracellular region experienced the highest enrichment for the cellular component. ECM-receptor interaction was one of the most important KEGG pathways for pathway signaling. These results indicated that the change in the ECM played a crucial role in pancreatic cancer genesis and development. Collagen, as the main component of the extracellular matrix, performs some key functions in the development of tumors . Different collagen proteins played different roles in the occurrence and development of pancreatic cancer. Some can promote tumor metastasis, while others can inhibit tumor growth . Hence, we hypothesized that certain collagens perform important roles in the occurrence and development of pancreatic cancer. We crossed the DEGs with 32 genes in the collagen family. Six collagen family genes were used for prognostic analysis in pancreatic cancer tissue. Only the COL12A1 gene was found to be notably related to the survival and prognosis of pancreatic cancer, but the others had no significant association, as shown in Figure 1. Therefore, we focused on COL12A1 to explore its mechanism in the occurrence and development of pancreatic cancer. Thirty-one pairs of clinical specimens were used to verify that COL12A1 expression in pancreatic cancer tissue was significantly higher than that in para-cancerous tissue. The result indicated COL12A1 might be a diagnosis and prognosis biomarker in pancreatic cancer. Several published papers have already indicated that COL12A1 might be the key prognosis biomarker for pancreatic cancer. Ding and Chen et al. indicated that MMP14 and COL12A1 constituted the potential combination of prognostic biomarkers in pancreatic cancer based on bioinformatics analysis. Performing bioinformatic analysis, Jing and Chen indicated that COL12A1 was the potential prognosis biomarker in pancreatic cancer . However, the aforementioned results are primarily based on large databases and are thus lacking in vitro and in vivo findings or real-world data. Simultaneously, the source and mechanism of COL12A1 secretion are not evident. Therefore, using bioinformatic analysis and experimental verification, we further explored the source of COL12A1 and investigated the mechanism of its involvement in tumor genesis and development. CAFs are the main contributor to tumor fibrosis, through increasing the synthesis of ECM proteins such as collagens and cross-linking enzymes, which could create a tumorigenic fibrotic environment around the PDAC tumor. Tumor fibrosis was closely associated with pancreatic cancer progression and drug resistance . In the current study, the single-cell analysis revealed that COL12A1 was mainly distributed in CAF cells but not in tumor cells and other adjacent cells. Furthermore, the results from our cell line analysis indicated that the COL12A1 expression in the extracted para-cancerous fibroblasts was significantly higher than that in pancreatic cancer cells. CIBERSORT, xCELL, TIDE, and EPIC analysis for the dataset indicated that COL12A1 was correlated with CAF infiltration. These results revealed that COL12A1 was mainly derived from CAFs in pancreatic cancer. This finding is consistent with the previously published results related to breast and colon cancers , which indicated that COL12A1 is mainly expressed in CAF cells. COL12A1 secreted by CAF can change type I collagen tissue, support the pre-invasion microenvironment of metastatic transmission, and promote organ regeneration. Furthermore, we verified that COL12A1 expression could induce CAF cells to express the fibro-activated proteins ACTA2, FAP, and FSP, enhancing the cell invasion and release of inflammatory factors. Simultaneously, COL12A1 could promote tumor cell growth in a paracrine manner. A substantial amount of data has indicated that CAFs act not only as bystanders but are actively involved in the process of cancer initiation, progression, and metastasis. Hence, the CAFs can be considered as the tumor promoter in pancreatic cancer . The most commonly exploited CAF biomarkers in PDAC are ACTA2, FAP, vimentin, FSP1, podoplanin (PDPN/gp38), and platelet-derived growth factor receptor alpha and/or beta (PDGFRa/b) . Our results also indicated that the expression of COL12A1 positively correlated with PDGFRB, ACTA2, S100A4, VIM, and FAP expressions at the mRNA level in the TCGA dataset. The CAFs in pancreatic cancer demonstrated heterogeneity for three types: myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen-presenting CAFs (apCAFs). These three types can be separated by the biomarkers of myCAF, which exhibits the high expression of ACTA2, FAP, and TGF-b, and low expression of IL6, which requires direct interaction with cancer cells in PDAC and might be associated with tumor progression. ICAF, with low ACTA2 expression and high IL6 secretion, can be activated by paracrine factors secreted from tumor cells. However, the location of ICAF was found to be far from the tumor cells and myCAF. Moreover, apCAFs, expressed by MHC class II family genes, exhibit an antioxidant response. The activation and location of the apCAFs need further exploration to be fully understood . Several studies have indicated that the TGF-b pathway can induce fibroblast transformation into myCAF and inhibit iCAF transformation. The findings of our study involving bioinformatic analysis indicated that COL12A1 expression was positively associated with the TGF-B pathway. The knockdown of COL12A1 inhibited ACTA2, FAP, and FSP1 expressions, which might indicate that COL12A1 expression is associated with myCAF transformation and activation. In the CAF subtype analysis, FAP + CAF could induce PDAC progression and indicate worse survival. However, the function of aSMA + CAF was controversial. Athleen. et al. used single-cell RNA sequencing and several genetic mouse models to show that the depletion of FAP + CAF leads to increased survival, but depleting aSMA + CAFs resulted in decreased survival. However, depleting IL6 in a-SMA + CAF could increase gemcitabine sensitivity for the PDAC mice through T cell regulation . Furthermore, Yurina et al., using 215 under-treatment PDAC patient samples, reported that aSMA-dominant and FAP-dominant fibroblast-rich stroma indicated poor prognosis . Sun et al. used in vitro and in vivo experimental results to indicate that CXCR2/CXCL3 enhanced PDAC metastasis by inducing CAF toward myoCAF transformation and upregulated a-SMA expression . Herein, we also found that COL12A1 knockdown can suppress CAF invasion and inhibit CAF biomarker aSMA and FAP expressions and cytokine IL6, chemokine CXCL5, and CXCL10 expression. The bioinformatics analysis also indicated that COL12A1 expression was highly associated with cytokine and chemokine expressions, such as IL6, IL8, CXCL5, and CXCL10 expressions. Furthermore, the colony formation of tumor cells can be suppressed when cultured in a conditional medium, which was collected from siCOL12A1 CAFs but not in the one collected from the group with siNC CAFs. The aforementioned result indicated that CAF expresses COL12A1 and could enhance tumor growth in a paracrine manner through increasing cytokine or chemokine secretion. The above results indicated that COL12A1 might provide new opportunities for TME-targeted therapies in pancreatic cancer. However, the exact mechanism of how COL12A1 effect CAF transformation as well as which subtype CAF was changed and induced tumor growth still not fully elucidated. The key factor that caused the COL12A1-induced tumor growth needs further exploration. Despite many useful inputs, there are several limitations in our research. First, the CAF collected herein were combined with myCAF, iCAF, and apCAF, which did not separate. In further studies, we need to investigate which part of CAFs expressed COL12A1, and thus plays an important role in tumor growth. Second, the prognosis value and pathways were primarily considered by the dataset but not our own clinical samples. Hence, it is possible that in a further study, we need to check OS for our clinical sample for further validation of the results. In this research, we systematically analyzed the mechanism involved in using COL12A1 as a therapy target and prognosis biomarker for pancreatic cancer. Our study demonstrated the potential diagnostic and prognostic value of COL12A1 expression in pancreatic cancer and elucidated the possible molecular mechanism underlying its role in promoting the development of pancreatic cancer in CAFs. These findings indicate that COL12A1 acts as a novel prognosis biomarker and provides new opportunities for TME-targeted therapies in pancreatic cancer. 5. Conclusions Our study demonstrated the potential diagnostic and prognostic value of COL12A1 expression in pancreatic cancer and elucidated the molecular mechanism underlying its role in CAFs and promoting the development of pancreatic cancer. These findings might provide new opportunities for TME-targeted therapies in pancreatic cancer. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Survival rates for COL1A1, COL3A1, COL5A2, COL8A1, and COL10A1 high and low expressions in pancreatic cancer; Figure S2: Genetic Alterations and Mechanism of COL12A1 Regulation; Figure S3: Represented genes correlated with COL12A1 expression. Click here for additional data file. Author Contributions Y.S. and P.Z. wrote the manuscript; Y.S. and P.Z. analyzed the data and performed cell experiments; L.W. and K.W. collected the patients' samples and analyzed parts of the data; P.Z. and Y.L. revised the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Affiliated Hospital of Nantong University (approval no. 2019-L034, date: 4 March 2019). Informed Consent Statement Informed consent was obtained from all patients involved in the study. Written informed consent has been obtained from the patients to publish this paper. Data Availability Statement All data generated or analyzed during this study are included in this published article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 DEGs and their functions in GSE15471, GSE16515, GSE60979, GSE62452, GSE71989, and GSE91035. (A) Volcano plot of DEGs between pancreatic cancer tissues and normal pancreas tissues in the GSE15471, GSE16515, GSE60979, GSE62452, GSE71989, and GSE91035 datasets. (B) Venn diagram of overlapping 123 DEGs from the GSE15471, GSE16515, GSE60979, GSE62452, GSE71989, and GSE91035 datasets; (C) GO (Biological process) analysis of the overlapping DEGs in pancreatic cancer. (D) GO (Cellular component) analysis of the overlapping DEGs in pancreatic cancer. (E) GO (Molecular function) analysis of the overlapping DEGs in pancreatic cancer. (F) KEGG pathway analysis of the overlapping DEGs in pancreatic cancer. Figure 2 Identification of the key gene, COL12A1. (A) Venn diagram of overlapping 6 DEGs from 123 DEGs in the GSE15471, GSE16515, GSE60979, GSE62452, GSE71989, and GSE91035 datasets and 32 collagens. (B) Gene Expression Profiling Interactive Analysis (GEPIA) was performed to validate the expression of six hub genes in pancreatic cancer samples compared with normal samples. Red box was the cancer tissue group, gray was the normal tissue group, and asterisk represented p < 0.01. The dots represented expression in each sample. (C) Check the Over survival (OS) curves of COL12A1 in pancreatic cancer tissues in TCGA dataset. (p < 0.05). Figure 3 Verification that COL12A1 expression was much higher in tumor tissues than in para-cancer tissues. (A) Oncomine was performed to validate the expression of COL12A1 in pancreatic cancer samples compared with normal samples. (B) COL12A1 expression levels in 31 pairs of fresh pancreatic cancer tissues and their para-cancer tissues. (COL12A1/GAPDH). (C) Verified COL12A1 expression was much higher in tumor tissues than in normal tissues in the CPTAC datasets. (D) Immunohistochemistry of COL12A1 based on the Human Protein Atlas. ***, p < 0.001. Figure 4 COL12A1 expression separated by different characters. (A) Pathological stages; (B) T stage; (C) N stage; (D) M stage; and (E) Histologic grade. *, p < 0.05, ***, p < 0.001, ns, non-significant. Figure 5 The clinical prognosis of COL12A1 in pancreatic cancer. (A) The dead and alive patients in low-COL12A1 expression people and high-COL12A1 expression people. (B) OS event in low-COL12A1 expression people and high-COL12A1 expression people. (C) Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) statistics were implemented to evaluate the capacity of COL12A1 to identify the prognosis in pancreatic cancer. (D) The progression-free interval (PFI) curve of COL12A1 in pancreatic cancer (p < 0.05). (E) Disease-specific survival (DSS) curve of COL12A1 in pancreatic cancer (p < 0.05). (F) Univariable analysis for the OS analysis in pancreatic cancer in the TCGA dataset. (G) Multivariate analysis for the OS analysis in pancreatic cancer analysis in the TCGA dataset. *, p < 0.05. Figure 6 Nomogram analysis for pancreatic cancer over survival. (A) The nomogram analysis involving COL12A1 expression, age, gender, and the T and N stages to predict the prognosis in pancreatic cancer patients. (B) Predicted survival ability of this nomogram for 1, 2, and 3 years. Figure 7 COL12A1 is mainly expressed in CAF and correlated with fibroblast activation protein expression. (A) TISCH checking indicated the major COL12A1-expressing cells in pancreatic cancer. (B) qPCR verified the COL12A1 expression in pancreatic cancer cell lines and cancer-associated fibroblast cells. (C) Relationship between COL12A1 and cancer-associated fibroblast infiltration in pan-cancer. (D) COL12A1 and cancer-associated fibroblast in pancreatic cancer infiltration were checked using the EPIC, MCPCOUNTE, XCELL, and TIDE methods. (E) Correlations between COL12A1 and fibroblast activation protein expression. Figure 8 Enrichment function for COL12A1. (A) Volcano plot of DEGs between high and low COL12A1 expressions. (B) GO analysis of the DEGs based on the COL12A1 expression in pancreatic cancer. (C) KEGG analysis of the DEGs based on the COL12A1 expression in pancreatic cancer. (D) COL12A1 and associated pathway in high and low COL12A1 expressions. (E) Correlation of COL12A1 expression and chemokines in PDAC. Figure 9 Verification of the function of COL12A1 in CAF and tumor cells. (A) COL12A1 mRNA expression in siNC-transfected CAFs. (B) EDU assay indicated the proliferation ability of CAFs in the siCOL12A1 and siNC groups. (C) Transwell assay analyzed the CAFs migration after COL12A1 knockdown. (D) Wound healing checked the CAFs migration in siNC-transfected CAFs. (E) Immunofluorescence intensity of ACTA2 and the number of ACTA2 fibers were checked after COL12A1 knockdown in CAFs. (F) Western blot demonstrated the protein level of ACTA2, FAP, and FSP expressions after COL12A1 knockdown in CAFs. (G) qPCR checked IL6, IL8, CXCL5, and CXCL10 expressions in siNC-group CAFs. (H) Collected the supernatant from siNC-group CAFs and then added it to incubate Panc-1 cells. Detected the clone formation of Panc-1 cells with conditional medium (*, p < 0.05, **, p < 0.01, ***, p < 0.001, ns, non-significant). cancers-15-01480-t001_Table 1 Table 1 The primer sequence. Primer Sequence CXCL8-F TGGCAGCCTTCCTGATTTCT CXCL8-R TTTCTGTGTTGGCGCAGTGT IL6-F AGTGGCTGCAGGACATGACAA IL6-R CAATCTGAGGTGCCCATGCTA CXCL5-F GAGAGAGCTGCGTTGCGTTT CXCL5-R TTCAGGGAGGCTACCACTTC CXCL10-F CCTCTCTCTAGAACTGTACGCT CXCL10-R TCAGACATCTCTTCTCACCCT COL12A1-F TATTGTGTTCTTGACTGATGCCTCCTG COL12A1-R AGACTTGACCTCATCGCTGTATTGC GAPDH-F GCCAAAAGGGTCATCATCTC GAPDH-R TGAGTCCTTCCACGATACCA Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
PMC10000533 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050894 diagnostics-13-00894 Article Gene Mutation Spectrum among Alpha-Thalassaemia Patients in Northeast Peninsular Malaysia Vijian Divashini 1 Wan Ab Rahman Wan Suriana 12* Ponnuraj Kannan Thirumulu 1 Zulkafli Zefarina 23 Bahar Rosnah 23 Yasin Norafiza 4 Hassan Syahzuwan 4 Esa Ezalia 4 Deconinck Eric Academic Editor 1 School of Dental Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia 2 Hospital Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia 3 Department of Hematology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia 4 Haematology Unit, Cancer Research Centre, Institute for Medical Research, Shah Alam 40170, Selangor, Malaysia * Correspondence: [email protected]; Tel.: +60-97675832; Fax: +60-97675505 27 2 2023 3 2023 13 5 89429 12 2022 18 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). (1) Background: Alpha (a)-thalassaemia is a genetic disorder that affects 5% of the world population. Deletional or nondeletional mutations of one or both HBA1 and HBA2 on chromosome 16 will result in reduced production of a-globin chains, a component of haemoglobin (Hb) that is required for the formation of red blood cells (RBCs). This study aimed to determine the prevalence, haematological and molecular characterisations of a-thalassaemia. (2) Method: The parameters were based on full blood count, high-performance liquid chromatography and capillary electrophoresis. The molecular analysis involved gap-polymerase chain reaction (PCR), multiplex amplification refractory mutation system-PCR, multiplex ligation-dependent probe amplification and Sanger sequencing. (3) Results: With a total cohort of 131 patients, the prevalence of a-thalassaemia was 48.9%, leaving the remaining 51.1% with potentially undetected a gene mutations. The following genotypes were detected: -a3.7/aa (15.4%), -a4.2/aa (3.7%), --SEA/aa (7.4%), aCSa/aa (10.3%), aAdanaa/aa (0.7%), aQuong Szea/aa (1.5%), -a3.7/-a3.7 (0.7%), aCSa/aCSa (0.7%), -a4.2/aCSa (0.7%), -SEA/aCSa (1.5%), -SEA/aQuong Szea (0.7%), -a3.7/aAdanaa (0.7%), --SEA/-a3.7 (2.2%) and aCSa/aAdanaa (0.7%). Indicators such as Hb (p = 0.022), mean corpuscular volume (p = 0.009), mean corpuscular haemoglobin (p = 0.017), RBC (p = 0.038) and haematocrit (p = 0.058) showed significant changes among patients with deletional mutations, but not between patients with nondeletional mutations. (4) Conclusions: A wide range of haematological parameters was observed among patients, including those with the same genotype. Thus, a combination of molecular technologies and haematological parameters is necessary for the accurate detection of a-globin chain mutations. a-thalassaemia genotype mutation globin prevalence molecular analysis Universiti Sains Malaysia Research University1001/PPSG/8012366 This study was funded by a Universiti Sains Malaysia Research University (individual) grant (1001/PPSG/8012366). pmc1. Introduction Haemoglobinopathies are inherited disorders caused by alterations in the globin genes (a and b), thus affecting the production of their proteins and synthesis of haemoglobin (Hb) in red blood cells (RBCs). The mutated globin genes may produce abnormal proteins that determine the Hb variant, or it may cause a reduction in the affected globin expression that subsequently leads to alpha (a-) or beta (b-) thalassaemia . The World Health Organization (WHO) estimates that 5% of the world's population are carriers of a-thalassaemia, with the majority being Southeast Asians . Besides Southeast Asia, the disorder is also prevalent in Mediterranean countries, the Middle East, Central Asia, India, Southern China, North Africa, and South America. The mutated globin genes have different combinations that can produce more than 60 thalassaemia syndromes, making Southeast Asia the region with the most complex disease genotype . Alpha (a)- and beta (b)-thalassaemia are caused by defects in HBA and HBB genes, respectively. Mutations of HBA1 and HBA2 on chromosome 16 will result in a-thalassaemia. A meta-analysis reported the prevalence of a-thalassemia in 22.5% of the population in Southeast Asia and 17.5% in Malaysia alone . Individuals with a single a-globin gene defect are silent carriers who will have no manifestation of the disease. Individuals who inherit two defective a-globin chains are known as a-thalassaemia traits and may display mild symptoms of anaemia. When three a-globin chains are affected, it results in Hb H, which is a moderate to severe form of the disease that requires lifelong health monitoring . The most severe form of a-thalassaemia is Hb Barts, in which all four a-globin genes are defective, and it is not compatible with life . This condition mostly affects foetuses, which may develop hydrops fetalis and end up stillborn. a-thalassaemia may occur due to deletional or nondeletional mutations in the a-globin gene, and the former has been observed to be more common. However, the clinical outcome among nondeletional a-thalassaemia individuals is more severe compared with deletional individuals. This is because nondeletional mutations usually involve HBA2, which has higher expression than HBA1 in a 3:1 ratio . Thus, it has a huge impact on the production of a-globin chains. The most common single deletional mutations detected in Southeast Asia are -a3.7 and -a4.2. Apart from those, the most common double-gene deletions reported worldwide are -(a)20.5, --SEA, --MED, --THAI and --FIL . The common nondeletional variants of a-thalassaemia mutations reported in Southeast Asia are Hb Constant Spring (CS), Hb Quong Sze and Hb Adana, whereas codon 30 and codon 35 mutations are rarely identified . Therefore, the aim of this study was to investigate the haematological and molecular characterisations of a-globin gene mutations and their variants in patients diagnosed with a-thalassaemia at the Hospital Universiti Sains Malaysia. The institution is an established teaching hospital of a public university in the northeast state of Kelantan in Peninsular Malaysia. It mostly serves as a referral centre for medical treatments on the east coast of the peninsula. 2. Materials and Methods 2.1. Patient Screening and Selection This cross-sectional study involved 131 patients suspected of having a-thalassaemia based on haematological parameters (mean corpuscular haemoglobin (MCH) < 27 pg and mean corpuscular volume (MCV) < 80 fl). Those with normocytic and normochromic indices were excluded. Upon obtaining informed consent, two millilitres of peripheral blood samples were collected in ethylenediaminetetraacetic acid (EDTA) tube. The Hb concentrations and red cell indices were determined using an automated blood cell counter. The quantitation of Hb was performed using an automated high performance liquid chromatography (HPLC) and capillary electrophoresis (CE) system. Molecular tests were conducted on patients suspected of a-thalassaemia. This study was approved by the Medical Research and Ethics Committee (NMMR-21-606-58737) and the Human Research Ethics Committee of Universiti Sains Malaysia (USM/JEPeM/20020104). 2.2. Haematological Analysis The Sysmex XN-1000 automated haematology analyser (Sysmex America Inc., Lincolnshire, IL, USA) was used to obtain the parameters of whole blood samples (MCH, MCV and MCHC). Preparation of blood samples for HPLC and CE was carried out according to the institution's routine protocols. In HPLC, the VARIANT II b-Thalassemia Short Programme (Bio-Rad Inc., Hercules, CA, USA) was used to detect the level of Hb A2 and Hb F. The programme utilised the cation exchange principle to separate Hb variants in patients' blood. The presence of variants such as Hb H, Hb Barts and Hb Constant Spring was quantified through CE using the CAPILLARYS 2 Flex Piercing instrument (SEBIA, Lisses, France). 2.3. DNA Extraction DNA was extracted from patients' whole blood using the QIAamp DNA Blood Minikit (Qiagen GmBH, Dusseldorf, Germany) according to the manufacturer's instructions. The concentration and purity of extracted DNA were determined using the Eppendorf BioPhotometer spectrophotometer (Eppendorf GmBH, Hamburg, Germany). 2.4. Multiplex Gap-PCR The extracted DNA was subjected to multiplex gap-polymerase chain reaction (gap-PCR) to detect deletions in a-globin genes. The multiplex gap-PCR contained mutation-specific primers for amplification of --SEA, -a3.7, -a4.2, --FIL, --THAI, -(a)20.5 and --MED. All positive controls for known genotypes were provided by the Haematology Unit of the Cancer Research Centre at the Institute for Medical Research in Selangor, Malaysia. The primer sequences shown in Table S1 are available in the "Supplementary Materials" and were based on a previous study . Amplification was carried out in a 25 mL reaction volume consisting of 50 ng of DNA template, 2.5 U of HotStarTaq master mix (Qiagen, Dusseldorf, Germany), 1x Q solution (Qiagen, Dusseldorf, Germany), forward and reverse primers and nuclease-free water. The concentration of each primer used is shown in Table S1. PCR was carried out in a thermocycler (Bio-Rad, Hercules, CA, USA), beginning with initial denaturation at 96 degC for 15 min, followed by 30 cycles of denaturation (98 degC, 45 s), annealing (64 degC, 1 min 30 s) and extension (72 degC, 2 min 30 s). In the final extension, the reaction was allowed to run at 72 degC for 5 min before terminating at 8 degC. 2.5. Multiplex Amplification Refractory Mutation System-Polymerase Chain Reaction Multiplex amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) was performed to detect nondeletional mutations in the a-globin gene. The method can detect common mutations that occur in the initiation codon (c.2delT), codon 30 (c.91_93delGAG), codon 35 (c.106T>C), Hb Adana (c.179G>A), Hb Quong Sze (c.377T>C) and Hb Constant Spring (c.427T>C). The primer sequences used had been stated in a previous study . Amplification was carried out in a 25 mL reaction volume consisting of 50 ng of DNA template, 2.5 U of HotstarTaq master mix (Qiagen, Dusseldorf, Germany), 1x Q solution (Qiagen, Dusseldorf, Germany), forward and reverse primers and nuclease-free water. The concentration of each primer used shown in Table S2 is available in the "Supplementary Materials". PCR began with an initial denaturation at 96 degC for 15 min, followed by 30 cycles of denaturation (98 degC, 45 s), annealing (62.4 degC, 1 min) and extension (72 degC, 2 min 30 s). Final extension was performed at 72 degC for 5 min before the PCR products were subsequently cooled to 8 degC. 2.6. Duplex-PCR Samples with mutations identified through multiplex ARMS-PCR were further tested with duplex-PCR to determine zygosity for the detected mutation (zygosity test). The zygosity test helps to identify whether the patient carries homozygous or heterozygous nondeletional mutations. Each designed PCR reaction volume consisted of a 25 mL reaction volume of 2.5 U HotstarTaq master mix, 1x Q solution, forward and reverse primers and nuclease-free water. The designed master mix was only able to detect the heterozygosity for each mutation. PCR was carried out under the following conditions: initial denaturation at 96 degC for 15 min, followed by 30 cycles of denaturation at 98 degC for 45 s, annealing at 62.4 degC for 1 min, extension at 72 degC for 2 min 15 s and final extension at 72 degC for 5 min. 2.7. Agarose Gel Electrophoresis The PCR products of multiplex gap-PCR were subjected to electrophoresis at 110 V for 40 min in a 1% agarose gel, whereas the products of multiplex duplex-PCR were run on a 2% agarose gel. All gels were stained with Florosafe DNA stain (1st BASE, Singapore) and visualised under ultraviolet (UV) rays in an image analyser. 2.8. Multiplex Ligation-Dependent Probe Amplification The DNA samples of subjects who were determined to have no mutations in their a-globin genes after multiplex gap-PCR and ARMS-PCR were subjected to multiplex ligation-dependent probe amplification (MLPA) to screen for rare deletions. The SALSA MLPA Probemix P140-C1 HBA (MRC Holland, Amsterdam, The Netherlands) was used according to the manufacturer's instructions. The SALSA MLPA reagent kit contained 45 MLPA probes that could be used to detect sequences in the a-globin gene cluster and their flanking regions. A comparative analysis of fragments was performed using the probe manufacturer's Coffalyser.Net software to identify the deleted regions in HBA. 2.9. Sanger Sequencing All the samples that were negative for mutations in multiplex gap-PCR, multiplex ARMS-PCR and MLPA were subjected to Sanger sequencing for detection of rare nondeletional mutations. The target genes of HBA1 and HBA2 were amplified separately before being sequenced. The master mix consisted of 50 mL reaction volume, 50 ng of DNA template, 2.5 U HotstarTaq plus master mix (Qiagen, Dusseldorf, Germany,) 0.5x Q solution (Qiagen, Dusseldorf, Germany), forward and reverse primers and nuclease-free water. The PCR conditions for the amplification of target genes used were an initial denaturation at 96 degC for 5 min, followed by 35 cycles of denaturation at 98 degC for 45 s, annealing at 64 degC for 1 min 30 s and extension at 72 degC for 2 min 30 s. The amplified target genes were sent to Apical Scientific Sdn Bhd and Institute for Research in Molecular Medicine, Universiti Sains Malaysia, for sequencing. The results were analysed using BioEdit version 7.2. The wild-type sequences of target genes were retrieved from the National Center for Biotechnology Information (NCBI) under accession number NG 000006.1 and aligned with the sequencing results for mutation identification. 2.10. Statistical Analysis All the data were analysed using IBM SPSS version 22 (IBM Corp, Armonk, NY, USA). The Kruskal-Wallis test with Dunn-Bonferroni post hoc correction was used to determine whether there were significant variations between haematological parameters according to individual a-thalassaemia mutations. A p-value of <0.05 was considered significant. 3. Results Among 131 subjects, 72 (55.0%) were female, and the remaining 59 (45.0%) were male. Most of them were aged 21 and above (n = 79, 60.3%), followed by 1-12-year-olds (n = 40, 30.5%), 13-20-year-olds (n = 10, 7.6%) and 1-11-month olds (n = 2, 1.5%). Ethnically, 96.2% of the subjects were Malays, followed by 3.1% Chinese and 0.8% Indians. Multiplex gap-PCR and ARMS-PCR determined that 64 (48.9%) subjects had a-thalassaemia. Among the a-thalassaemia cases identified, 37 (57.8%) carried deletional mutations in HBA, whereas 18 (28.1%) had nondeletional mutations. The remaining nine subjects (14.1%) were identified as having compound heterozygous for a-thalassaemia. However, there were no mutations detected in the MLPA and Sanger sequencing analyses, leaving 67 (51.1%) subjects with no detectable mutations in HBA1 and HBA2. There were single (-a3.7/aa and -a4.2/aa) and double-gene (--SEA/aa) deletional mutations detected. The point mutations identified were as follows: aCSa/aa, aAdanaa/aa and aQuong Szea/aa. The type of a-globin gene mutations is listed in Table 1. Figure 1 and Figure 2 show the PCR genotype results for common deletional and nondeletional a-globin gene mutations, respectively. Analyses of Haematological Parameters The haematological parameters, including Hb, MCV, MCH, MCHC, red blood cells (RBCs), red cell distribution width (RDW), haematocrit (Hct) and quantification of Hb A2, Hb A and Hb F were analysed for differences among genotypes. As shown in Table 2, the Kruskal-Wallis test found significant differences between deletional mutations in Hb, MCV, MCH, RBC and Hb A2, but none in MCHC, RDW, Hct, Hb A and Hb F. The haematological parameters of nondeletional mutations are shown in Table 3. The haematological parameters of compound heterozygous patients, including the CE analysis, are shown in Table 4. Furthermore, in the CE analysis, the Hb Constant Spring value among the compound heterozygous patients with Constant Spring genotypes had a mean value +- SD of 2.13 +- 1.06, while Hb H values of patients with --SEA/ aQuong Szea, --SEA/aCSa and --SEA/-a3.7 were 6.4%, 2.4-12.2% and 5.1-12.2%, respectively. The Hb Barts mean values among compound heterozygous patients with --SEA/ aQuong Szea, --SEA/aCSa and aCSa/ aAdanaa were 29.2%, 0.9-1.8% and 0.8%, respectively. On the other hand, in the compound heterozygous group, the majority of patients presented as Hb H phenotype, while some had fraction(s) of Hb H and/or Hb Barts. There were also three Hb Constant Spring variants identified in the compound heterozygous group with a mean +- SD value of 2.13 +- 1.06%. 4. Discussion The prevalence of a-thalassaemia in this study was 48.9%. In a previous study, 22.5% of a-thalassaemia cases worldwide had been reported in Southeast Asian countries, and 17.5% of them were in Malaysia . However, that prevalence varied among geographical areas and ethnicity. Malaysia is a multiracial country with a Malay majority, followed by Chinese, Indians and other small groups such as the Siamese. Kelantan state, which is where our institution is located, is next to south Thailand, a country that has a 20.1% prevalence of a-thalassaemia. Many people in northern Peninsular Malaysia are related to those in south Thailand due to intermarriage and migration throughout time . The most common deletional mutation was the -a3.7 genotype, followed by aaCS, --SEA, -a4.2 and aaQuong Sze, and the least common was aaAdana. The findings were in accordance with a few local studies . Similar distributions of mutations have been reported in neighbouring countries, including Thailand , Laos , Cambodia and Vietnam . Among nondeletional mutations, Hb Constant Spring was the most prevalent in this study, followed by Hb Quong Sze. These findings are similar to other local studies and in Southeast Asia . This study showed similar frequency patterns in which 10.3% of patients had Hb Constant Spring (n = 14), followed by Hb Quong Sze (n = 2, 1.5%). Compound heterozygous a-thalassaemia patients had a different mutation in each a-globin chain. In this study, 6.6% of patients (n = 9) were diagnosed with compound heterozygous a-thalassaemia, which were --SEA/-a3.7 (n = 3) and --SEA/aCSa (n = 2), and one patient each with the following genotypes: -a4.2/aCSa, --SEA/aQuong Szea, -a3.7/aAdanaa and aaCS/aAdanaa. Compound heterozygous --SEA/-a3.7 had only one unaffected a-globin gene leading to Hb H disease, which has been commonly reported worldwide. Similarly, Malaysia , Thailand and Taiwan had reported --SEA/-a3.7 as a common compound heterozygous deletional mutation in their population. This study showed that 2.2% of patients had --SEA/-3.7, and this was the most common compound heterozygous deletion detected in the studied population. Single-gene deletion mutations, including -a3.7 and -a4.2, resulted in asymptomatic/mild clinical manifestations. Most carriers of a single globin gene deficiency had normal Hb due to a compensatory increase in the number of microcytic RBCs. Such individuals would not experience severe anaemia-related symptoms, such as fatigue or weakness . If the diagnostic criteria solely depended on haematological parameters, then this would lead to misdiagnosis . There were no significant differences in Hb levels between -a4.2 and -a3.7 patients. However, some parameters, including Hb, MCHC, RBC and Hct, were lower in the heterozygous 3.7 kbp a deletion patients compared with those who had the 4.2 kbp deletion, even though both had lower readings in these parameters. Previously, few studies reported mildly low to normal levels of MCV and MCH among similar genotypes . In this study, there were no significant differences in the parameters between aa/aa and the heterozygous -a3.7 observed in the further statistical test, post hoc analysis. This is probably because the aa/aa group of suspected thalassaemia patients might have other conditions/diseases that affected haematological parameters. The normal range of Hb A2 is between 2.2% and 3.2% . Hb A2 levels in individuals with a single a-globin gene deletion are within the normal range. Consistent with that, in this study, the mean value of Hb A2 among the a-thalassaemia patients was 3.03%. However, a slight increase in Hb A2 levels was observed in two patients with normal Hb F. Hb A2 comprised two a-globin chains and two delta (d)-globin chains (a2d2), and its level was also a significant marker of b-thalassaemia. The defective b-globin gene could result in the absence or reduction of b-globin chain synthesis, leading to an excess of a-globin chains and subsequent formation of Hb A2 . There were also other factors that could cause an increase in Hb A2 levels, including vitamin B12 deficiency, folate deficiency, antiretroviral therapy and hyperthyroidism . In this study, the cause of elevated Hb A2 level was not further investigated, including in b-thalassaemia genotyping. No significant differences in haematological parameters and Hb quantification were also detected in double-gene deletion patients. Under normal circumstances, the level of Hb F would decrease with increased gestational age. In adults, the normal Hb F level is <1%, and a decrease in Hb F has been reported with more defective a-globin genes . However, no significant differences were identified among the double-gene deletions in this study. Moreover, the level was within the normal range among the patients. A study suggested that the level of Hb F would increase with a greater number of b-globin genes affected in b-thalassaemia , whereas a-thalassaemia patients usually have normal Hb F levels . The double-gene deletion showed a significantly lower level of MCV, MCH and MCHC compared with silent-trait groups . A similar outcome was found in this study, in which --SEA patients showed the lowest median values for MCV, MCH and MCHC compared with other deletional groups. In addition, --SEA patients showed significantly lower levels of MCV and MCH than -a3.7 patients. The Hb level in a patient with the homozygous a3.7 genotype showed the lowest level among other deletional groups, followed by heterozygous --SEA patients. The homozygous a3.7 had two deleted genes with a similar haematological parameter range as in the heterozygous a double-gene mutations. . The Hb A2 level was within the normal range for all patients, and the lowest median for Hb A2 was observed in the heterozygous --SEA mutation. Carriers of double-gene deletions usually present with a normal or slightly lower Hb A2 level . RDW measures the variation in RBC size and plays an important role in differentiating between iron-deficiency anaemia (IDA) and thalassaemia traits. IDA patients commonly report higher RDW levels compared with thalassaemia . The level of RDW in thalassaemia patients is usually normal or slightly increased, reflecting uniformity in RBC size and microcytes . Thalassaemia patients in this study showed normal to slightly low RDW. However, the value of RDW increased with the increased number of defective genes in thalassaemia patients . A similar finding has also been reported in which higher RDW levels were found in cases with more affected a-globin genes . In contrast, a mild elevation in RDW has been observed in the a-thalassaemia trait compared with the normal genotype . However, in this study, there were no significant differences among the different deletional mutations at the RDW level. In addition, the heterozygous --SEA patient presented with the lowest median value of RDW compared with other deletional groups. Nondeletional mutations show diverse haematological parameters depending on the mutated region and its interaction with b-globin chains . The mutation in the HBA2 termination codon would result in elongated a-globin chains. This condition might lead to unstable RBC formation due to the weak binding of globin chains. Among the Hb Constant Spring patients, abnormal MCV has been reported . Similarly, a study reported a decrease in levels of MCV, MCH and MCHC among heterozygous Hb Constant Spring patients . In contrast, another study showed normal MCV, MCH and Hb A2 among the same patients . Previous studies have reported a wide range in various parameters; however, in the current study, Hb quantification showed normal Hb A, Hb A2 and Hb F levels in all subjects. The Hb, MCV, MCH and MCHC of Hb Constant Spring patients showed a slight decrease, but it was not significant compared with other mutations. It was challenging to characterise the mutation solely depending on haematological parameters. In heterozygous patients, this variant made up 1 to 2% of total Hb. HPLC and CE could both detect this variant. However, individuals with a small amount of this Hb were often not detectable in HPLC, but this limitation could be resolved by using CE . In HPLC and CE analyses, Hb Constant Spring would produce a peak in window C and zone 2, as shown in Figure 3. Patients with Hb Quong Sze showed normal haematological parameters except for MCV and MCH, which were slightly lower compared with the normal range. Similar findings were also published; however, most of the studied population had mild to moderate anaemia . Hb Quong Sze is undetectable in routine electrophoresis and, thus, requires molecular analysis for confirmation . The point mutation in codon 59 in either HBA1 or HBA2 would lead to the production of an abnormal Hb known as Hb Adana. The MCV, MCH and MCHC levels in these patients were slightly lower, but they were not statistically different among the different mutation groups. A previous study reported that Hb Adana carriers had a normal to slight decrease in MCV levels or an increase in RBC levels . Similarly, another study found the carriers had normal haematological parameters with mild anaemia . On the other hand, this Hb variant is highly unstable, which cannot be detected in routine CE . Thus, it could be missed if the diagnosis depended only on haematological parameters . Therefore, multiplex ARMS-PCR and Sanger sequencing played an important role in ensuring an accurate diagnosis and the provision of genetic counselling. Hb H disease reflects the presence of three defective a-globin genes (--/-a), and it can occur due to deletion or mutation. The disease is the symptomatic form of a-thalassaemia. The most prevalent type of Hb H disease is the deletional type, which is brought on by compound heterozygosity caused by a double-globin gene deletion on one allele and a single globin gene deletion on the other allele. Nondeletional Hb H disease is rare, and it has a more severe clinical presentation. The disease is usually caused by homozygosity for nondeletional alleles or compound heterozygous for point mutations in either a2-globin chains, with heterozygosity for double-gene deletion on one chromosome . However, the clinical outcome and haematological parameters are widely variable, from very mild to severe phenotypes. The severity depends on the imbalanced production of b-globin chains, which is determined by the underlying a-globin gene mutations . There is a significant decrease in Hb, MCV, MCH and MCHC compared with cases with one or two defective a-globin genes . All haematological parameters of deletional compound heterozygous (--SEA/-a3.7) showed low haematological parameters. The RDW was high in a patient with aCSa/aAdanaa. The Hb Adana was a severe nondeletional mutation and commonly associated with Hb H-induced hydrops fetalis syndrome in compound heterozygous cases . The RDW level has been reported to be elevated in Hb H disease patients . The Hb H level was detected in zone 15 of the CE analysis, with a mean value of 8.9 +- 3.56. Comparatively, other compound heterozygous mutations in this study, including -a4.2/aCSa, --SEA/aCSa, --SEA/aQuong Szea, -a3.7/aAdanaa, and aCSa/aAdanaa, showed the presence of Hb Barts. A decrease in the production of a-globin chains due to the mutation on HBA1 and HBA2 leads to excess gamma (g) chain production, which joins together to form an unstable tetramer called Hb Barts . This causes the formation of Hb Barts, which is usually observed in patients with a-thalassaemia major. The involvement of nondeletional mutations in a-globin genes can cause severe and significant clinical outcomes that might require regular blood transfusion . The nondeletional mutations result in unstable Hb production, which leads to the formation of damaged RBCs. However, the most unstable Hb is produced when nondeletional mutations interact with deletional ones . The haematological parameters were lower in all patients with Hb H disease in this study. Hb, MCV, MCH, Hct and Hb F were found to be lower in patients with deletional compound heterozygous (--SEA/-a3.7) compared with other mutations. A contradictory finding was reported, in which cases of compound nondeletional mutations showed lower values for most of the haematological parameters . Therefore, molecular analysis is necessary to understand the pathology and, more importantly, provide correct genetic counselling and prenatal diagnosis in high-risk families. Despite the results obtained in this study, this research has several limitations, such as investigation into the lack of iron to rule out coinheritance IDA, and the selection of patients based on haematological parameters, resulting in the inability to identify a-thalassaemia in asymptomatic patients. 5. Conclusions This study found a 48.9% prevalence of a-thalassaemia in the patient cohort. The Hb, MCV, MCH, MCHC, RBC, RDW, Hct, Hb A, Hb A2 and Hb F levels in patients, including those with the same genotypes, revealed variations that might be due to environmental and genetic modifiers. Thus, haematological parameters alone would not be specific enough to describe each a-thalassaemia mutation. A combination of molecular techniques, including multiplex gap-PCR, multiplex ARMS-PCR, MLPA and Sanger sequencing, would be helpful for the accurate and precise detection of a-globin chain mutations. Acknowledgments We highly appreciate the efforts and cooperation given by all the staff from the Haematology Department of the Hospital Universiti Sains Malaysia and the Institute for Medical Research. Supplementary Materials The following supporting information can be downloaded at: Table S1: List of primers and concentrations used in multiplex gap-PCR, Table S2: List of primers and concentrations used in multiplex ARMS-PCR. Click here for additional data file. Author Contributions Conceptualisation D.V. and W.S.W.A.R.; methodology, D.V., W.S.W.A.R., K.T.P., Z.Z., N.Y., S.H. and E.E.; validation W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; formal analysis, D.V.; investigation; D.V. and W.S.W.A.R.; resources, D.V., W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; data curation, D.V., W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; writing--original draft preparation, D.V., W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; writing--review and editing D.V., W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; visualisation, D.V., W.S.W.A.R., K.T.P., Z.Z., N.Y., S.H. and E.E.; supervision, W.S.W.A.R., K.T.P., Z.Z., R.B., N.Y., S.H. and E.E.; project administration, D.V., W.S.W.A.R., K.T.P. and Z.Z.; funding acquisition, W.S.W.A.R. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki. This study was approved by the Medical Research and Ethics Committee (NMMR-21-606-58737) and Human Research Ethics Committee, Universiti Sains Malaysia (USM/JEPeM/20020104). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Representative gel image for a deletional mutations: Lane M: 100 bp plus ladder; Lane 1: heterozygous 4.2 mutation (-a4.2/aa); Lane 2: heterozygous 20.5 mutation (-a20.5/aa); Lane 3: heterozygous SEA mutation (--SEA/aa); Lane 4: heterozygous 4.2 mutation (-a4.2/aa); Lane 5: heterozygous Fil mutation (--FIL/aa); Lane 6: heterozygous 3.7 mutation (-a3.7/aa); Lane 7: compound heterozygous (--SEA/-a3.7); Lane 8: negative control; Lane 9: heterozygous 4.2 mutation (-a4.2/aa). Figure 2 Representative gel image for a nondeletional mutations: Lane M: 100 bp ladder; Lane 1: initiation codon mutation; Lane 2: codon 30 mutation; Lane 3: codon 59 mutation (Hb Adana); Lane 4: codon 142 mutation (Hb Constant Spring); Lane 5-6: normal a; Lane 7: codon 142 mutation (Hb Constant Spring); Lane 8: negative control. Figure 3 (a,b) A representative result of Hb Constant Spring by HPLC and CE analyses. The red arrow represents the Hb Constant Spring peak and zone in HPLC and CE respectively. diagnostics-13-00894-t001_Table 1 Table 1 Types of a-globin genotypes identified. Type of a-Globin Genotype Frequency Percentage (%) Deletional -a3.7/aa 21 15.4 -a4.2/aa 5 3.7 --SEA/aa 10 7.4 -a3.7/-a3.7 1 0.7 37 57.8 Nondeletional aCSa/aa 14 10.3 aAdanaa/aa 1 0.7 aQuong Szea/aa 2 1.5 aCSa/aCSa 1 0.7 18 28.1 Compound heterozygous -a4.2/aCSa 1 0.7 --SEA/aCSa 2 1.5 --SEA/aQuong Szea 1 0.7 -a3.7/aAdanaa 1 0.7 --SEA/-a3.7 3 2.2 aCSa/aAdanaa 1 0.7 9 14.1 diagnostics-13-00894-t002_Table 2 Table 2 Haematological parameters among deletional mutations of a-thalassaemia patient. Parameters (Median, Interquartile Range) aa/aa n = 67 -a3.7/aa n = 21 -a3.7/-a3.7 n = 1 -a4.2/aa n = 5 --SEA/aa n = 10 p-Value Hb (g/dL) 11.4 (8.8-12.7) 12.0 (10.0-13.7) 8.1 13.6 (13.1-16.85) 11.55 (10.78-12.53) 0.022 * MCV (fL) 71.1 (65.4-74.8) 76.8 (68.85-81.75) 77.1 70.9 (70.85-79.65) 66.35 (62.68-70.68) 0.009 * MCH (pg) 22.7 (19.1-24.5) 25.5 (20.75-26.50) 22.9 24.1 (23.3-26.55) 20.5 (19.78-22.3) 0.017 * MCHC (g/dL) 31.7 (29.6-32.9) 31.70 (30.90-33.10) 29.8 34.0 (31.8-34.45) 31.4 (31.25-31.85) 0.173 ns RBC (1012/L) 4.97 (4.43-5.48) 4.92 (4.59-5.45) 3.53 5.5 (4.72-6.45) 5.83 (5.25-6.22) 0.038 * RDW (fL) 39.9 (35.4-44.7) 40.8 (37.3-43.1) 44.9 40.0 (39.8-50.85) 34.8 (33.1-38.75) 0.060 ns Hct (%) 35.6 (30.6-39.8) 36.3 (33.15-42.4) 27.2 40.0 (39.8-50.85) 37.15 (33.85-40.03) 0.058 * Hb A (%) 96.4 (72.3-97.1) 96.8 (96.1-96.95) 96.1 96.4 (95.45-96.55) 96.6 (96.0-97.13) 0.747 ns Hb A2 (%) 2.9 (2.6-26.4) 2.8 (2.65-3.1) 3.2 3.2 (2.95-3.2) 2.45 (2.35-2.75) 0.048 ns Hb F (%) 0.6 (0.3-0.9) 0.4 (0.3-0.75) 0.7 0.4 (0.4-1.45) 0.6 (0.38-1.25) 0.388 ns Note: ns indicates nonsignificant p-value. * Indicates p < 0.05 and statistically significant. Kruskal-Wallis test was performed. diagnostics-13-00894-t003_Table 3 Table 3 Haematological parameters among nondeletional mutations of a-thalassaemia patients. Parameters (Median, Interquartile Range) aa/aa n = 64 aCSa/aa n = 14 aCSa/aCSa n = 1 aAdanaa/aa n = 1 aQuong Szea/aa n = 2 Hb (g/dL) 11.3 (8.73-12.68) 12.4 (11.55-13.55) 10 15.3 13.65 (12.5-14.8) MCV (fL) 71.25 (65.1-74.95) 79.55 (70.48-80.55) 70.9 79.8 70.3 (64.7-75.9) MCH (pg) 22.7 (19.1-24.48) 25.15 (23.35-26.0) 21.1 23.8 24.95 (22.9-27.0) MCHC (g/dL) 31.75 (29.68-32.9) 25.15 (23.35-26.0) 29.8 29.8 35.5 (35.4-35.6) RBC (1012/L) 4.96 (4.44-5.46) 5.14 (4.78-5.50) 4.74 6.44 9.2 (5.46-12.94) RDW (fL) 39.8 (35.5-44.6) 37.84 (35.95-40.43) 40.7 45.2 38.8 (36.6-41.0) Hct (%) 35.6 (30.3-39.68) 38.25 (36.1-42.93) 33.6 51.4 38.15 (35.3-41.0) Hb A (%) 96.4 (72.33-97.08) 96.7 (96.3-96.93) 94.4 96.6 96.55 (96.3-96.8) HbA2 (%) 2.9 (2.45-26.25) 2.7 (2.48-2.9) 2.1 3 2.7 (2.6-2.8) Hb F (%) 0.6 (0.3-0.9) 0.55 (0.48-0.9) 2.1 0.4 0.75 (0.4-1.1) diagnostics-13-00894-t004_Table 4 Table 4 Haematological parameters between compound heterozygous a-thalassaemia patients. Genotype --SEA/-a3.7 n = 3 --SEA/aQuong Szea n = 1 --SEA/aCSa n = 2 -a4.2/aCSa n = 1 -a3.7/aAdanaa n = 1 aCSa/aAdanaa n = 1 Parameters/ Phenotype Deletional Hb H Nondeletional Hb H Hb H phenotype Hb (g/dL) 8.2 (6.5-10.3) 6.7 5.8-9.5 10.9 9.2 7.0 MCV (fL) 60.6 (57.6-67.7) 71.1 75.4-78.7 64 65.9 90.1 MCH (pg) 18.5 (16.9-21) 18.5 20.1-24.1 19.7 21.3 24.7 MCHC (g/dL) 30.5 (29.3-31) 26.5 26.6-30.6 30.8 32.4 27.5 RBC (1012/L) 4.44 (3.1-6.11) 3.56 2.89-3.94 5.53 4.31 2.83 RDW (fL) 44.1 (40.9-45.2) 59 40.1-57.1 33.2 36.4 82.0 HCT (%) 26.9 (21-35.2) 25.3 21.8-31 35.4 28.4 25.5 Hb A (%) 98.1 (98-98.4) 52.7 81.7-85 96.9 96.7 80.0 Hb A2 (%) 1.5 (1.4-1.8) 1.1 0.7-2.9 2.4 2.5 2.5 Hb F (%) 0.2 (0.2-0.4) 14.5 0.5-1 1.1 0.8 3.6 Hb H (%) 9.4 (5.1-12.2) 6.4 2.4-12.2 - - - Hb Barts - 29.2% 0.9-1.85 - - 0.8 The parameters for --SEA/-a3.7 are shown as median and interquartile range. 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PMC10000534 | Introduction: Osteosarcoma treatment has benefitted greatly from collaborative research. This paper describes the history and accomplishments of the Cooperative Osteosarcoma Study Group (COSS), mainly dedicated to clinical questions, as well as remaining challenges. Materials and Methods: Narrative review of over four decades of uninterrupted collaboration within the multi-national German-Austrian-Swiss COSS group. Results: Since its very first prospective osteosarcoma trial starting in 1977, COSS has continuously been able to provide high-level evidence on various treatment-related questions. This includes both the cohort of patients enrolled into prospective trials as well as those patients excluded from them for various reasons, followed in a prospective registry. Well over one hundred disease-related publications attest to the group's impact on the field. Despite these accomplishments, challenging problems remain. Discussion: Collaborative research within a multi-national study group resulted in better definitions of important aspects of the most common bone tumor, osteosarcoma, and its treatments. Important challenges continue to persist. osteosarcoma collaborative trial registry child adolescent adult This research received no external funding. pmc1. Origins and Early COSS History "If we operate they die, if we don't operate they die. This meeting should be concluded with prayers." (Sir Stanford Cade, 1955) Osteosarcoma arises in approximately 2-3/Mio. individuals per year. Adolescent males are most frequently affected, but it may affect all ages and both genders. It was an almost universally fatal disease until a therapeutic revolution manifested itself some fifty years ago. Surgery, overwhelmingly often in the form of an amputation, had been performed for this disease for decades. It was mostly not curative: patients soon thereafter succumbed to metastases to the lungs. In the early 1970s, systemic therapies active against micro-metastases were finally discovered . A breakthrough towards a cure was achieved when active agents were combined and employed in an adjuvant and, very soon thereafter, a neoadjuvant setting . The formerly untreatable disease had suddenly become curable. The news was soon heard in Germany , Austria , and Switzerland. Inspired by the first optimistic reports in a previously unequivocally fatal malignancy, the Cooperative Osteosarcoma Study Group, COSS, was founded. As any single center would encounter far too few individual patients to come up with any meaningful findings, visionary clinicians and scientists joined efforts far beyond national borders. Together, they performed the first of many joint, multi-center, multi-national osteosarcoma trials . Thus, the first multi-national group dedicated to this disease emerged. This laid the foundation for more than 45 years of collaboration against osteosarcoma and related malignancies. 2. Structure of the COSS Group 2.1. Multi-Disciplinarity COSS has always been a decidedly multi-disciplinary group. This was due to the obvious fact that it took more than only one specialty to treat osteosarcoma. By themselves, no single discipline could conquer the disease. Together, they stood a realistic chance. The group therefore invited all specialties required for affected patients. In addition to both pediatric and medical oncologists, this includes radiologists and nuclear medicine specialists, responsible for primary and metastatic tumor imaging and staging; pathologists, offering reference histology in each and every case; and tumor surgeons, responsible for diagnostic biopsies and tumor removal with, if at all feasible, wide margins. In special tumor locations--for instance, the head and neck--site-specific specialists assist orthopedic surgeons. Thoracic surgeons assess the possibilities of removing pulmonary metastases. Radiation oncologists, including proton and heavy-ion specialists, explore treatment options for unresectable primary and metastatic lesions. Other experts are in charge of questions surrounding, for instance, molecular tumor biology, late effects of therapy, quality of life, or statistics. 2.2. Multi-Centricity COSS was designed as a disease-related, inclusive network. Not merely pure science, but also the best achievable care for as many patients as possible, has been and still is a major impetus. Over the decades, more than 200 individual institutions have registered between one and several hundred patients with the group. This allowed compensation for limited local expertise--expected in such a rare disease--by that of the group as a whole. This was accomplished by an ever more elaborate consultation system (see below). A downside of this is that some institutions merely seek expertise, without wishing to contribute to knowledge generation. COSS has thus fought a never-ending battle to propagate the virtues of collaborative knowledge generation. 2.3. Multi-Nationality COSS, run under the auspices of the German Society for Pediatric Oncology and Hematology (GPOH), has traditionally been open for all institutions from Germany, Austria, and Switzerland. Some sites from the Czech Republic and Hungary have also contributed patients to the international EURAMOS trial . 2.4. Patient Recruitment The group has always followed an inclusive registration strategy. Any patient with an osteosarcoma and some closely related tumors was eligible for registration into a disease-oriented registry. Although the clear majority of registered individuals stem from pediatric institutions, age has never been an exclusion factor. With the years and decades, the COSS registry has grown into the largest disease-related database worldwide . Trials have at all times been limited to specific subpopulations who fulfilled relevant inclusion and exclusion criteria. Thus, important research questions were answered. However, prospective trials are bound to loose patient (sub-)groups. Information that could be learned from such would be lost. COSS has therefore implemented its patient registry with much less stringent entry criteria, run in parallel to any prospective trial from day one . 2.5. Long-Term Follow-Up and Cancer Survivorship Risk-stratified long-term care, involving both tertiary care centers and the multi-disciplinary teams and general practitioners with whom they interact, is the group's aim. Such was reported as the preferred model of care after cancer . Cooperation is, however, challenged by the constant needs for communication, instruction, and training as well as continuous data sharing . The recommendations for practical use presented here might serve as a tool to improve collaboration between multi-disciplinary teams and general practitioners. Such was highlighted in a recent Australian study, where highly prescriptive care plans from the oncologist/long-term follow-up clinic were the preferred mode of communication. However, such were often not provided . 3. Aims of the COSS Group From the very beginning, the group has had two major aims: science and, no less important, providing every patient with the best available care. Prospective clinical trials are the benchmark of clinical science. These have hence been a major focus. Additional information about osteosarcoma and related tumors was generated from the group's clinical registry with far less stringent inclusion criteria. Up-to-date clinical care to each registered patient is COSS' second core aim. Clinical pathways were therefore implemented and a multi-disciplinary consultation service was put into place. Named specialists may be called upon to address individual questions that treating physicians may have. An interdisciplinary, real-life tumor board takes place once every week. The possibility to attend virtually is offered to the treating institutions. 4. Prospective COSS Trials 4.1. Groupwise Trials The first of several published COSS trials, COSS-77, was a relatively small trial of adjuvant osteosarcoma chemotherapy. This trial proved both that chemotherapy worked in the disease and, notably, that multi-centric collaboration was possible in a rare cancer . Neoadjuvant treatment was first introduced in the following trial, COSS-80. It could not demonstrate the superiority of one chemotherapy combination over another or a role for fibroblast interferon . The follow-up trial, COSS-82, was a disappointment as far as outcomes were concerned, but a great success for the following generations of osteosarcoma patients. It was attempted to spare patients from treatment's late effects. Particularly toxic substances were administered only post-operatively and only against tumors not responding to a less intensive regimen. As expected, the percentage of patients whose tumors responded to de-escalated therapy was lower than in the control arm, where individuals received intensive chemotherapy upfront. However, patients whose tumors did not respond to the less intensive regimen remained to have a very poor prognosis despite post-operative therapeutic intensifications. Consequently, all osteosarcoma patients now receive intensive therapy from day one . Intra-arterial therapy was associated with great hope when it first made its entrance into osteosarcoma treatment. Cisplatin was proposed to be administered by this technique. COSS addressed its intra-arterial versus intravenous administration in a prospective, randomized trial, COSS-86. Early laboratory results by spectroscopy suggested caution: similar blood and intratumoral cisplatin concentrations were obtainable by either technique . Clinical results later proved that neither the response rate nor the survival rate were improved with the intra-arterial technique . Because of this and other trials , it was largely abandoned. The COSS-96 trial then attempted to introduce risk-based therapy but failed to be successful. A manuscript on its long-term results is in preparation. 4.2. Intergroup Trials Acknowledging that even the largest individual efforts would need many years to answer randomized questions, several of the world's leading osteosarcoma groups joined efforts in the largest prospective osteosarcoma study ever, EURAMOS-1 . In addition to COSS, these were the Children's Oncology Group (COG), the European Osteosarcoma Intergroup (EOI), and the Scandinavian Sarcoma Group (SSG). Together, they recruited well over 2200 patients . Intergroup collaboration was not without its unique challenges. Each partner had to adapt. Nevertheless, all participants ultimately benefitted. In slightly over five years, two separate research questions were addressed. Firstly, postoperative therapeutic adaptations could not improve the poor prognosis of patients with a poor histological tumor response to upfront chemotherapy . In the same trial, maintenance therapy with interferon-a was of no benefit for the remaining good responders . Both conclusions remained valid with extended follow-up . In addition to mere survival data, it was also possible to investigate the quality of life of the participating individuals . Unfortunately, novel innovative research questions were lacking after EURAMOS-1 had closed, so that no follow-up trials materialized. Osteosarcomas in older adults have always been largely uncharted territory. Prospective osteosarcoma trials have generally had an upper age limit of, at the most, 40 years. COSS, the Italian Sarcoma Group (ISG), and SSG addressed this deficit by jointly performing the only prospective trial ever in this cohort of patients. After addressing several challenging regulatory hurdles, the resulting European Over 40 Bone Sarcoma (EURO-B.O.S.S.) trial managed to include 218 adult osteosarcoma patients. The proposed treatment regimen differed from that in younger patients: primary surgery, while not advocated, was allowed. Drug doses were reduced and high-dose methotrexate was limited to patients with a non-response to doxorubicin, cisplatin, and ifosfamide. The study's results proved that this prescribed therapy, while associated with substantial toxicity, was generally feasible. The resulting five-year overall survival rates of 66% for patients with seemingly localized disease and 22% for patients with primary metastases may be seen as new benchmarks for the age group . 5. COSS Registry 5.1. Rationale Owing to more or less strict study entry and exclusion criteria, many patients would be lost to science if they were limited to prospective trials. The knowledge that could be gained from such patients and their unique disease situations is, however, substantial. This problem is addressed by the COSS registry with its very liberal inclusion and almost no exclusion criteria. 5.2. Recruitment The COSS registry includes all patients from participating institutions, be they eligible for trials or not, with a diagnosis of osteosarcoma, whatever its grade might be. Some biologically related tumors, such as undifferentiated pleomorphic sarcomas or dedifferentiated or mesenchymal chondrosarcomas, may also be entered. Therapy according to published guidelines and guidance is suggested. However, the choice of specific therapeutic measures does not represent a prerequisite for recruitment. 5.3. Published Groupwise Analyses By including all osteosarcoma patients and some others into its registry, COSS has been able to assess a wide variety of questions. Those based on the collectively gathered data are summarized here. A summary of all osteosarcoma results has been published . For detailed analyses, this first and foremost included a report of all newly diagnosed osteosarcomas. This paper on prognostic factors of 1702 multi-modally treated patients with high-grade osteosarcomas set benchmarks. The tumor site and size, the presence or absence of primary disease spread, the tumor response to pre-operative chemotherapy, and, foremost, the surgical clearance of all diseased sites were proven as independent prognostic factors. According to pubmed.com (accessed on 22 February 2023), this has become the most referenced clinical osteosarcoma paper of all time . Using the large COSS database, various specific tumor presentations and therapeutic details could be analyzed. For instance, tumor size was found to correlate closely with outcomes . As for therapy, methotrexate (when given at a fixed dose of 12 g/m2) dose intensity was proven not prognostic in modern polychemotherapy protocols . The dose intensity of received chemotherapy was the focus of another analysis. It was not found to correlate with treatment outcomes, neither were the received dose intensities of individual agents prognostic . Great hopes were once associated with high-dose chemotherapy with blood stem cell rescue. A review of COSS patients treated in this way, usually for advanced disease situations, showed these to remain uncured even after this procedure, which was subsequently largely abandoned . A very large cohort of 2847 COSS patients with high-grade central extremity osteosarcomas was recently screened for the presence of pathological fractures. They were present in 11.3% of patients. Pathological fractures correlated with the tumor site, histologic subtype, relative tumor size, and primary metastatic status. They were prognostic in adults but not in pediatric patients . Primary metastases affect around 15% of osteosarcoma patients. They were another early research focus of the cooperative group . A benchmark analysis of affected individuals clearly demonstrated that their number and the ability to achieve complete surgical remission were strong prognostic factors. In addition, the factors established as prognostic in localized disease held their value in the primary metastatic setting . Skip metastases were not as negatively prognostic as previously assumed. This was true if the lesion affected the same bone as the primary tumor. Prognosis was inferior with trans-articular skip lesions . The structure of data collection allowed the investigation of several of the more uncommon tumor sites, elucidating the roles of local and systemic therapies. Osteosarcomas of the hands and feet carried many of the same prognostic factors as did the more common long-bone primaries. Osteosarcomas affecting various locations in the axial skeleton shared many of those characteristics, with some distinct differences. Arising in somewhat older patients, they responded far less favorably to chemotherapy. Most importantly, however, surgical remission was found to be much more difficult to achieve. This resulted in a far inferior prognosis . Again demonstrating the benefits of registering all osteosarcoma patients, COSS was also able to take a detailed look at craniofacial osteosarcomas. The role of chemotherapy at this site is often considered far less pivotal than with tumors elsewhere. COSS detected clues to its efficacy, without convincingly providing a definitive answer . Osteosarcoma arising as a second or later malignancy was long thought to carry an almost uniformly fatal prognosis. A COSS analysis of 30 affected patients could, for the first time, prove this wrong. The predilection of secondary tumors for the axial skeleton, a consequence of former irradiation, remained challenging . Even osteosarcoma arising after bone marrow transplantation, again often secondary to former radiotherapy, proved to be treatable . The combination of osteosarcoma and a phyllodes tumor of the breast was observed most often in female patients affected by Li-Fraumeni syndrome . Moreover, several cases of osteosarcoma in patients affected by Rothmund-Thomsen syndrome could be analyzed. In particular, affected individuals were evaluable for their chemotherapy tolerance . The discussion about which type of therapy is to be employed, an osteosarcoma regimen or rather a soft-tissue sarcoma regimen, surrounds extraosseous osteosarcoma. A review of the COSS experience demonstrated favorable results with osteosarcoma-based regimens. It must, however, be noted that the COSS patients analyzed were far younger than the average extraosseous osteosarcoma patient . Osteosarcoma most often affects children or adolescents. The typical preponderance of males was not evident in the youngest patients below the age of five years at diagnosis. Otherwise, they generally seemed to behave as expected . Misdiagnosis and then mistreatment of osteosarcoma as some other, often benign tumor is one of the most dreaded mishaps of oncologists. Hesitancy often precludes the reporting of such diagnostic failures. COSS recently reported on such patients and could prove that uncommon sites of tumor presentation were at a particular risk for misinterpretation. Systemic spread occurring during the lag time between incorrect and correct diagnoses was observed. Some affected patients were still cured once appropriate therapy was finally initiated . COSS' unlimited follow-up allowed a detailed look at those unfortunate patients who developed disease recurrences. As assumed, these were most often pulmonary, followed by the distant bones and local failures. The timing and number of metastases correlated with outcomes. Achieving a (second) complete surgical remission was essentially found to be a prerequisite for a cure. The use of second-line chemotherapy seemed prognostically favorable, but its influence was limited . Even second and subsequent recurrences could be investigated with large patient numbers. The ability to achieve renewed surgical remissions once again emerged as pivotal. Some patients became long-term survivors despite multiple recurrences. Renewed chemotherapy may again have contributed, but within very narrow limitations . Regarding special metastatic sites, an analysis of distant osseous recurrences demonstrated these to be treatable if solitary . Focusing on the local site as the region of recurrence, 76 out of 1355 analyzed patients with extremity or axial osteosarcomas developed this complication. Not participating in a clinical trial, pelvic primaries, limb-sparing surgery, soft-tissue infiltration beyond the periosteum, a poor response to neo-adjuvant chemotherapy, a failure to complete the planned chemotherapy protocol, and a biopsy at a center other than the one performing the definitive procedure were significant predictors of an increased local recurrence risk. No differences were obvious for varying surgical margin widths. Surgical treatment at centers with a small patient volume and more than one surgical procedure of the primary tumor area were significantly associated with a higher rate of ablative surgery . As for long-term outcomes after a rotationplasty, these were the results of a recent patient survey. It proved this procedure to be a realistic therapeutic option for eligible patients, with few revision procedures needed even long-term . In addition to classical osteosarcoma, the group has always followed some other tumors considered biologically related. Undifferentiated pleomorphic sarcoma (UPS, formerly malignant fibrous histiocytoma, MFH) of bone, the focus of a European joint analysis, responded to many of the same treatment principles as osteosarcoma itself. While the histologic response rate to chemotherapy was worse, the overall outcome was nevertheless quite similar . The COSS registry's inclusion of tumors biologically similar to osteosarcoma allowed the group to contribute to the dedifferentiated chondrosarcoma cohort of the EURO-B.O.S.S. study. It could thus be demonstrated how patients (aged 40-65 years) suffering from such a malignancy fared when treated according to an up-to-date, multi-disciplinary approach, setting a new benchmark for the disease . The group's efforts never ended with successful antineoplastic treatment. As early as 1983, its toxicities also came into focus . A major step forward was the foundation of the Late Effects Surveillance System (LESS), GPOH's collaborative late effects study group, to which COSS contributes relevant data regularly . Analyses including former osteosarcoma patients have focused on doxorubicin's cardiotoxicity , the platinum analogues ototoxicitis , cisplatinum, and ifosfamide's nephrotoxicity , the thyroid's function after therapy , and the long-term immunity of these heavily treated patients . Lately, efforts to better define a treatment's late effects have been extended into a European collaboration within the PANCARE consortium. As a first step, it was thus possible to amass sufficient patients for analyses of cisplatin's ototoxicity . 6. Adolescent and Young Adult Oncology Osteosarcomas are among the most frequent malignancies affecting adolescents and young adults (AYA). Anyone with even a remote interest in osteosarcomas will therefore necessarily need to address the specific challenges associated with this transitional period between childhood and adult life. Historically, AYA have been lost between pediatric and medical oncology, with very limited interaction between these. Often, this resulted in completely different approaches to the same diseases. Consequently, individuals from the COSS group have had roles in the foundation and leadership of both national and European AYA working groups, bridging the relevant national and continental pediatric and medical oncology societies. These collaborations have led to several pivotal publications in the field of osteosarcoma in AYAs and AYA oncology in general . 7. Intergroup Collaboration Using Anonymized Data Anonymized patient baseline, treatment, and outcome data from COSS were entered into a variety of retrospective collaborative intergroup analyses, allowing for adequate patient numbers. It was thus possible to gather a very large cohort of patients for potential prognostic differences between children, adolescents, and young adults with osteosarcoma and to demonstrate that the youngest patients had a more favorable prognosis . This form of collaboration also helped to describe the successes and knowledge gaps in older adults with osteosarcoma . Periosteal osteosarcomas were shown to require meticulous local therapy. A role for systemic chemotherapy could not be documented . A detailed analysis of 266 extraosseous osteosarcomas defined both similarities and prognostic and therapeutic distinctions from their osseous counterparts . Those patients who developed very late osteosarcoma recurrence were the focus of one , and the toxicity of high-dose methotrexate, a pivotal drug in the disease, of another large collaborative analysis . European collaboration also helped to better define the principles of local and systemic therapy in mesenchymal chondrosarcoma . The prevalence and outcomes of secondary malignancies after a diagnosis of a sarcoma of any type and their relation to predisposing factors were the topics of a collaboration between GPOH's bone and soft tissue sarcoma groups . Rare bone tumors other than osteosarcoma could be analyzed in part thanks to COSS's contribution to Germany's network of rare pediatric tumors . 8. Bringing European Researchers Together Osteosarcoma treatment has seen little prognostic improvement over the past few decades. Trying to end this stalemate, COSS has had its role in bringing Europe's clinical and laboratory osteosarcoma researchers together to discuss their current projects and future plans . Individuals charged with leading roles within the COSS group have had rules in drafting both national and European osteosarcoma guidelines. The group was also influential in drafting essential requirements for the quality care of affected patients on a European level . 9. Past, Current, and Future Challenges to Collaboration 9.1. Maintenance of Multi-Disciplinary Collaboration Relevant publications with COSS contribution are summarized in Table 1. The successful running of such a large multi-disciplinary, multi-institutional study group is no one-time effort, but poses its own, perpetual challenges. Potential study group members must understand the benefits of being part of the endeavor and accept the obligations coming with their participation. For them, the benefits must clearly outweigh the costs. It remains a constant struggle to convince physicians that COSS and especially its consultation service are no easy way to substitute for inadequacies, but that this requires input on their part. However, this seems by now to be widely understood throughout the participating countries, with notable exceptions. 9.2. Ever Increasing Regulatory Demands The early years of COSS cooperation had lax ethical requirements and fledgling regulatory demands. This has definitely changed. Any patient-related project is now the subject of very strict ethical guidelines, designed to protect patients from harm through unjustified or ill-considered interventions. As Germany is part of the European Union and the COSS study center is located in Germany, one of its member states, it also bears the full brunt of the EU Good Clinical Practice directive 2001/20. Mainly designed to protect patients, it also brought with it an unparalleled bureaucratic workload and serious financial consequences. The directive's negative consequences on investigator-initiated research are unquestionable: designed with the well-meaning intention to protect participants in clinical trials, it may rather prevent trials from ever opening. Recent legislative changes designed to ease this situation promise long-awaited relief, but this only time will tell. 9.3. Financial Sustainability The financial sustainability of trial groups such as COSS is a constant challenge. Its trials and registries have been funded by Deutsche Krebshilfe (DKH), Deutsche Forschungsgesellschaft (DFG), the European Science Foundation (ESF), charities, and others. A major step forward was Germany's public insurance companies recently agreeing to reimburse GPOH's study centers for their remote patient consultations. It remains open if the recent ERN PaedCan initiative to reimburse for consultations from other EU member states will be met with success. Its online reference system may provide quick answers, but also places considerable obligations on those asking for advice. 10. Current and Future COSS Projects COSS has had its part in recent international efforts to define the current treatment principles, and the solved and the open questions in osteosarcoma . However, the group has had no open trial for its main patient cohort, young patients with osteosarcoma, for over 10 years. A paucity of new, efficacious agents and ever-increasing regulatory demands have led to a certain standstill. The COSS registry, however, is ongoing. An updated version recently received ethical approval. It now includes biological questions and a centralized tumor bank. As one possible way forward, COSS has entered into several large-scale, international collaborations. One of these, FOSTER (Fight Osteosarcoma Through European Research), is a Pan-European effort to gather experts from all European countries. Organized in work packages, FOSTER seeks to answer relevant tumor-biological and clinical questions. Ultimately, it may even develop multi-institutional, international trials. On a global scale, multiple groups interact in the Harmonization International Bone Sarcoma Consortium (HIBISCus), led by the University of Chicago. This seeks to collect existing data into a harmonized database for later analysis . COSS' ultimate goal, however, is to once again perform prospective, randomized osteosarcoma trials. 11. Conclusions The Cooperative Osteosarcoma Study Group, COSS, has been witness to unprecedented progress in the fight against a rare cancer, as well as to highly frustrating prognostic stagnation. It has been able to contribute pivotal data to the field and novel answers to specific questions. Further advances will now probably or even definitely require completely novel approaches, without ever forgetting what made osteosarcoma therapy successful in the first place. The group will address these challenges under new leadership and with renewed vigor. Its ultimate goal remains unaltered: one day, no patient will have to die from osteosarcoma. Author Contributions S.S.B. conceptualization, data curation, formal analysis, investigation, methodology, validation, writing; L.K. investigation, writing; T.K. investigation, writing; T.L. investigation, writing; P.R. investigation, writing; C.B. funding acquisition, resources, supervision, investigation, writing; M.K. formal analysis, writing; V.M. formal analysis, writing; B.S. formal analysis, writing; S.H.-N. data curation, investigation, writing. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki. Use of patient-data was approved by Ethik-Kommission der Arztekammer Westfalen-Lippe und der Medizinischen Fakultat der WWU Munster, 5 V Bielack, 30.06.05 and Ethik-Komission der Landesarztekammer Baden-Wurttemberg, protocol code F-2021-007, 1 April 22). Informed Consent Statement Informed consent was obtained from all subjects involved in the study or from their legal guardians. Data Availability Statement The data presented in this study are available on request from the corresponding author. The data are not publicly available due to lack of ethical approval. Conflicts of Interest Stefan S. Bielack reports consultancy/advisory boards for Hoffmann-La Roche, Boehringer-Ingelheim, EISAI, Y-mAbs, and MAP Biopharma, all outside the scope of the submitted work. Peter Reichardt reports consulting fees from Bayer, Novartis, Roche, Deciphera, Mundibiopharma, PharmaMar, Blueprint Medicines, GSK, and Boehringer Ingelheim, all outside the scope of the submitted work, and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Clinigen, Deciphera, PharmaMar, and Boehringer Ingelheim, all outside the scope of the submitted work. He is Chairman of the German Sarcoma Foundation. Stefanie Hecker-Nolting reports grants from Forderkreis krebskranke Kinder Stuttgart e.V., outside the scope of the submitted work. Claudia Blattmann, Leo Kager, Matthias Kevric, Thomas Kuhne, Thorsten Langer, Vanessa Mettmann, and Benjamin Sorg report no conflict of interest. Figure 1 Recruitment per year of 4657 previously untreated Cooperative Osteosarcoma Study Group osteosarcomas 1980-2001. Patients registered > 1 year after biopsy excluded. (a)--all 4657 patients. (b)--by primary tumor site: limb (n = 4071, solid line) vs. trunk (n = 404, dashed line) vs. head and neck (n = 177, dotted line); 5 primary sites unknown. (c)--by grade of malignancy: high-grade central (n = 4136, solid line) vs. others (n = 337, dashed line); head and neck osteosarcomas excluded; 8 grades not documented. Figure 2 Survival probability of previously untreated Cooperative Osteosarcoma Study Group patients with osteosarcomas 1980-2001. Patients registered >1 year after biopsy excluded. Median follow-up 5.04 (0.003--37.96) years from diagnostic biopsy. (a)--all 4657 patients. (b)--by primary tumor site: limb (n = 4071, solid line) vs. trunk (n= 404, dashed line) vs. head and neck (n = 177, dotted line); 5 primary sites unknown. Osteosarcomas of the trunk had an inferior survival probability to either those of the extremities or the head and neck (p < 0.001, log-rank test, respectively). (c)--by grade of malignancy: high-grade central (n = 4136, solid line) vs. others (n = 337, dashed line); head and neck osteosarcomas excluded; 8 grades not documented (p < 0.001, log-rank test). cancers-15-01520-t001_Table 1 Table 1 Publications on oncological topics by the COSS group or with COSS contribution. Results relate to osteosarcoma and to COSS patients as long as not explicitly stated otherwise. Publication Ref. Doi Topic Groupwise trials Winkler1982 10.1055/s-0028-1105579 COSS-77: first adjuvant trial results Winkler 1983 10.1007/BF00625042 COSS-80: preliminary trial results Winkler 1984 10.1200/JCO.1984.2.6.617 COSS-80: final trial results Purfurst 1985 10.1055/s-2008-1033974 COSS-77 and -80: updated trial results Winkler 1988 10.1200/JCO.1988.6.2.329 COSS-82: final trial results Bielack 1989 10.1055/s-2008-1026715 COSS-80 and COSS-82: updated trial results Winkler 1990 - COSS-86: preliminary trial results Winkler 1990 10.1002/1097-0142(19901015)66:8<1703::aid-cncr2820660809>3.0.co;2-v COSS-86: final trial results Bieling 1996 10.1055/s-2007-1025433 COSS-86: preliminary trial results Fuchs 1998 10.1023/a:1008391103132 COSS-86: updated trial results Bielack 2009 10.1007/978-1-4419-0284-9_15 COSS: pooled results Intergroup trials Marina 2009 10.1007/978-1-4419-0284-9_18 EURAMOS-1: design Whelan 2015 10.1093/annonc/mdu526 EURAMOS-1: pre-randomization results Bielack 2015 10.1200/JCO.2014.60.0734 EURAMOS-1: poor responder results Marina 2016 10.1016/S1470-2045(16)30214-5 EURAMOS-1: good responder results Ferrari 2018 10.5301/tj.5000696 EURO-B.O.S.S S.: osteosarcoma results (>40 years) Smeland 2019 10.1016/j.ejca.2018.11.027 EURAMOS-1: updated trial results Calaminus 2019 10.1016/j.ejca.2022.03.018 EURAMOS-1: quality of life methodology Hompland 2021 10.1016/j.ejca.2021.04.017 EURO-B.O.S.S: dedifferentiated chondrosarcomas in patients 41-65 Budde 2022 10.1016/j.ejca.2022.03.018 EURAMOS-1: quality of life results Patient-related variables and outcomes Grimer 2003 10.1016/s0959-8049(02)00478-1 EMSOS: osteosarcoma over the age of forty Bielack 2003 10.1038/sj.bmt.1703864 Osteosarcoma after bone marrow transplantation Kager 2010 10.1002/cncr.25287 Osteosarcoma in very young children Collins 2013 10.1200/JCO.2012.43.8598 Intergroup meta-analysis: younger vs. older patients with osteosarcoma Bielack 2015 10.1097/MPH.0000000000000197 Osteosarcoma and phyllodes tumor Zils 2015 10.1097/MPH.0b013e3182a2719c Osteosarcoma after bone marrow transplantation Zils 2015 10.3109/08880018.2014.987939 Osteosarcoma in Rothmund-Thomson syndrome Gotta 2022 10.1055/a-1681-1916 Questionnaire: long-term function and quality of life with a rotationplasty Tumor-related variables and outcomes Bieling 1996 10.1200/JCO.1996.14.3.848 Initial tumor size and prognosis Rehan 1993 10.1055/s-2007-1025228 Initial tumor size and prognosis Bielack 1995 10.1002/mpo.2950240103 Osteosarcoma of the trunk Bielack 1999 10.1200/JCO.1999.17.4.1164 Osteosarcoma as secondary malignancy Bielack 2002 10.1200/JCO.2002.20.3.776 Prognostic factors in osteosarcoma Ozaki 2002 - Osteosarcoma of the spine Ozaki 2003 10.1200/JCO.2003.01.142 Osteosarcoma of the pelvis Daecke 2005 10.1245/ASO.2005.06.002 Osteosarcoma of the hand and forearm Jasnau 2008 10.1016/j.oraloncology.2007.03.001 Craniofacial osteosarcoma Zils 2013 10.1093/annonc/mdt154 Osteosarcoma of the mobile spine Schuster 2018 10.1155/2018/1632978 High-grade osteosarcomas of the foot Kelley 2020 10.1200/JCO.19.00827 Pathological fracture and prognosis Hecker-Nolting 2022 10.1007/s00432-022-04156-1 Osteosarcoma pre-diagnosed as another tumor Primary and secondary metastatic disease Winkler 1989 10.1159/000216608 Primary metastatic osteosarcoma Kager 2003 10.1200/JCO.2003.08.132 Primary metastatic osteosarcoma Kempf-Bielack 2005 10.1200/JCO.2005.04.063 Osteosarcoma relapse after combined modality therapy Kager 2006 10.1200/JCO.2005.04.2978 Primary skip metastases Hauben 2006 10.1016/j.ejca.2005.09.032 Intergroup analysis: late osteosarcoma relapses Bielack 2009 10.1200/JCO.2008.16.2305 Second and subsequent osteosarcoma recurrences Franke 2011 10.1002/pbc.22864 Solitary skeletal osteosarcoma recurrences Andreou 2011 10.1093/annonc/mdq589 Local osteosarcoma recurrences Osteosarcoma variants and non-osteosarcomas Bielack 1999 10.3109/17453679908997824 EMSOS: undifferentiated pleomorphic sarcoma Grimer 2005 10.1016/j.ejca.2005.04.052 EMSOS: periosteal osteosarcoma Goldstein-Jackson 2005 10.1007/s00432-005-0687-7 Eextraskeletal osteosarcoma Brecht 2014 10.1002/pbc.24997 STEP: rare malignant pediatric tumors Frezza 2015 10.1016/j.ejca.2014.11.007 EMSOS: mesenchymal chondrosarcoma Longhi 2017 10.1016/j.ejca.2016.12.016 EMSOS: extraskeletal osteosarcoma Anti-tumor drugs Bielack 1989 10.1007/BF00257446 Tumor tissue cisplatin levels after i.a. vs. i.v. infusion Graf 1994 10.1200/JCO.1994.12.7.1443 Methotrexate pharmacokinetics and prognosis Sauerbrey 2003 10.1038/sj.bmt.1703023 High-dose chemotherapy in relapsed osteosarcoma Widemann 2004 10.1002/cncr.20255 Meta-analysis: high-dose methotrexate-induced nephrotoxicity Eselgrim 2006 10.1002/pbc.20608 Dose intensity of chemotherapy and outcomes Side effects of therapy Jurgens 1983 10.1007/BF00625045 Toxicity of osteosarcoma chemotherapy Langer 2004 10.1002/pbc.10325 LESS: overview of late toxicity in sarcoma patients Stohr 2005 10.1081/cnv-200055951 LESS: cisplatin-induced ototoxicity in osteosarcoma Paulides 2006 10.1002/pbc.20492 LESS: doxorubicin-induced cardiomyopathy in sarcoma Stohr 2007 10.1002/pbc.20812 LESS: nephrotoxicity of cisplatin and carboplatin in sarcoma Stohr 2007 10.1002/pbc.208 LESS: ifosfamide nephrotoxicity in sarcoma Paulides 2007 10.1111/j.1365-2265.2007.02813.x LESS: thyroid function in pediatric and young-adult sarcoma Paulides 2010 10.1055/s-0030-1249609 LESS: Immunity against tetanus and diphtheria after childhood sarcoma Paulides 2011 10.1016/j.vaccine.2010.12.084 LESS: antibodies against tetanus and diphtheria after childhood sarcoma Nitz 2013 10.3892/ol.2012.997 LESS: carboplatin-mediated ototoxicity in sarcoma Langer 2020 10.1016/j.dib.2020.106227 PanCareLIFE: association of pharmacogenetic markers and platinum ototoxicity Langer 2020 10.1016/j.ejca.2020.07.019 PanCareLIFE: genetic markers and platinum-induced ototoxicity Kube 2022 10.1002/cncr.34110 COSS, CESS, and CWS: secondary malignancies after sarcomas Guidelines/guidance/consensus papers Wilhelm 2014 10.1093/annonc/mdu153 ENCCA WP17-WP7: consensus on teenagers/young adults with bone sarcoma Andritsch 2017 10.1016/j.critrevonc.2016.12.002 ECCO: essential requirements for quality sarcoma care AWMF 2021 - Expert consensus: German osteosarcoma guidelines Strauss 2021 10.1016/j.annonc.2021.08.1995 ESMO-EURACAN-GENTURIS-ERN PaedCan: European sarcoma guidelines International reviews Isakoff 2015 10.1200/JCO.2014.59.4895 Osteosarcoma treatment and a collaborative pathway to success Beird 2022 10.1038/s41572-022-00409-y Osteosarcoma Abbreviations: ref. = reference, doi = digital object identifier, COSS = Cooperative Osteosarcoma Study Group, EURAMOS = European and American Osteosarcoma Study Group, EURO-B.O.S.S S. = EUROpean Bone Over Forty Osteosarcoma Study, EMSOS = European Musculo-Skeletal Oncology Society, STEP = Register Seltene Tumor-Erkrankungen in der Padiatrie, LESS = Late Effects Surveillance System, PanCareLIFE = a pan-European consortium that addresses survivorship issues, CESS = Cooperative Ewing Sarcoma Study Group, CWS = Cooperative Weichteilsarkom-Studiengruppe, ENCCA WP17-WP7 = European Network for Cancer in Childhood and Adolescence Work Package 17--Work Package 7, ECCO = European Cancer Organisation, AWMF = Arbeitsgemeinschaft der Wissenschaftlich-Medizinischen Fachgesellschaften, ESMO-EURACAN-GENTURIS-ERN PaedCan = European Society for Medical Oncology--European Reference Network on Rare Adult Solid Cancers--European Reference Network on Genetic Tumor Risk Syndromes--European Reference Network on Paediatric Cancers. 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PMC10000535 | Population-based data on the incidence and surgical treatment of patients with colorectal cancer (CRC) and synchronous liver and lung metastases are lacking as are real-life data on the frequency of metastasectomy for both sites and outcomes in this setting. This is a nationwide population-based study of all patients having liver and lung metastases diagnosed within 6 months of CRC between 2008 and 2016 in Sweden identified through the merging of data from the National Quality Registries on CRC, liver and thoracic surgery and the National Patient Registry. Among 60,734 patients diagnosed with CRC, 1923 (3.2%) had synchronous liver and lung metastases, of which 44 patients had complete metastasectomy. Surgery of liver and lung metastases yielded a 5-year OS of 74% (95% CI 57-85%) compared to 29% (95% CI 19-40%) if liver metastases were resected but not the lung metastases and 2.6% (95% CI 1.5-4%) if non-resected, p < 0.001. Complete resection rates ranged from 0.7% to 3.8% between the six healthcare regions of Sweden, p = 0.007. Synchronous liver and lung CRC metastases are rare, and a minority undergo the resection of both metastatic sites but with excellent survival. The reasons for differences in regional treatment approaches and the potential of increased resection rates should be studied further. liver metastases lung metastases colorectal cancer synchronous metastases incidence treatment Bengt Ihre Research FellowshipRuth and Richard Julin foundationRegion Stockholm (clinical postdoctoral appointment)This research was funded by Bengt Ihre Research Fellowship and Ruth and Richard Julin foundation and supported by Region Stockholm (clinical postdoctoral appointment). None of the funding organizations had any role in the design and conduct of the study; in the collection, management, and analysis of the data or in the preparation, review, and approval of the manuscript. pmc1. Introduction Colorectal cancer (CRC) is the fourth most frequently diagnosed cancer and second leading cause of cancer-related death in Sweden . About 15-25% of all CRC patients have distant metastases at the time of diagnosis of primary tumor in the colon or rectum, named synchronous metastases, where liver metastases are found in 17% and lung metastases are found in 5% . Even though liver and lungs are the two most frequent sites of distant metastatic spread from CRC , the simultaneous diagnosis of both liver and lung metastases synchronously to CRC is not as frequent. A Dutch nationwide population-based study concluded that simultaneous liver and lung metastases were present in only 3.4% of all patients diagnosed with CRC between 2008 and 2011 . The general assumption is that the complete metastasectomy of liver and lung metastases from CRC is oncologically beneficial . The few studies on the surgical management of simultaneously diagnosed liver and lung metastases include both synchronously and metachronously diagnosed metastases and report a 5-year survival of 43-72% if all the intended metastasectomies are completed . For comparison, the overall median survival for the entire group of patients with synchronous liver and lung metastases is estimated to be 11.4 months . Due to the complexity of these patients, especially if synchronously diagnosed with the primary tumor in situ, decisions about selection and timing for surgical resection should be managed in the setting of a multidisciplinary team (MDT). Previous studies have shown that a low proportion of patients, about one-third, complete the initially intended curative resections due to disease progression . These studies are based on the already selected patients referred to a liver MDT; thus, the actual proportion of patients presenting with synchronous liver and lung metastases and the resection rates are still unknown. The aim of this nationwide registry-based study was to report on the incidence of synchronous liver and lung metastatic CRC, the proportion of patients undergoing metastasectomy and survival associated with different treatment approaches. 2. Materials and Methods The present study is a population-based cohort study that includes all patients diagnosed with CRC in Sweden between the years 2008 (9.2 million inhabitants) and 2016 (9.9 million inhabitants), utilizing data from several nationwide registers in Sweden. The overall incidence of CRC in Sweden decreased in the past decade, but in patients under 50 years of age, the incidence of CRC continued to increase over time . Colon resections are performed at 47 hospitals, while rectal cancer is resected at 31 hospitals. Referral to a liver or thoracic MDT meeting is decided at the local colorectal cancer MDT. In Sweden, liver and lung resections are regionally centralized to six University hospitals, each providing weekly held liver and lung-specific MDT meetings. Swedish Colorectal Cancer Registry: All patients diagnosed with CRC and registered in the Swedish Colorectal Cancer Registry (SCRCR) between 2008 and 2016 while living in Sweden were extracted from the registry. The SCRCR is a nationwide quality registry that includes data on all patients diagnosed with CRC. The completeness, defined as the proportion of all cases registered in the SCRCR of all CRCs, is assessed annually by comparison to the Swedish Cancer Registry with an estimated overall completeness of 98.8% . The registry contains data on date of diagnosis of the primary tumor, preoperative investigations and findings including the presence of liver and or lung metastasis, site and stage of the CRC, operative treatment of the primary tumor, histopathologic examination including distant metastasis (liver, lung and other locations) and data on the postoperative course after resection of the primary. The accuracy of the registration of synchronous metastases was recently validated and found to be high, where synchronous metastases were wrongly registered in 3.6% and not registered in 1% . National Patient Register: The personal identity number assigned to all residents in Sweden enables linkage among different national registries. To identify the whole cohort of interest consisting of patients with simultaneous liver and lung metastases, data from SCRCR were linked to data from the National Patient Register (NPR). Data from all hospitalizations in Sweden are included in NPR, and reporting is obligatory in both public and private healthcare facilities. The information available in NPR includes all inpatients' and outpatients' visits including date of admission, date of discharge, main diagnosis, secondary diagnosis enabling up to 21 accompanying diagnoses during the intended hospitalization period, and data on procedures. From NPR, patients with liver metastases (C78.7) and lung metastases (C78.0) as the main or secondary diagnosis documented on an inpatient or outpatient visit within six months prior to and six months after the date of diagnosis of primary CRC were identified and included in the study cohort. The codes used for identifying other metastatic sites were as follows: pleura (C78.2), other respiratory organs (C78.1/.3), peritoneum (C78.6), other gastro-intestinal (C78.4/.5/.8), urinary system (C79.0/.1), skin (C79.2), nervous system (C79.3/.4), bone (C79.5), ovary (C79.6), adrenal (C79.7), and other specified (C79.8). National Quality Registry for Liver, Bile Duct and Gallbladder Cancer: In the National Quality Registry for Liver, Bile Duct and Gallbladder Cancer (SweLiv), one of the sections registers the surgical interventions in the liver and includes data on the metastatic burden in the liver (number of metastases, size of largest metastasis, involved segments), detailed data on the intervention (resection and or ablation) and intervention-related complications. For patients with CRC metastatic disease, only patients undergoing intervention are included. Patients who underwent a liver intervention were thus found in SweLiv, and all available data concerning the liver metastatic burden and procedure-related data were extracted. The registry has a 97% nationwide coverage for inclusion . National Quality Registry on Thoracic Surgery: In the same way, ThoR--a National Quality Registry on Thoracic Surgery--exists and contains data on surgical procedures in the lungs with a last reported nationwide coverage of 92.5% (primary and secondary tumors) . This registry only contains information on patients undergoing a thoracic intervention, and if so, data were extracted. To account for interventions not registered in SweLiv or ThoR, procedural codes linked to liver or thorax were extracted from NPR and merged into the dataset. Lung interventions (resection and/or ablation) and liver interventions (resection and/or ablation) were identified by the appropriate codes, and both liver and lung intervention codes were presumed to correspond to metastasectomy, but information on intent (curative or not) and if complete metastasectomy was performed cannot be interpreted from NPR. Metastases detected within 6 months prior to and 6 months after the documented diagnosis date of primary colon or rectal cancer were considered synchronous. Liver and lung metastases were labeled as simultaneously diagnosed if both metastatic sites were diagnosed within the above-mentioned timeframe. Primary tumors of the caecum to the transverse colon were assigned as right-sided colon tumors, whilst tumors in the splenic flexure to sigmoid colon were assigned as left-sided colon tumors. Major hepatectomy was defined as resection of 3 or more liver segments according to Couinaud's classification . Descriptive statistics were used, and categorical variables are described using proportions and compared using the Chi-squared test or Fisher's exact test. Continuous variables are described as median values (interquartile range (IQR) and min, max) if non-normally distributed and compared using Kruskal-Wallis equality-of-populations rank test (three-group comparison). Changes in treatment trend was evaluated using the Chi-square test for trend (denominator: all patients with liver and lung metastases). The main outcome was survival estimated from the diagnosis of liver metastases to date of death or last follow-up up set to 5 September 2019. The reverse Kaplan-Meier method was used to assess median follow-up . Univariable survival estimates were illustrated in Kaplan-Meier graphs and compared using the log-rank test. Statistical significance was set to p < 0.050. STATA version 15.0 (StataCorp, Collage Station, TX, USA) was used for all data analyses. This study was approved by the Ethics Review Board in Linkoping, Sweden. Because this study was a register-based study, individual informed consent was not required. 3. Results 3.1. Participants and Baseline Characteristics In all, 60,734 individuals were diagnosed with colorectal cancer in Sweden between 2008 and 2016. Of these, 2703 (4.5%) were identified as diagnosed with liver and lung metastases within 6 months prior or after the diagnosis of colorectal cancer . Among these patients, 780 (29%) were also diagnosed with extrahepatic, non-pulmonary metastases. When excluding these, 1923 (3.2%) remained for further analysis, as illustrated in Figure 1. Patient and primary tumor characteristics are summarized in Table 1. 3.2. Treatment of Liver and Lung Metastases Liver resections were conducted on 156 patients (based on data from NPR) of which 143 patients were identified in SweLiv and metastasis-specific data could be extracted for 35 patients undergoing complete metastasectomy and for 48 patients having liver resection and resection of the primary tumor only . The majority, 84 patients (54%), underwent liver resection on one occasion, while 46 patients (29%) had repeat hepatectomy and a further 27 patients (17%) underwent liver resection at three or more occasions. Lung resections were performed on 61 patients of which 44 patients were found in ThoR and metastasis-related data could be extracted on 32 patients having complete metastasectomy . There were 44 (2.3%) patients having surgery for both liver and lung metastases and resection of the primary tumor . This subgroup, undergoing complete metastasectomy (n = 44), included patients who were younger and less often had a right-sided primary tumor compared to patients having liver resection only (n = 83) (Table 2). The subgroup where only the primary tumor was resected (no metastasectomy, n = 594) had a higher American Society of Anesthesiologists (ASA) score and a more advanced primary tumor stage as compared to the two other treatment groups depicted in Table 2. Only 58 patients (10%) among those who did not undergo any metastasectomy were referred for metastatic surgery (Table 2). Multiple liver metastases did not preclude patients from hepatectomy (Table 2). Four patients in the "liver resection and resection of primary only" group did not undergo liver resection per se but instead underwent thermal ablation. If these patients were too frail to undergo resection or if the MDT decided on ablation for any other reason cannot be interpreted from the register data (Table 2). The complexity of treatment strategy in metastatic CRC is illustrated by the multiple treatment allocations found in this cohort . 3.3. Survival The median follow-up from diagnosis of liver metastases was 10 months (range 0.03-142 months, IQR 135 months) and median follow-up of patients who were alive at end of follow-up was 53 months (range 29-142 months, IQR 103 months). Estimated 5-year OS following resection of liver and lung metastases (including resection of primary tumor) was 93.2% (95% CI 80.3-97.8%) and 74.2% (95% CI 57.2-85.3%), respectively . Patients undergoing liver resection and resection of their primary tumor had a significantly better survival compared to those only undergoing resection of the primary tumor, an estimated 5-year OS of 29.3% (95% CI 19.2-40.0%) versus 2.6% (95% CI 1.5-4.2%), p < 0.001, despite not having resection of the present lung metastases, as illustrated in Figure 2. Twenty-six patients had liver resection only with an achieved estimated 5-year OS of 40% (95% CI 21-58%) and 5% (95% CI 0-21%), respectively (Table 3). The reason for not proceeding with complete metastasectomy and resection of the primary cannot be ascertained from the registries. Likewise, 13 patients underwent lung resection and resection of the primary CRC (Table 3) with 5-year OS of 85% (95% CI 51-96%) and 73% (95% CI 25-91%), respectively, in whom the extent of the liver metastatic burden, administration and response to chemotherapy remains unknown. 3.4. Trend over Time The annual number of patients diagnosed with synchronous liver and lung metastases are depicted in Figure 3. Divided into three-year periods, no significant increase was seen in the proportion of patients undergoing complete metastasectomy when comparing the first time period (2008-2010) to the last time period (2014-2016) with 1.5% and 2.7%, respectively (p = 0.107) nor between the second (2011-2013) and last time period (2.6% versus 2.7%, p = 0.845). Referral for metastasectomy, by treating colorectal surgeon and/or medical oncologist, did however increase over time, from 7% (n = 44) in the first time period to 13% (n = 86) in the second time period and 22% (n = 145) in the last time period (p < 0.001). A clear trend over time was a decrease in the proportion of patients undergoing resection of the primary tumor only, in the presence of synchronous liver and lung metastases, from 46% in the first time period to 20% in the last time period, p < 0.001 . The median survival of the entire group, irrespective of treatment, increased from 8 months (95% CI 6.7-9.1 months) in the first time period (2008-2010) to 10.5 months (95% CI 9.3-11.7 months) in the second time period (2011-2013) and 11.3 months (95% CI 10.3-13.1) in the third time period (2014-2016), with a significant increase in median survival comparing time period 1 and 3, p = 0.001 . 3.5. Regional Differences The percentage of patients receiving complete metastasectomy ranged from 0.7% to 3.8% between the six healthcare regions of Sweden, as illustrated in Figure S2. There was a significant difference in resection rate between the regions with the highest and lowest resection rates, p = 0.007. 4. Discussion This nationwide registry-based study demonstrates several intriguing findings. First, isolated synchronous liver and lung metastases are diagnosed in 3.2% of patients with CRC. Second, among them, only 2.3% undergo complete metastasectomy. When complete metastasectomy was performed, it resulted in excellent estimated long-term survival of 74% at 5 years. Third, an intermediate survival was seen in patients undergoing resection of liver metastases only, even when the lung metastases were not resected. Fourth, contrary to what was expected, this study did not show an increase in resection rate over time but revealed a low referral rate for metastasectomy and regional differences in resection rates within Sweden. The proportion of synchronous liver and lung metastases aligns with previous findings of 3.1-3.4% . The actual resection rate of both liver and lung metastases in a population-based setting has not previously been reported on. The low resection rate presented in this study of 2.3% is perceived as unexpectedly low. Most other studies on resection rates originates from surgical cohorts naturally affected by selection bias, also including both synchronously and metachronously detected liver and lung metastases and most often with an already resected primary tumor . In these studies, about one-third of patients referred for the metastasectomy of simultaneously diagnosed liver and lung metastases underwent the intended curative treatment . The reason for the low resection rate presented in this study and whether the decision on resectability was justified or not cannot be deduced from the registries. A limitation of the study is that despite the high degree of coverage in the Swedish registries, the registries do not provide detailed information on reasons to deny surgical treatment. Certainly, as a proof of selection, the group that underwent liver resection was younger with lower ASA, presented with a less advanced primary tumor stage and was more often located in the left colon and rectum. Nevertheless, a non-negligible proportion of patients who underwent liver surgery in this study had multiple liver metastases and subsequent major hepatectomy, which is in line with the long-known fact that resectability is not determined by the number and size of liver metastases but rather a sufficient future remnant liver volume . The study draws attention to a low referral rate for metastasectomy; hence, one could hypothesize that not all patients eligible for metastasectomy are properly assessed for surgery. Generally, referral practice to regional MDT varies widely, from mandatory referral of all patients to referral at the discretion of referring physicians . Medical oncologists and colorectal surgeons assess the resectability of liver metastases differently . Reassessment of resectability by a hepatobiliary surgeon has shown that a meaningful number of patients with liver metastases are not managed according to the best available evidence, and the potential for higher resection rates is substantial . Clearly, there is a need for an individualized, multidisciplinary approach to handle the complex decision-making process of patients with synchronously diagnosed liver and lung metastases, especially with the primary tumor in situ. Even though no randomized trial has been performed on the topic, it is widely presumed that metastasectomy of both liver and lung metastases generates superior survival. Consistent with several other studies, a high estimated survival rate of 74% at 5 years was achieved among those selected to undergo complete metastasectomy in this study . Contrary, the non-metastasectomy cohort, of which an unknown proportion had received palliative chemotherapy, had an estimated 5-year survival of 2.6%. The assumption that the surgical removal of lung metastases favorably affects survival has been questioned through the results from the randomized trial of Pulmonary Metastasectomy in Colorectal Cancer (PulMiCC) . From that trial, it became clear that the assumption of zero survival without metastasectomy is contradicted and that the survival difference varies little, if any, in patients randomly assigned to metastasectomy compared to no surgical treatment of isolated lung metastases . As the cohort of the PulMiCC trial only included patients with resectable lung metastases, with previously resected CRC, no concurrent liver metastases and by being considered for metastasectomy, hence presumably having favorable features, it is unclear if the results from the PulMiCC trial can be applicable on patients suffering from synchronously diagnosed liver and lung metastases. Instead, the results from the PulMiCC trial can support that the theory of lung metastases themselves may not present the decisive factor for survival and thereby supporting the suggestion presented by Mise et al. to resect liver metastases in selected patients with unresectable lung metastases yielding a survival benefit compared to palliative chemotherapy only . This is further supported by the intermediate survival displayed in this population-based setting with a 5-year survival of 29% in patients having liver resection in the presence of synchronous lung metastases, even when the lung metastases were not resected, as opposed to 2.3% if not undergoing metastasectomy at all. On the other hand, an analysis based on the Surveillance, Epidemiology and End Results database, assessing the impact of metastasectomy in metastasized CRC patients with resected primary tumor, found a significant increase in survival for liver resection but not for metastasectomy of lung or both sites . Because of improved surgical techniques and treatment possibilities, we expected an increased resection rate of both liver and lung metastases over time but that was not found in this study. A Dutch study evaluating nationwide trends in incidence and treatment between 1996 and 2011 found an increase in metastasectomy rate over the years but only in patients with metastatic disease confined to one organ, which was most evident in patients with isolated liver metastases . The resection rate of multiple metastatic sites (not further specified) remained constant during the study period . Whether treatment trends have changed during the last five years remains to be revealed. The resection rate of the primary tumor in the presence of synchronous liver and lung metastases decreased over the study period, which was consistent with previous findings . This decrease could be the result of recent publications addressing the question of whether to perform palliative tumor resection in incurable stage IV disease or instead favoring colonic stents and diverting stoma . Over the last decades, thermal ablation has been established as a treatment alternative to liver resection, mainly for small liver metastases < 3 cm, as adjunct to liver resection for patients with multiple bilobar disease or as completion treatment . As a fact, current treatment guidelines include thermal ablation as a treatment alternative to liver resection for selected oligometastatic colorectal cancer disease . The use of thermal ablation in this cohort was limited and only registered in four patients as the sole treatment strategy. Perhaps, an extended utilization of thermal ablation could have increased the proportion of patients undergoing complete metastasectomy, especially in the frail subgroup of patients. This study shows variation in the rates of complete metastasectomy across Sweden. Similarly, such variations have previously been shown for both lung metastasectomy and liver metastasectomy . Despite statistical significance, these differences could be explained by the low number of patients having complete metastasectomy, but it requires reflection as Sweden, even though geographically large, has relative few inhabitants, and all six health units follow the same national guidelines for metastatic CRC . The present study is hampered by several limitations. First, it is limited by its retrospective nature dating back to treatment prior to 2016; on the other hand, this allows for a relatively long follow-up, making the survival analysis reliable. Second, although the study managed to present population-based data including resection rate of both liver and lung metastases for the first time, the analyses are limited by the lack of completeness regarding patient and tumor-specific data from the registries, regarding the large group of non-resected patients. In addition, no reliable data could be obtained on stereotactic body radiotherapy as treatment of lung metastases, nor the proportion of the non-resected population having chemotherapy. Eligibility for liver and lung metastasectomy includes confirming operative candidacy, which is also unknown from this dataset, as is whether the patient was assessed by a dedicated liver and or lung multidisciplinary team which makes the reasons for the low resection rate and whether the presumed low referral was reasonable or not impossible to analyze. The low number of patients having complete metastasectomy and the even lower number of patients with metastasis-related data makes any attempt on further analysis in a multivariable regression model meaningless. These limitations can only be overcome by the review of medical records on all patients, which hopefully is a future study. Nonetheless, the results from this study are still relevant, as they demonstrate excellent survival for patients completely treated for synchronous liver and lung metastasis as well as colorectal primary. 5. Conclusions In summary, we provide reliable population-based numbers on the incidence and curative treatment of synchronously diagnosed liver and lung metastatic CRC. We conclude that it is likely that a larger proportion of this patient cohort could be offered treatment that leads to a prolonged overall survival. For this reason, a larger proportion of this patient cohort should be referred and evaluated at a dedicated multidisciplinary conference with appropriate specialties attending. Supplementary Materials The following supporting information can be downloaded at: Figure S1: Kaplan-Meier estimates of overall survival irrespective of treatment in different time periods; Figure S2: Differences in treatment approach in the six healthcare regions of Sweden performing liver and lung resection. Click here for additional data file. Author Contributions Conceptualization, J.E., P.S., B.B. and K.H.; Data curation, J.E.; Formal analysis, J.E.; Funding acquisition, J.E.; Investigation, J.E., H.T., J.L.R., O.H., J.U., P.S., B.B. and K.H.; Methodology, J.E., P.S., B.B. and K.H.; Project administration, J.E.; Resources, J.E., P.S., B.B. and K.H.; Software, J.E.; Supervision, P.S. and B.B.; Validation, J.E. and K.H.; Visualization, J.E.; Writing--original draft, J.E., P.S., B.B. and K.H.; Writing--review and editing, J.E., H.T., J.L.R., O.H., J.U., P.S., B.B. and K.H. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee (protocol code 2017/363-31 with date of approval 20 September 2017). Informed Consent Statement Patient consent was waived due to anonymized data retrieved from patient registries. Data Availability Statement Data are available through the different Swedish national quality registries and the National Patient Registry following appropriate approval. Derived data supporting the findings of this study are available from the corresponding author J.E. on request after appropriate ethical approval. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Flowchart of the identification of all patients diagnosed with liver and lung metastases within six months from diagnosis of colorectal cancer between 2008-2016 in Sweden. CRC, colorectal cancer. Figure 2 Kaplan-Meier estimates of overall survival in patients treated with complete metastasectomy versus liver resection only versus resection of primary only. Complete metastasectomy including resection of the primary tumor resulted in a 5-year overall survival (OS) of 74.2% (95% CI 57.2-85.3%), while patients having resection of liver metastases and primary tumor had a corresponding estimated median and 5-year OS of 43 months (95% CI 31-49 months) and 29.3% (95% CI 19.2-40.0%), respectively. Resection of the primary tumor only resulted in a median survival of 10 months (95% CI 9-12 months) and a 5-year OS of 2.6% (95% CI 1.5-4.2%). There was a significant survival difference between complete metastasectomy and resection of liver metastases only, log rank test p < 0.001 and between the latter and resection of the primary only (no metastasectomy), log-rank test p < 0.001. CRC, colorectal cancer. Figure 3 Treatment trends over time. Bar chart illustrating different treatment strategies in different time periods; 2008-2010 (n = 608), 2011-2013 (n = 655), and 2014-2016 (n = 660). Complete metastasectomy was conducted in 9 patients (1.5%) in the first time period, 17 patients (2.6%) in the middle time period and 18 patients (2.7%) in the last time period of the study. The proportion of patients having resection of the primary tumor only, in the presence of synchronous liver and lung metastases, significantly decreased over time from 46% (2008-2010) to 28% (2011-2013) and finally 20% (2014-2016), log-rank test p < 0.001. CRC, colorectal. cancers-15-01434-t001_Table 1 Table 1 Patient and tumor characteristics in 1923 patients with synchronously diagnosed liver and lung metastases from colorectal cancer. n = 1923 (%) Patient characteristics Gender, n = 1818 Male/Female 1024 (56)/794 (44) Age (years), median (IQR) 70 (14) ASA, n = 671 1 68 (10) 2 323 (48) 3 232 (35) 4 48 (7) Primary tumor characteristics Primary tumor location, n = 1912 Caecum 206 (11) Ascending colon 151 (8) Hepatic flexure 73 (4) Transverse colon 69 (4) Splenic flexure 31 (2) Descending colon 59 (3) Sigmoid colon 515 (27) Rectum 808 (42) Resection of primary tumor 734 (38) Pathological tumor stage, n = 527 pT0 5 (1) pT1 4 (1) pT2 15 (3) pT3 290 (55) pT4 213 (40) Pathological nodal stage, n = 506 pN0 95 (19) pN1 166 (33) pN2 245 (48) Referred for metastasectomy 1 275 (14) 1 Referred for metastatic surgery evaluation by treating colorectal surgeon and/or medical oncologist, data from the Swedish colorectal cancer registry. Values are n (%) unless otherwise indicated. IQR, interquartile range; ASA, American Society of Anesthesiology. cancers-15-01434-t002_Table 2 Table 2 Comparison of patient and tumor characteristics in three different treatment strategies. Liver and Lung Metastasectomy and Resection of Primary, n = 44 Liver Resection and Resection of Primary Only, n = 83 Resection of Primary Only, n = 594 p *,+ Age (IQR) 62 (13) 68 (13) 71 (55) <0.001 ++ Gender, female 21 (48) 33 (40) 272 (47) 0.477 ASA 1 1 11 (25) 17 (21) 39 (7) <0.001 2 22 (50) 39 (49) 255 (48) 3 11 (25) 24 (30) 193 (36) 4 0 (0) 0 (0) 47 (9) Missing 0 3 60 Primary tumor location 2 Right-sided colon 4 (9) 27 (33) 186 (31) 0.032 Left-sided 21 (49) 28 (34) 190 (32) Rectum 18 (42) 28 (34) 217 (37) Missing 1 0 1 Tumor stage of primary 2 T1-T2 4 (9) 5 (7) 8 (2) <0.001 T3 30 (70) 51 (66) 201 (52) T4 9 (21) 21 (27) 181 (46) Missing 1 6 204 Referral for metastatic surgery 3 37 (84) 53 (64) 58 (10) <0.001 Number of liver metastases 1 N/A 1 10 (29) 17 (36) 0.646 ** 2-5 18 (51) 24 (50) 6-10 5 (14) 3 (6) >=11 2 (6) 4 (8) Missing 9 35 Liver resection 1 N/A Major hepatectomy 13 (32) 28 (37) 0.303 ** Minor hepatectomy 28 (68) 44 (58) Ablation only 0 4 (5) Missing 3 7 Size of largest liver metastasis, mm (IQR) 1 20 (18) 25 (21) N/A 0.016 ++ Missing 9 12 Number of lung metastases (min, max) 4 1 (1, 9) N/A N/A Missing 12 Unilateral lung metastases 4 32 (100) N/A N/A Missing 12 * p values refers to a comparison between all three groups, except ** which indicate a comparison between "complete metastasectomy" and "liver resection and resection of primary only". 1 Non-complete data on patient and metastasis characteristics due to missing data in National Quality Registry for Liver, Bile Duct and Gallbladder Cancer (SweLiv). 2 Non-complete data on primary tumor location from Swedish Colorectal Cancer Registry. 3 Referred for metastatic surgery evaluation by treating colorectal surgeon and/or medical oncologist, data from the Swedish Colorectal Cancer Registry. 4 Based on metastasis data on 32 patients from National Quality Registry on Thoracic Surgery. Values are n (%) unless otherwise indicated. + Categorical variables were compared using the chi-squared test or Fisher's exact test as appropriate. ++ Continuous variables were compared using Kruskal-Wallis equality-of-populations rank test (three-group comparison) or Wilcoxon rank sum test (two-group comparison. IQR, interquartile range; ASA, American Society of Anesthesiology; N/A, not applicable. cancers-15-01434-t003_Table 3 Table 3 Treatment allocation in 1923 patients diagnosed with liver and lung metastases within six months from diagnosis of colorectal cancer in Sweden between 2008 and 2016. Treatment Allocation n = 1923 Liver + Lung + CRC 44 (2.3) Liver + CRC 83 (4.3) CRC only 594 (30.9) No metastasectomy, no resection of CRC 1159 (60.3) Liver + Lung 3 (0.2) Liver only 26 (1.4) Lung only 1 (0.05) Lung + CRC 13 (0.7) Values are n (%). CRC, colorectal cancer. 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PMC10000536 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050925 diagnostics-13-00925 Article Hybrid Multilevel Thresholding Image Segmentation Approach for Brain MRI Sharma Suvita Rani Conceptualization Methodology Writing - original draft 1* Alshathri Samah Supervision Funding acquisition 2* Singh Birmohan Conceptualization Validation Formal analysis Supervision 1 Kaur Manpreet Validation Investigation Supervision 3 Mostafa Reham R. Visualization Supervision 4 El-Shafai Walid Software Resources 56 Zhang Yu-Dong Academic Editor Khan Muhammad Attique Academic Editor 1 Department of Computer Science and Engineering, Sant Longowal Institute of Technology and Engineering, Longowal, Sangrur 148106, Punjab, India 2 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia 3 Department of Electrical and Instrumentation Engineering, Sant Longowal Institute of Technology and Engineering, Longowal, Sangrur 148106, Punjab, India 4 Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura 35511, Egypt 5 Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh 11586, Saudi Arabia 6 Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt * Correspondence: [email protected] (S.R.S.); [email protected] (S.A.) 01 3 2023 3 2023 13 5 92517 1 2023 17 2 2023 21 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). A brain tumor is an abnormal growth of tissues inside the skull that can interfere with the normal functioning of the neurological system and the body, and it is responsible for the deaths of many individuals every year. Magnetic Resonance Imaging (MRI) techniques are widely used for detection of brain cancers. Segmentation of brain MRI is a foundational process with numerous clinical applications in neurology, including quantitative analysis, operational planning, and functional imaging. The segmentation process classifies the pixel values of the image into different groups based on the intensity levels of the pixels and a selected threshold value. The quality of the medical image segmentation extensively depends on the method which selects the threshold values of the image for the segmentation process. The traditional multilevel thresholding methods are computationally expensive since these methods thoroughly search for the best threshold values to maximize the accuracy of the segmentation process. Metaheuristic optimization algorithms are widely used for solving such problems. However, these algorithms suffer from the problem of local optima stagnation and slow convergence speed. In this work, the original Bald Eagle Search (BES) algorithm problems are resolved in the proposed Dynamic Opposite Bald Eagle Search (DOBES) algorithm by employing Dynamic Opposition Learning (DOL) at the initial, as well as exploitation, phases. Using the DOBES algorithm, a hybrid multilevel thresholding image segmentation approach has been developed for MRI image segmentation. The hybrid approach is divided into two phases. In the first phase, the proposed DOBES optimization algorithm is used for the multilevel thresholding. After the selection of the thresholds for the image segmentation, the morphological operations have been utilized in the second phase to remove the unwanted area present in the segmented image. The performance efficiency of the proposed DOBES based multilevel thresholding algorithm with respect to BES has been verified using the five benchmark images. The proposed DOBES based multilevel thresholding algorithm attains higher Peak Signal-to-Noise ratio (PSNR) and Structured Similarity Index Measure (SSIM) value in comparison to the BES algorithm for the benchmark images. Additionally, the proposed hybrid multilevel thresholding segmentation approach has been compared with the existing segmentation algorithms to validate its significance. The results show that the proposed algorithm performs better for tumor segmentation in MRI images as the SSIM value attained using the proposed hybrid segmentation approach is nearer to 1 when compared with ground truth images. brain tumor multilevel thresholding optimization algorithm segmentation Princess Nourah bint Abdulrahman University Researchers Supporting ProjectPNURSP2023R197 This work is supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R197), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. pmc1. Introduction Brain tumors, cancerous or noncancerous, are an outgrowth of abnormal cells in the brain. Malignant brain tumors are possible but rare . Malignant brain tumors have a non-uniform structure and contain active (cancer) cells, while benign brain tumors have a uniform structure and are not cancerous . Tumor identification, treatment planning, and monitoring of response to ontological therapy for brain tumors rely heavily on the reliable quantification and morphology of tumors derived from imaging data . Magnetic Resonance Imaging (MRI) is a noninvasive medical imaging technique . MRI produces high-quality images of human organs in 2D and 3D formats. Owing to its high-resolution images on brain tissues, the MR imaging modality is regarded to be one of the most accurate techniques for MRI categorization and is also used to identify many disorders due to its image quality. MRI is the most common method to examine brain tissues that have been infected. Different operations are applied to MRI images for the detection of brain tumors. Brain tumor segmentation is one important method which plays a crucial role in the detection of brain tumors. Gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) are the normal brain tissues that are separated from the tumor tissues (active tumor, edema, and necrosis) during brain tumor segmentation . Brain tumors are notoriously difficult to segment due to their various appearances in terms of location, size, forms, and recurrence . Different researchers have proposed several methods for brain tumor segmentation. Joseph and Singh used k means and morphological operation methods for the segmentation of the MRI image . Rehman et al. proposed a segmentation approach for the MRI images based on deep autoencoder-decoder . Toufiq et al. utilized an optimized threshold difference algorithm and rough set methods for the segmentation task . Tripathi et al. proposed an automatic segmentation method based on deep learning, cross-channel normalization, and parametric rectified linear units for the segmentation of the brain tumor . Bodapati et al. proposed a segmentation approach using two channel based deep learning model . Maqsood et al. proposed a multi-model system for segmentation using deep learning and a multi-class support vector machine . The deep learning-based models are widely used and are quite successful . However, the deep learning methods extensively depend on the size of the dataset and model performance degrades when there is a data distribution difference between the training data and test data. These models have parameter setting problems due to the presence of a large number of trainable parameters. Additionally, data collection at a high level is often time consuming, expensive, or even not possible in different scenarios. Thus, in such cases these models become inefficient. Apart from the deep learning-based segmentation methods, threshold-based approaches are used for the segmentation task by selecting the optimal threshold values. The threshold-based approaches are characterized by their ease of implementation and ability to give accurate segmentation results . It can be divided into two types: bi-level and multi-level threshold. In the bi-level category, a single threshold value is used in the prior category to separate the image into two homogeneous foreground and background areas. While in the multi-level category, these are utilized to segment an image into more than two areas based on pixel intensities, known as histogram . When segmenting an image, determining the thresholding values is very important due to the presence of enormous image thresholds; hence, this topic demands more investigation. This motivates us to propose a novel method for selecting the optimal multilevel thresholding values for segmentation of the brain tumors and performance enhancement for brain tumor detection. The remaining paper is organized as follows: Section 2 provides the related work. The proposed approach has been described in Section 3. In Section 4, the dataset used in this work has been detailed. The experimental results and discussions are given in Section 5. The conclusions and future scope of the work are given in Section 6. 2. Related Work In this section, segmentation methods based on the multilevel threshold values have been analysed. Two approaches are commonly used to determine optimal threshold values for segmenting a given image into several regions. These are Otsu method and Kapur entropy . Otsu method maximizes the between-class variance, while Kapur entropy maximizes the entropy of the classes. These techniques are applicable for determining a single threshold value. However, it is impossible to precisely determine ideal threshold values for multi-level in these approaches. Consequently, multi-level thresholding is considered a challenge that needs to be optimized. The relevant literature makes extensive use of meta-heuristic approaches to solve these challenges. Given their versatility and ease of implementation, academics have extensively demonstrated metaheuristic algorithms' ability to handle complex real-world issues, such as tracking of objects , feature weighting , feature selection , improvement of machine learning algorithms , monitoring , and engineering optimization algorithms , etc., in recent decades. Metaheuristic algorithms, in contrast to deterministic approaches, do not rely on gradient information to discover optimal solutions in the search space, instead, the randomly generated search agents and specialized operators. Many natural phenomena served as inspiration for these operators. Consequently, there are primarily three types of metaheuristic algorithms: (1) swarm-based, (2) natural evolution-based, and (3) physics-based methods. The two main approaches of study for multilevel image segmentation are the classical approach and the meta-heuristic approach. An incredible amount of progress has been made in the field of image segmentation during the past few decades. Traditional approaches to multilevel image thresholding have been proven to be inefficient due to the lengthy time required to find the optimal values with which to maximize the objective function. As a result, the computational time issue of multilevel thresholding algorithms for image segmentation is successfully addressed by a number of evolutionary metaheuristic algorithms in the literature. Oliva et al. proposed a multilevel thesholding method for the segmentation of the digital images based on the harmony search optimization algorithm . Oliva et al. utilized an electromagnetism-like algorithm for the selection of optimal threshold values of the images . Kandhway and Bhandari introduced energy curve and the minimum cross entropy and multiverse optimizer algorithm-based multilevel threshold selection approach . Upadhyay and Chhabra proposed Kapur's entropy and crow search optimization algorithm-based multilevel thresholding method . Rather and Bala proposed constriction coefficient-based particle swarm optimization and gravitational search algorithm to find the optimal threshold values by utilizing the strength of both algorithms . Resma and Nair proposed kill herd optimization for the segmentation of the images by maximizing the values of Kapur and Otsu entropy . Houssein et al. utilized black widow optimization and the best threshold configuration using Otsu or Kapur as an objective function for the optimal threshold selection of the images . Existing multilevel thresholding methods are only available for generalized images. The existing multilevel thresholding methods based on optimization algorithms are not utilized for the segmentation of the medical images because of their variability and complexity. Additionally, the optimization algorithm has the problem of slow convergence speed and can stuck in local optima. Considering these as motivation, in this work, a novel Dynamic Opposite Bald Eagle Search (DOBES) optimization algorithm has been proposed which is an improved version of the Bald Eagle Search (BES) algorithm. The modifications are applied to solve the problem of slow convergence speed and local optima stagnation of BES algorithm. Using this DOBES algorithm a hybrid Multilevel Thresholding Image Segmentation method has been proposed to find the optimal threshold values and the additional undesired regions of the segmented image are further removed using the morphological operations based post-processing procedure. The main contributions of this work are as follows:The DOBES algorithm is proposed by invoking the DOL method in the initialization, as well as exploitation, phases of the BES algorithm to solve the problems of slow convergence speed and local optima stagnation. A hybrid multilevel threshing approach is proposed for the segmentation of the brain tumor. The proposed hybrid segmentation approach is compared with state-of-the-art algorithms to show its significance. 3. Proposed Hybrid Multilevel Thresholding Image Segmentation Approach In this paper, a hybrid multilevel threshold segmentation approach has been proposed for the detection of brain tumors in the MRI image. The hybrid approach has two phases: Proposed Dynamic Opposite Bald Eagle Search (DOBES) optimization based multilevel threshold selection, and morphological operations-based post-processing procedure. The generalized block diagram of the proposed approach has been depicted in Figure 1. The hybrid approach has utilized the proposed DOBES algorithm in the first phase to find the optimal threshold levels. The selected optimal threshold levels are utilized to generate the threshold image based on the different threshold levels. The binary segmented image of the threshold image is generated for the next phase of operations. In the second phase, the morphological operations are applied to the previously generated binary segmented image to find out the area of interest and neglect the other undesired regions. The details of the different phases of the proposed approach are as follows. 3.1. DOBES Based Multilevel Threshold Selection Image thresholding is classified into two types: bilevel and multilevel. The multilevel technique is the progression from the bilevel approach . For a bimodal gray-level histogram with one valley between two peaks, the bi-level thresholding process is computationally simple and straightforward. The multilevel thresholding approach, on the other hand, is significantly more computationally demanding, but it might be well suited to a multimodal gray-level histogram with several peaks and troughs . However, as the number of necessary thresholds rises, multilevel thresholding becomes more complex, and it becomes considerably more difficult when working with a two-dimensional gray-level histogram. To overcome this issue, metaheuristic optimization algorithms have been developed, which yield exceptionally better results for different types of images. In this paper, a Dynamic Opposite Bald Eagle Search (DOBES) optimization algorithm is used for the selection of the optimal multilevel threshold of the brain MRI image. This algorithm is an improved version of the Bald Eagle Search (BES) optimization algorithm. The BES algorithm has problems of slow convergence and local optima stagnation. These problems are addressed in the DOBES algorithm by employing Dynamic Opposition Learning (DOL). The BES algorithm has three phases: Select, Search, and Swoop. The select phase is used for exploring the available whole search space to search for the solution. Whereas the search phase is used to exploit the selected area, and the swoop phase is used to target the best solution. The formulation of the three phases is as follows:(1) Pi,new=Pbest+axr(Pmean-Pi) In this equation, i is the total number of search agents, random variable r have value ranging from 0,1, and a is between 1.5,2. (2) Pi,new=Pi+m(i)x(Pi-Pi+1)+l(i)x(Pi-Pmean)where,l(i)=lr(i)max(lr)andm(i)=mr(i)max(mr)lr(i)=r(i)xsin(th(i)),mr(i)=r(i)xcos(th(i))th(i)=axpxrand,r(i)=th(i)+Rxrand where, a is a algorithmic parameter having values in between 5 and 10, rand have values in between 0 and 1, and R denotes the number of search cycles having value in between 0.5 and 2. (3) Pi,new=randxPbest+l1(i)x(Pi-c1xPmean)+m1(i)x(Pi-c2xPbest)l1(i)=lr(i)max(lr)andm1(i)=mr(i)max(mr)lr(i)=r(i)xsinhth(i),mr(i)=r(i)xcoshth(i)th(i)=axpxrand,r(i)=th(i) where c1,c2 are the algorithmic numbers having values in the range of 1,2. The proposed DOBES approach employs DOL to improve the initialization of the search agents. The initialization technique influences both the rate of convergence and the time necessary to find the best solution. As a result, DOL has been implemented in the DOBES algorithm to improve the likelihood of convergence to the global optimum while avoiding the stagnation problem associated with local optima. Furthermore, DOL has been used to accelerate the convergence rate by more equally spreading the search phases. DOL is utilized during the exploitation phase (the search phase) to analyse both the candidate solutions and their corresponding opposing candidate solutions, extending the exploitation space and improving the chance of discovering a better solution. The flow chart of the DOBES algorithm is given in Figure 2. The working of the DOBES algorithm starts with the parameter setting of the algorithm. Then, in the modified initialization phase randomly initial positions of the search agents have been generated, and using the DOL method opposite positions of the search agents have been determined. Fitness values have been calculated for the search agents and only the best search agents are selected. In the select phase, the positions of the search agents are updated to explore the search space and selection of the best area. The selected area has been extensively searched in the modified search phase. In the modified search phase, the DOL positions of the search agents are considered to improve the working of the exploitation phase. In the last phase, the best optimal solutions have been selected. These phases are repeated until a stopping criterion has been satisfied. Fitness Function for Multilevel Thresholding For the multilevel thresholding Kapur's entropy which is based on the probability distribution of the image's histogram is used as a fitness function in the proposed DOBES algorithm. The formulation of Kapur's method is as follows:(4) Fkap=i=0kHi,Hi=-j=tij=ti+1PjAjlnPjAj where Pj is the probability of the gray-levels. The DOBES algorithm has utilized Kapur's entropy as a fitness function to find the multilevel threshold levels in the MRI image. 3.2. Morphology-Based Post-Processing Procedure The morphological operations are used in the proposed hybrid approach to remove the additional undesired areas which are available in the binary segmented image. The operations used in this work are for the edge detection, image dilation, boundary detection, unwanted area removal, and area filling. Figure 3 shows the block diagram of the post-processing method adapted in this work. In Figure 3, the binary segmented image of the previous phase is used as an input image. The Canny edge detection method has been utilized in the first step to detect all the edges of segments, then the image dilation method has been used to fill the gaps by adding pixels in the edges of the selected area. In the next step, boundary detection method has been applied to fetch the boundaries of the regions and the small undesired regions are removed from the binary segmented image. The image filling morphological operation has been used to fill the remaining enclosed area regions. In the end, the region of tumor is selected from the processed image. The brain image processing layout of the proposed approach has been shown in Figure 4. The layout shows that the optimal multilevel threshold values have been first computed using the proposed DOBES optimization algorithm and using the selected multilevel threshold values a threshold image is generated. Further, a binary segmented image has been generated using the threshold image to detect the tumor region. After the generation of the binary segmented image, a post-processing procedure based on the morphological operations has been applied to select the tumor region and remove other undesired regions. 4. Dataset Description The brain tumor dataset has been taken from the Figshare website having URL [ (accessed on 15 November 2022)]. The dataset contains T1-weighted images of 233 patients. The images contain three types of tumor which are meningioma, glioma, and pituitary tumor. Figure 5 shows the input and ground truth images of the brain MRI. In Figure 5, different types of MRI image views, i.e., Axial, Sagittal, and Coronal have been depicted. In the figure, three types of tumors and their respective ground truth image representation of tumor locations in the brain. 5. Results and Discussions A hybrid segmentation approach for the segmentation of tumor regions from the MRI image has been proposed in this paper. The segmentation tests are performed on a computer equipped with the Windows 10 Pro operating system, an Intel(r) Xenon(r) CPU E5-2650 v3 (2.30 GHz), 8 GB of RAM, and MATLAB 2019a platform. The performance metrics used for the analysis of the proposed segmentation model are structured similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), fitness value, mean square error (MSE), and standard deviation. Mean square error (MSE) quantifies the error at each pixel position and generates a mean value, which is then used to calculate the image's PSNR. MSE is the difference in intensity between the input image and the segmented image. Peak signal-to-noise ratio (PSNR) is defined as the ratio of the highest achievable signal power to introduced noise. It is used to assess the quality of an image's reconstruction. The SSIM is a perception-based approach that takes image deterioration into account as a perceived change in structural information. SSIM is commonly used to determine the relationships between input and segmented images. 5.1. Comparison of Proposed DOBES and BES Algorithm for Benchmark Images The performance of the proposed DOBES algorithm has been analysed and compared with the original BES algorithm to show the significance of the proposed DOBES algorithm. For the performance comparison five benchmark images (Baboon, Boat, Cameraman, Couple, Male) have been selected. The images have been taken from the UCS-SIPI image dataset having URL [ (accessed on 27 January 2023)]. The values of the performance measures are provided in Table 1. These results are obtained after running the algorithm for 100 iterations and 10 reruns with a population size of 30. Table 1 shows a performance comparison of the proposed DOBES algorithm and BES algorithm for the benchmark images. The DOBES algorithm attains higher PSNR values for the baboon, boat, cameraman, and couple images while the BES algorithm attains higher PSNR values only for the male image. The DOBES algorithm attains SSIM metric values close to 1 and higher than the BES algorithm which shows that the DOBES algorithm performs better than the BES algorithm. This proves that the proposed DOBES algorithm is significantly better. 5.2. Analysis of Proposed Hybrid Segmentation Approach for the Brain Images The proposed hybrid segmentation approach has been tested on the Figshare MRI image database for the tumor area detected from the MRI images. In Figure 6, the input, threshold image, binary segmented image, final segmented image after morphological operations, and segmented images mapped with the ground truth images have been depicted for the BES and proposed hybrid segmentation approach. The morphological operations-based post-processing approach has been applied to the segmented images generated using BES optimization algorithm for a fair comparison of these algorithms. Figure 6 represents the segmentation performance of the BES and the proposed hybrid segmentation approach. From the figure, it has been observed that the BES algorithm fails to identify the optimal threshold values of the MRI image, and the tumor region is not identified. This can be observed in the image generated after mapping with the ground truth image. The pink part in the image shows the original ground truth value of the tumor region and the green part in the image shows the tumor region selected using the BES algorithm. In comparison to the BES algorithm, the proposed hybrid segmentation approach is able to successfully select the optimal threshold values, and the tumor region is segmented correctly. This is proved using the ground truth mapping image. The threshold levels and the convergence curves obtained using the proposed segmentation approach have been shown in Figure 7. Figure 7 depicts three threshold values in the histogram image of the MRI in the (a) part of the figure. From (a), it has been observed that the threshold values are optimal as the changes in the intensity level of the pixel values are correctly identified. In (b), the convergence curve has been plotted to show the convergence speed of the proposed hybrid segmentation approach. For the performance comparison of the proposed approach, three existing multilevel thresholding optimization algorithms are selected, i.e., Constriction Coefficient Based Particle Swarm Optimization and Gravitational Search Algorithm (CPSOGSA) , Electromagnetism-like Algorithm (EMO) , Harmony Search (HS) optimization . Additionally, the proposed algorithm is compared with the BES algorithm to show the significance of the proposed DOBES algorithm. In Figure 8, multilevel thresholding images and the corresponding binary images have been shown for the optimization algorithms. From Figure 8, it has been observed that the DOBES algorithm has segmented the tumor region clearly from the other brain regions whereas the BES and the state-of-the-art optimization algorithms fail to find the optimal threshold values for the tumor segmentation which leads to merging of the tumor region with the brain regions. This proves that the proposed algorithm is better in comparison to the comparative optimization algorithms. In Table 2, a comparison of the proposed hybrid approach with the existing methods for the brain tumor detection has been shown. The same morphological operations-based post-processing procedure has been applied to all the state-of-the-art algorithms for a fair comparison of the segmented brain tumor images. From the table, it has been observed that the proposed algorithm attains better values for the metrics 'best fitness values', as well as 'mean fitness values', in comparison to the BES and the other existing algorithms. Additionally, the proposed segmentation approach attains the highest or comparable SSIM values in the case of the segmented images vs. ground truth images. Thus, the multilevel threshold values which have been obtained using the proposed approach are optimal as detection of the tumor regions in the brain MRI images is close to ground truth values. Additionally, the visual analysis proves that the existing algorithms are not able to find the optimal threshold values especially in the cases where the contrast difference between foreground and the background regions are not quite distinctive. 6. Conclusions and Future Directions Brain tumors, a leading cause of death worldwide, are abnormal growths of tissue inside the skull that can impede the nervous system and body function. In neurology, segmenting brain MRIs is a foundational first step with multiple uses, including quantitative analysis, operational planning, and functional imaging. In this work, we apply the hybrid segmentation approach having two phases for the task of segmenting brain tumors from the MRI images. The selection of optimal multilevel threshold values has been accomplished using the Dynamic Opposite Bald Eagle Search (DOBES) optimization algorithm in the first phase and morphological operations-based post-processing procedure is utilized in the second phase for the selection of tumor regions. The proposed DOBES algorithm is a development by improving the original Bald Eagle Search (BES) algorithm. The original BES method has the issues of slow convergence and local optima stagnation. These problems are resolved in the DOBES algorithm by employing Dynamic Opposition Learning (DOL). Then the morphological operations based post-processing procedure has been applied for the tumor segmentation of the MRI image. The performance of proposed DOBES algorithm has been analysed using the benchmark images. The proposed DOBES algorithm achieves better PSNR and SSIM values in comparison to the BES algorithm for the benchmark images. The proposed hybrid segmentation approach is compared with the existing algorithm for the performance analysis. The SSIM values attained using the proposed hybrid segmentation approach for the segmented vs. ground truth images prove that the segmented images obtained using the proposed hybrid approach are closer to the ground truth images. Thus, the results show that the proposed approach successfully finds the optimal threshold values for the segmentation of the tumors. In the future, the proposed method can be used to find the optimal thresholds in RGB images. Additionally, in place of Kapur's method other variance schemes can be used as objective functions. Medical data analysis is now a very active area of research and a fertile application domain for machine learning. As a result, the proposed approach can be used to find optimal multilevel thresholding values from more complex medical images and feature selection to improve the classification performance. Acknowledgments The authors would like to acknowledge Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R197), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Author Contributions Conceptualization, S.R.S., S.A. and B.S.; methodology, S.R.S., B.S., M.K. and W.E.-S.; software, B.S. and M.K.; validation, S.R.S., B.S. and M.K.; formal analysis, S.R.S., S.A., B.S. and M.K.; investigation, B.S., M.K., R.R.M. and W.E.-S.; resources, S.R.S., S.A.; data curation, S.R.S., B.S. and R.R.M.; writing--original draft preparation, S.R.S., S.A. and B.S.; writing--review and editing, S.R.S., S.A., B.S., M.K., R.R.M. and W.E.-S.; visualization, S.R.S., S.A., B.S. and M.K.; supervision, M.K., R.R.M. and W.E.-S.; project administration, S.R.S., S.A., B.S., M.K., R.R.M. and W.E.-S.; funding acquisition, S.A. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement The data presented in this study are openly available in Figshare website at URL [ and USC-SIPI image database at URL [ Conflicts of Interest The authors declare no conflict of interest. Figure 1 Generalized layout of proposed hybrid segmentation approach. Figure 2 DOBES algorithm. Figure 3 Block diagram of morphological based post-processing. Figure 4 Image processing layout of proposed hybrid multilevel thresholding image segmentation approach. Figure 5 Visual representation of the brain MRI and respective ground truth images. Figure 6 Visual representation of the MRI images generated at different phases of proposed hybrid segmentation approach. Figure 7 Multilevel threshold and convergence curve of proposed hybrid segmentation approach. (a) Multilevel thresholds and (b) Convergence curve. Figure 8 Threshold and binary image of the optimization algorithms obtained using optimization algorithms. DOBES = Dynamic Opposite Bald Eagle Search optimization algorithm, BES = Bald Eagle Search optimization algorithm, CPSOGSA = Constriction Coefficient Based Particle Swarm Optimization and Gravitational Search Algorithm, EMO = Electromagnetism-like Algorithm, HS = Harmony Search optimization . diagnostics-13-00925-t001_Table 1 Table 1 Evaluation metrics of the proposed DOBES and original BES algorithm for benchmark images. Image Name Algo Name Optimal Level Best Fitness Value Mean Fitness Standard Deviation MSE PSNR SSIM Baboon DOBES 44.5825 41.2860 1.8289 3.90 x 103 22.2251 0.9028 BES 43.2949 41.0181 2.4316 1.05 x 103 17.9447 0.7972 Boat DOBES 45.0538 43.4139 1.4986 5.86 x 103 20.4532 0.7886 BES 44.5601 42.7437 1.6598 7.06 x 103 19.6419 0.7593 Cameraman DOBES 44.6614 42.7581 0.9297 4.05 x 103 22.0586 0.7587 BES 43.9419 41.5759 2.0517 5.56 x 103 20.6824 0.7063 Couple DOBES 43.9526 41.4636 1.1683 2.90 x 103 23.5099 0.5521 BES 41.8404 40.1056 1.7395 7.47 x 103 19.3993 0.4066 Male DOBES 45.6260 43.7534 1.4264 6.15 x 103 20.2439 0.7806 BES 43.6013 43.4959 1.6096 5.62 x 103 20.6373 0.7598 diagnostics-13-00925-t002_Table 2 Table 2 Evaluation metrics of the proposed hybrid segmentation approach. Tumor Name Image Number Algo Name Optimal Level Best Fitness Value Mean Fitness Standard Deviation MSE PSNR SSIM (Input Image vs. Threshold Image) SSIM (Segmented Image vs. Ground Truth) Meningioma 1 Proposed hybrid segmentation approach 47.9206 45.4620 1.7862 5.02 x 102 21.1280 0.6750 0.9998 BES 47.4714 44.8024 2.3320 1.07 x 103 17.8513 0.5552 0.9998 CPSOGSA 44.5615 42.1077 1.7931 5.12 x 102 21.0401 0.6665 0.9998 EMO 44.3197 44.2593 0.0754 8.67 x 101 28.7517 0.7650 0.9931 HS 42.1911 41.8324 0.2809 1.51 x 102 26.3402 0.7319 0.9927 177 Proposed hybrid segmentation approach 46.0736 44.4955 1.5804 1.35 x 103 16.8425 0.4624 0.9999 BES 45.3021 43.2352 2.5435 1.20 x 103 17.3250 0.4791 0.9975 CPSOGSA 43.5696 41.1617 1.4121 1.09 x 102 27.7433 0.6206 0.9973 EMO 44.1964 44.1614 0.0422 6.47 x 101 30.0209 0.6547 0.9974 HS 42.0029 41.4002 0.5052 2.38 x 102 24.3740 0.5914 0.9967 660 Proposed hybrid segmentation approach 48.8510 47.7180 1.5629 1.33 x 103 16.8945 0.4046 0.9997 BES 48.8194 46.1231 1.7590 1.28 x 103 17.0730 0.3872 0.0.9888 CPSOGSA 47.9582 42.7699 2.7136 1.92 x 103 15.2996 0.2862 0.9951 EMO 44.7735 44.6824 0.0878 1.94 x 102 25.2540 0.6314 0.9913 HS 41.9134 41.9134 0.0000 1.50 x 102 26.3837 0.6498 0.9916 Giloma 719 Proposed hybrid segmentation approach 48.3412 45.8864 1.8913 1.00 x 103 18.1200 0.5247 0.9999 BES 47.8164 44.8459 2.3497 1.04 x 103 17.9696 0.5205 0.9999 CPSOGSA 44.5352 40.5329 2.5836 1.29 x 102 27.0192 0.7309 0.9959 EMO 44.5907 44.5582 0.0728 9.33 x 101 28.4307 0.7228 0.9958 HS 42.5611 42.5611 0.3693 1.35 x 102 26.8168 0.7018 0.9961 799 Proposed hybrid segmentation approach 48.2201 46.6109 2.7537 1.33 x 103 16.8896 0.5149 0.9999 BES 48.1490 44.7736 2.2807 1.31 x 103 16.9455 0.5821 0.9969 CPSOGSA 43.4365 40.8422 1.9584 3.70 x 102 22.4465 0.6895 0.9999 EMO 44.0809 44.0121 0.1339 1.15 x 102 27.5277 0.7183 0.9989 HS 41.8422 41.8422 0.0000 1.40 x 102 26.6661 0.7505 0.9986 895 Proposed hybrid segmentation approach 47.9738 46.3416 1.9144 1.42 x 103 16.6180 0.3920 0.9999 BES 47.8793 45.2731 2.2741 1.35 x 103 16.8191 0.4138 0.9977 CPSOGSA 46.3880 42.3097 2.5580 7.08 x 102 19.6282 0.5084 0.9990 EMO 44.7794 44.6589 0.0832 1.71 x 102 25.8036 0.6951 0.9985 HS 42.9729 42.5060 0.0000 1.60 x 102 26.1007 0.7308 0.9986 Pituitary 59 Proposed hybrid segmentation approach 49.2296 46.8252 2.6490 1.82 x 103 15.5255 0.3652 0.9997 BES 48.1580 45.2139 2.0382 1.78 x 103 15.6157 0.3687 0.9981 CPSOGSA 45.7014 43.1113 2.3225 1.62 x 103 16.0319 0.3885 0.9982 EMO 45.2712 45.1999 0.1596 1.54 x 102 26.2647 0.7128 0.9982 HS 41.9849 41.9453 0.1430 1.26 x 102 27.1156 0.7223 0.9983 1391 Proposed hybrid segmentation approach 45.5724 44.3092 1.1470 1.02 x 103 18.0536 0.5370 1.0000 BES 45.3682 43.9759 1.4224 7.36 x 102 19.4634 0.6091 0.9986 CPSOGSA 43.5107 40.8545 1.6167 5.72 x 102 20.5536 0.6519 0.9999 EMO 42.0512 41.6049 0.2809 8.78 x 101 28.6962 0.7966 0.9980 HS 39.2840 38.4971 0.9387 1.84 x 102 25.4932 0.7513 0.9982 1405 Proposed hybrid segmentation approach 46.2615 44.8582 1.1550 1.48 x 103 16.4229 0.5128 0.9998 BES 46.0916 42.9182 2.3297 1.44 x 103 16.5362 0.5179 0.9998 CPSOGSA 44.3048 41.7757 1.9603 4.08 x 102 22.0293 0.7199 0.9995 EMO 43.6460 43.5694 0.1596 1.14 x 102 27.5647 0.8004 0.9987 HS 40.0705 40.0705 0.0000 1.82 x 102 25.5385 0.7476 0.9985 DOBES = Dynamic Opposite Bald Eagle Search optimization algorithm, BES = Bald Eagle Search optimization algorithm, CPSOGSA = Constriction Coefficient Based Particle Swarm Optimization and Gravitational Search Algorithm, EMO = Electromagnetism-like Algorithm, HS = Harmony Search optimization. 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PMC10000537 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050718 healthcare-11-00718 Article Identification of a Link between Suspected Metabolic Syndrome and Cognitive Impairment within Pharmaceutical Care in Adults over 75 Years of Age Macekova Zuzana 1 Fazekas Tomas 2 Krivosova Michaela 3 Dragasek Jozef 4 Zufkova Viera 5 Klimas Jan 1* Snopkova Miroslava 6 Cauli Omar Academic Editor Martinez-Arnau Francisco Miguel Academic Editor Buigues Cristina Academic Editor 1 Department of Pharmacology and Toxicology, Faculty of Pharmacy, Comenius University in Bratislava, 832 32 Bratislava, Slovakia 2 Department of Physical Chemistry of Drugs, Faculty of Pharmacy, Comenius University in Bratislava, 832 32 Bratislava, Slovakia 3 Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia 4 1st Department of Psychiatry, Faculty of Medicine, Pavol Jozef Safarik University, 040 81 Kosice, Slovakia 5 Department of Languages, Faculty of Pharmacy, Comenius University in Bratislava, 832 32 Bratislava, Slovakia 6 Department of Organisation and Management of Pharmacy, Faculty of Pharmacy, Comenius University in Bratislava, 832 32 Bratislava, Slovakia * Correspondence: [email protected] 01 3 2023 3 2023 11 5 71827 1 2023 20 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The prevalence of metabolic syndrome (MetS) and cognitive impairment (CI) is increasing with age. MetS reduces overall cognition, and CI predicts an increased risk of drug-related problems. We investigated the impact of suspected MetS (sMetS) on cognition in an aging population receiving pharmaceutical care in a different state of old age (60-74 vs. 75+ years). Presence or absence of sMetS (sMetS+ or sMetS-) was assessed according to criteria modified for the European population. The Montreal Cognitive Assessment (MoCA) score, being <=24 points, was used to identify CI. We found a lower MoCA score (18.4 +- 6.0) and a higher rate of CI (85%) in the 75+ group when compared to younger old subjects (23.6 +- 4.3; 51%; p < 0.001). In the age group of 75+, a higher occurrence, of MoCA <= 24 points, was in sMetS+ (97%) as compared to sMetS- (80% p < 0.05). In the age group of 60-74 years, a MoCA score of <=24 points was identified in 63% of sMetS+ when compared to 49% of sMetS- (NS). Conclusively, we found a higher prevalence of sMetS, the number of sMetS components and lower cognitive performance in subjects aged 75+. This age, the occurrence of sMetS and lower education can predict CI. metabolic syndrome older adults community pharmacy cognitive screening cognitive impairment pharmaceutical care Slovak Chamber of Pharmacists (Z.M.)21/SLeK/2019 Ministry of Education, Science, Research and Sport of the Slovak Republic (J.K.)VEGA 1/0195/20 This work was supported by the grant 21/SLeK/2019 from the Slovak Chamber of Pharmacists (Z.M.) and the grant VEGA 1/0195/20 from the Ministry of Education, Science, Research and Sport of the Slovak Republic (J.K.). pmc1. Introduction The prevalence of both metabolic syndrome (MetS) and cognitive impairment (CI) is increasing with age . According to the international classification of MetS the prevalence of MetS ranged from 37% up to 60% in the elderly population . Although cognitive impairments and dementia are often age-related disorders and according to World Health Organisation affect approximately 20-25% older population, they are not part of normal ageing . In 2019 already over 55 million people worldwide suffer from cognitive disorders, AD, or dementia, and this number will almost double every 20 years, expect reaching 78 million in 2030 and 139 million in 2050 . In general, MetS impairs overall intellectual functioning , and CI is the most significant factor of therapy failure in chronic disorders , mainly in older adults . The presence of MetS, according to the classification of the International Diabetic Federation 2006 for the European population , can also be routinely evaluated in pharmaceutical care in a community pharmacy. For assessment of CI, Montreal Cognitive Assessment (MoCA) can be used as a simple, easy-to-use, but reliable cognitive screening tool with high sensitivity for mild cognitive impairment . Community pharmacists are the most accessible and frequently contacted healthcare professionals worldwide who may play a crucial role in the identification of individuals with chronic disorders , including those suffering from cognitive disorders in case that pharmacist is trained in the diagnosis of this type of disorder. Nowadays, common pharmaceutical care such as preparation, storage and dispensation of medicines, the provision of expert advice on their correct and safe use, or advice on the possibilities of non-pharmacological regimen measures is being globally expanded by other professional pharmacists' competences (for example the monitoring of biochemical parameters, blood pressure measurement, management of obesity, smoking cessation, etc.) which are gradually becoming a part of pharmaceutical care worldwide which is more patient-oriented, defined as the expanded pharmaceutical care. Pharmaceutical care provided in nursing homes or senior care centres brings additional benefits to older adults . Identification of potentially preventable risk factors (such as MetS and/or its components) and/or early stages of serious illnesses (e.g., cognitive impairment and dementia) within pharmaceutical care might help in slowing the rate of their progress and further disability . Assessment of cognitive functions in elderly patients with MetS components is critical, but due to lack of time, it is routinely performed by only 24% of general practitioners, although 82% believe screening is needed . Thus, the extension of pharmaceutical care toward cognitive screening might provide significant benefits for patients and the healthcare system. The association between MetS and CI appears to be age-dependent . The presence and onset of cardiovascular risk factors for CI are crucial for vascular modifications that result in reduced cerebral blood flow and metabolism in the brain . While younger old (60-74 years) may be more susceptible to the cardiovascular load imposed by MetS on central neural pathways regulating mental processes , on the other side, MetS might have a positive influence on health status in older old (75+) individuals . In our pilot study, we focused on the risk of suspected MetS (sMetS) estimated when providing healthcare service by a pharmacist and its related CI in the elderly and showed the feasibility of cognitive testing in pharmaceutical care and its potential in identifying sMetS subject affected by CI but we did not investigate the impact of MetS in different age groups of elderly patients. We concluded that a quick and simple cognitive assessment could be a helpful extension of pharmaceutical care . As our previous findings showed: (i) 56% of a random population over 60 years of age exhibited lower cognitive performance on the MoCA (ii) subnormal MoCA scores were significantly present with increasing age of the respondents, and (iii) the presence of MetS moderately but significantly correlated/associated negatively with the MoCA score . Currently, in the same cohort as previously , we aimed to investigate whether sMetS has different effects on cognition in "younger old" (60-74 years) and "older old" (aged 75 years and over) individuals. Recent research reports diverse findings . While MetS contributes to cognitive decline in "younger old" subjects , there is evidence that this effect may be weakened or vanished in 75+ individuals . More detailed studies of the relationship between MetS and CI in the elderly population before the age of 75 and at the age of 75+ could have a global benefit , but further studies are needed. In this study, we aimed to investigate the impact of sMetS on cognition in aging individuals, with respect to the age category of 75+ years. Subjects were provided with pharmaceutical counselling, which means the specific patient-oriented pharmaceutical care service in community pharmacy targeted at the identification of components of MetS and MetS itself (according to IDF classification), including screening of cognitive features of enrolled older patients. We hypothesized that sMetS estimated within pharmaceutical care has a different influence on cognitive performance in a younger elderly population aged 60-74 years and in the 75+ population. We expected that younger old sMetS+ individuals will achieve significantly worse cognitive performance compared to the same age group without sMetS. On the other side, we expected that the cognitive performance in sMetS+ and old individuals will be either without difference or in the sMetS+ group only slightly weaker than in . 2. Materials and Methods 2.1. Study Settings, Design and Sample Size Here, we used data from a randomized pilot study in Slovakia , where 323 subjects were enrolled. Among them, 222 voluntary participants were interviewed in 16 community pharmacies, and 101 participants from 3 senior care centres aged 60 years and over were included, 63% in the 60-74 years group and 37% in the group 75+ (the age of the oldest participant was 95 years). 2.2. Study Participants and Selection The participants (68% women, 32% men), who visited a community pharmacy or lived in a senior care centre (between February 2018-February 2019) in Slovakia and who were willing to provide their general input data (socio-demographic information) and the list of all chronically used medications with the codes for their chronic diseases. Participants were randomly selected on the base of their voluntary consent and physical and mental ability to undergo screening. All respondents completed a simple data collection form in the Slovak language comprised of socio-demographic information (age, gender, education level), smoking and physical activity habits, and presence or absence of abdominal obesity, mediated by a pharmacist. The basic characteristics of the cohort sample are displayed in Table 1. Subsequently, a cognitive screening by the MoCA test was performed by trained pharmacists. Exclusion criteria were severe physical or mental health conditions that interfered with cognitive screening test realization and/or incompletely filled data collection form. We excluded 42 incompletely filled data collection forms. The forms were collected for one year (February 2018-February 2019), and the study was approved by the Ethics Committee of Faculty of the Pharmacy, Comenius University in Bratislava (EK FaF UK 01/2018). All procedures followed the relevant guidelines and regulations under the Declaration of Helsinki. 2.3. Classification of MetS and Assessment of Cognitive Function According to provided codes for patients' chronic diseases and information about the present/absence of abdominal obesity, there were identified individual components of MetS. Suspected metabolic syndrome (sMetS) was assessed according to the International Diabetes Federation Worldwide Definition of MetS, 2005, modified for the European population . Accordingly, patients were divided with respect to the presence (sMetS+) or absence of suspected MetS (sMetS-). The Montreal Cognitive Assessment is one of the available cognitive screening instruments, which scans seven cognitive domains: executive functioning; visuospatial abilities; language; attention, concentration and working memory; abstract reasoning; memory and orientation. The Slovak version of the Montreal Cognitive Assessment (MoCA) with a reduced cut-off of <=24 points for cognitive impairment by Bartos and Fayette was used by pharmacists who were trained in the MoCA screening tool. Administration time was approximately 15 min, participant achieved a score between 0-30 points. 2.4. Statistical Analysis Data were analysed using the SAS Education Analytical Suite for Microsoft Windows, version 9.3 (Copyright (c) 2012 SAS Institute Inc., Cary, NC, USA). The continuous demographic and clinical variables of study groups (e.g., age, the MoCA score) were represented by simple arithmetic mean, standard deviation, or 95% confidence interval. Categorical descriptive variables (e.g., sMetS status, MoCA status) were characterized by absolute frequencies and percentages. When comparing two groups with continuous data, a two-sample t-test was used. In addition, Pearson's Chi-Square test and Fisher's exact test of cross-tabulated data were performed to analyse the association between frequencies of categorical variables. The 0.05 significance level was used as a threshold for statistical significance for all tests, and 0.8 was taken as a minimally acceptable power of tests. Exogenous variables are independent of the error term (e.g., metabolic symptoms and cognitive function) and they may have a significant impact on the validity of the measurement. We investigated these terms by standard procedures of regression diagnostics and control procedures were applied, like sample randomization and matching, and finally the ANOVA method was used as a statistical control to reduce the possible effect of extraneous variables. We used random allocation which is a technique that minimizes confounders and eliminates systematic bias by allocating individuals for treatment and control groups solely by a chance. We chose this method for its simplicity and effectiveness in eliminating distortion. Due to the pilot nature of the study, we did not perform an exact a priori calculation of the number of participants according to the case-control methodology. However, the power of the performed tests was controlled by appropriate post hoc calculations. We also suggested simple predictive analytics to forecast the impact of patients' age, sMetS status, and education level on cognitive performance in the MoCA test. As exclusive predictors in this model, the age (dichotomic groups 60-74 years vs. 75+), sMetS status (sMetS+/sMetS-) or MetS components (central obesity, high blood pressure, dyslipidaemias, diabetes mellitus 2) and education level (dichotomic groups "lower education" for 12 years and less, vs. "higher education" for 13 years and more, were used. The calculated output data were the MoCA status (MoCA normal/MoCA lower cognitive performance). The success score of the prediction model was expressed by the evaluation of the confusion matrix in percentage. 3. Results 3.1. Prevalence of sMetS and Cognitive Impairment The prevalence of sMetS in the study cohort was 18.5% in 60-74 years participants and 27% in 75+ (NS). On average, individuals 75+ achieved significantly lower MoCA score (18.4 +- 6.0) than patients aged 60-74 (23.6 +- 4.3). Lower cognitive performance (MoCA score <=24) was more frequent in 75+ (85%) vs. participants aged 60-74 years (51%; p < 0.001). In both subcohorts (60-74 years vs. 75+), age had a significant influence on cognitive performance (p < 0.05; vs. p < 0.001, respectively). 3.2. Occurrence of sMetS and Patients' Cognitive Performance sMetS influenced MoCA score in 75+ seniors as we found a significantly higher occurrence of lower cognitive performance in MoCA in 75+ with sMetS (97%), when compared to 75+ (80%; p < 0.05; r2 = 0.063), the difference was -1.99 points in MoCA mean (NS). In contrast, the MoCA score in younger seniors was unaffected by the presence of sMetS. In participants aged 60-74 years, the prevalence of lower cognitive performance according to MoCA was 63% in the sMetS+ group and 49% in sMetS- (NS; the difference was -1.21 points in MoCA mean, NS). 3.3. Number of MetS Components and Patients' Cognitive Performance 75+ individuals had a significantly higher number of MetS components (2.2 +- 0.9) than 60-74 participants (1.6 +- 1.1; p < 0.001) in both age groups, however, the number of MetS components was not associated with patients' cognitive performance in MoCA. 3.4. Association between a MetS Status, Age, Education Level and Cognitive Performance We proposed here a simple predictive model using three input categorical components, such as an occurrence or absence of sMetS and affiliation with a given age group (60-74 vs. over 75 years) and the observed output data expressed by the cognitive performance group (below or above the norm) with the success rate of classification of 73% (p < 0.001). The odds ratio for the age group 75+ against the youngers was 5.54; Cl 95% = 3.24-9.83 (p < 0.001), and this parameter for the occurrence of sMetS against the missing metabolic syndrome was as high as 2.04; CI 95% = 1.11-3.87 (p < 0.05), respectively. The odds ratio for the lower education group against the higher was 3.88; CI 95% = 1.87-8.46 (p < 0.001). We also performed an alternative predictive model based on the number of MetS components and patients' cognitive performance expressed on the MoCA scale. The results of this model predicted a negative impact on the cognitive performance given by MoCA levels with the increasing number of MetS components (r = 0.44; p < 0.05) at the success rate of classification of 61%. The addition of other input parameters (gender, physical activity, smoking habits) that were available in the research did not improve the quality of the model. 4. Discussion Previously, in a pilot study investigating the feasibility of cognitive screening within extended pharmaceutical care in elderly patients with sMetS , we reported that the population over 60 years of age exhibits lower cognitive performance in MoCA test and subnormal MoCA scores are significantly present with increasing age of study participants. In this investigation which widens previous findings, we hypothesized that sMetS has a different influence on cognitive performance in the younger elderly population aged 60-74 years and the 75+ population. The main results of the present study are as follows: (i) Presence of sMetS did not have a significant effect on achieved MoCA score in elderlies aged 60-74 years; (ii) sMetS has, thought moderate but significant, effect on achieved MoCA score in participants aged 75 years and more. 4.1. Prevalence of MetS and Cognitive Impairment in Elderly Several recent studies reported that MetS increases the risk of developing CI or dementia for elderly patients aged 60-75 but not in the 75+ elderly population . These outcomes may have been related to a survival bias because participants with more severe MetS may have passed away earlier than reaching the older age . Our findings did not show an association between sMetS and lower MoCA scores in participants aged 60-74 years compared to age-matched patients without sMetS. The potential explanations of controversy may lie in the possible influence of single MetS components as they strongly correlate with lower cognitive performance . We can only speculate that there could be a more significant substantial influence of age than sMetS on CI in younger seniors. 4.2. Prevalence of MetS and Cognitive Impairment in Younger Elderly Patients Recent studies conferred that MetS-related CI that has been observed in younger elderly participants aged 60-74 years tends to diminish after reaching age 75+ and can disappear or reverse in an oldest-old cohort . Instead, our results showed the opposite, i.e., a minimal but significantly higher occurrence of MoCA <= 24 points in 75+ subcohort with sMetS when compared to the 75+ . Decelerated CI related to MetS was shown in the 75+ cohort , mainly in 85+ . 4.3. Prevalence of MetS and Cognitive Impairment in Older Elderly Patients The presence of MetS in 75+ may be a protective evolutionary factor against the harmful aging process , and it may also have survival benefits in 75+ individuals with cardiovascular diseases . Individuals with cardiovascular diseases who reached the age of 85+ may be relatively less susceptible to the adverse effects of MetS and its components . Late-life MetS can also suppress the effects of other risk factors for the deterioration of cognitive features, such as malnutrition . Weight loss may be a potential risk factor for CI or Alzheimer's disease and a part of the process of dementia . Our findings support the hypothesis that the effect of MetS on cognitive function with advancing age (after 75 years) is relatively weakened and that individuals with components of MetS aged 85+ years are probably more resistant to the effect of MetS on cognition. 4.4. Coexistence of the Three Risk Factors: Occurrence of MetS, Age 75+, Lower Education Predicts Lower Cognitive Performance Our predictive model for estimation of CI status was able to discriminate between individuals with (MoCA score <= 24) and without impaired cognitive functions (MoCA score >24) using three simple variables-- the age group (60-74 vs. over 75 years, presence or absence of MetS and lower and higher education level) and this was superior to the predictive model using the number of MetS components. It might represent a simple tool for pharmacists to identify risk patients for CI who could need an individual approach in pharmaceutical care, e.g., control and management of modifiable risk factors for CI, revision of the medical list, and management of medication with potential risk for CI. Risk patients for CI also may undergo cognitive screening in a pharmacy and then be advised to visit a specialist when needed. Although previously suggested predictive models reached higher predictive performance than ours, they used various parameters such as subjective well-being, educational level, marital status, and the presence of other chronic diseases obtained within the medical examination. The advantage of our predictive model lies in applying a few easy predictors to collect within routine pharmaceutical counselling. 4.5. Possible Pathological Background Explaining the Link between sMetS and CI Previously , we reported an influence of the individual sMetS components, type 2 diabetes mellitus, hypertension and obesity, but not dyslipidaemias, on lower cognitive performance. This is also relevant to current findings. First, numerous epidemical studies supported that diabetes is closely related to a higher risk of cognitive decline , including mild cognitive impairment and dementia. At the same time, cognitive dysfunction is increasingly recognised as an important comorbidity and complication of diabetes that affects patients' quality of life, diabetes self-monitoring, and is related to diabetes treatment-related complications . Watts and colleagues reported that insulin is an important predictor of cognitive performance and decline, in opposite directions. In healthy older patients with normal cognition, higher insulin predicted greater cognitive impairment on attention and verbal memory. In contrast, in the group with early Alzheimer's disease, higher insulin was associated with better cognitive performance in attention and verbal memory. In general, hyperglycaemia is associated with lower cognitive abilities and with a prevalence of mild cognitive impairment in elderly subjects and achieved a score in test Mini-Mental State Examination is negatively correlated with fasting hyperglycaemia in the elderly population . Diabetes is in close association with a high risk for hyperglycaemia and hypoglycaemia events, mainly in the elderly, which may be caused by the disease itself or by the glucose-lowering medication and may lead to impairment of cognitive features. Cognitive dysfunction can also predict these complications. Early identification of individuals, particularly in older age, with mild cognitive decline and adequate intervention, can improve adherence and may help to avoid later complications . Second, a number of studies unveiled a relationship between high blood pressure and cognition in the elderly population. Their results showed a significant association between elevated blood pressure and lower cognitive performance in older subjects . Combination of hypertension in midlife and low diastolic blood pressure in late-life were in relationship with reduction of brain volume and lower cognitive performance in the aging population . In addition, longitudinal study demonstrated that long duration hypertension predicted cognitive decline independent of age . In line with this, women at the age of 75 years had faster declines in global cognition associated with higher systolic blood pressure and lower diastolic blood pressure . Third, also a relationship between obesity and worsened cognitive performance was investigated by many studies though outcomes are controversial. While being overweight is related to a lower risk for cognitive decline in the elderly population, central obesity increases the risk for it . While obesity, as a component of MetS, in young and middle age means a risk factor for cardiovascular and cerebrovascular events , likewise weight loss later in life can mean an early warning signal for both development of Alzheimer's disease and mild cognitive impairment . The possible explanation may lay in a possible key link between obesity, but also other components of MetS, and cognitive decline as a consequence of inflammation and oxidative stress in the brain tissues . 4.6. Limitations Our study has certain limitations in addition to cohort size. First, we used only the medication list of patients and diagnoses on the prescription to identify sMetS components. Second, pharmacotherapy of other possible morbidities was not analysed. Also, possible biases might occur. The main sources of probable data distortion in our research are selection, information, and confounding bias. We assume the most significant contribution of selection bias. It is well known that age, education and estimated premorbid intelligence correlate significantly with the total MoCA score. Since it was a pilot study, the extent of these individual contributions was not estimated. 5. Conclusions We found a higher prevalence of sMetS, the number of sMetS components and lower cognitive performance in MoCA in patients aged 75+. We confirmed the hypothesis that advancing age has a significant influence on cognition in both age groups (60-74 years vs. 75+). We observed a moderate but significant link between sMetS and CI exclusively in individuals aged 75+ but not in younger old participants. This finding confirms that metabolic syndrome substantially contributes to loss of cognitive performance during senescence, and it should also be considered when providing pharmaceutical services, particularly in adults aged 75+. Considering that forgetfulness or impaired memory is a common reason for low adherence in the elderly, early identification of elderly patients with potential cognitive impairment can help control modifiable risk factors for CI, prevent irregular medication use or non-adherence to medication and thus delay further complications. Acknowledgments We thank Martin Vyhnalek, Peter Soltys, Jozef Dobrovic, Viera Rusinkova, Michal Hajduk, Adriana Simkova, Stefan Mudrik, Edita Dlhanova, and Bernadeta Gajdosova for their cooperation. Author Contributions Conceptualization, J.K.; Data curation, Z.M. and T.F.; Formal analysis, T.F.; Funding acquisition, Z.M. and J.K.; Writing--original draft, Z.M.; Supervision, M.K., J.D. and M.S.; Validation, M.K., J.D. and M.S.; Writing--review & editing, V.Z. and J.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Ethics Committee of Faculty of Pharmacy, Comenius University in Bratislava (EK FaF UK 01/2018). All methods were performed in accordance with the relevant guidelines and regulations and in accordance with the Declaration of Helsinki. Informed Consent Statement Not applicable, the pilot study was anonym. The study did not involve participating patients who can be identified. Data Availability Statement Data are available from the authors upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Impact of sMetS on the achieved MoCA score in the age group of 75+ years old participants. Group sMetS+ represents patient's data with the presence of metabolic syndrome, and those without it. Solid lines in the centre of points (MoCA score) show the group means, while dotted lines represent boundaries of the appropriate confidence intervals. Figure 2 Receiver operating characteristic curve for a measure of discrimination of MoCA status (MoCA normal/MoCA lower cognitive performance) using three input variables (age, MetS status, education level). healthcare-11-00718-t001_Table 1 Table 1 Characteristics of respondents according to age groups. 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PMC10000538 | Healthcare (Basel) Healthcare (Basel) healthcare Healthcare 2227-9032 MDPI 10.3390/healthcare11050661 healthcare-11-00661 Article Assessment of the Possibility of Using the Laryngoscopes Macintosh, McCoy, Miller, Intubrite, VieScope and I-View for Intubation in Simulated Out-of-Hospital Conditions by People without Clinical Experience: A Randomized Crossover Manikin Study Ratajczyk Pawel 1* Kluj Przemyslaw Data curation 1 Dolder Przemyslaw 1 Szmyd Bartosz Formal analysis 2 Gaszynski Tomasz 1 Hsiang Ning Luk Academic Editor 1 Department of Anesthesiology and Intensive Care, Medical University of Lodz, 90-549 Lodz, Poland 2 Department of Pediatrics, Oncology and Hematology, Medical University of Lodz, 90-549 Lodz, Poland * Correspondence: [email protected] 23 2 2023 3 2023 11 5 66121 12 2022 14 2 2023 21 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The aim of the study was to evaluate the laryngoscopes Macintosh, Miller, McCoy, Intubrite, VieScope and I-View in simulated out-of-hospital conditions when used by people without clinical experience, and to choose the one that, in the case of failure of the first intubation (FI), gives the highest probability of successful second (SI) or third (TI). For FI, the highest success rate (HSR) was observed for I-View and the lowest (LSR) for Macintosh (90% vs. 60%; p < 0.001); for SI, HSR was observed for I-View and LSR for Miller (95% vs. 66,7%; p < 0001); and for TI, HSR was observed for I-View and LSR for Miller, McCoy and VieScope (98.33% vs. 70%; p < 0.001). A significant shortening of intubation time between FI and TI was observed for Macintosh (38.95 (IQR: 30.1-47.025) vs. 32.4 (IQR: 29-39.175), p = 0.0132), McCoy (39.3 (IQR: 31.1-48.15) vs. 28.75 (IQR: 26.475-35.7), p < 0.001), Intubrite (26.4 (IQR: 21.4-32.3) vs. 20.7 (IQR: 18.3-24.45), p < 0.001), and I-View (21 (IQR: 17.375-25.1) vs. 18 (IQR: 15.95-20.5), p < 0.001). According to the respondents, the easiest to use were I-View and Intubrite, while the most difficult was Miller. The study shows that I-View and Intubrite are the most useful devices, combining high efficiency with a statistically significant reduction in time between successive attempts. videolaryngoscopes intubation out-of-hospital settings This research received no external funding. pmc1. Introduction Ensuring airway patency is the primary task of a paramedic in a patient with symptoms of respiratory failure . It enables the delivery of oxygen to the lungs and the elimination of carbon dioxide from the body . Various devices are used to obtain airway patency, e.g., oropharyngeal, nasopharyngeal, or supralaryngeal airway devices. However, the gold standard to ensure airway patency and at the same time to protect the lungs against the aspiration of food content is endotracheal intubation . Correct intubation requires not only theoretical knowledge but also considerable manual skills, which deteriorate if not constantly improved . This especially applies to people who do not perform it on a daily basis . In out-of-hospital conditions, endotracheal intubation is most often performed at the ground level in conditions requiring the adoption of non-physiological and non-ergonomic body positions, often in unfavorable environmental conditions. This results in a significantly reduced level of comfort for the professional, which together with the stressful situation related to the patient's life-threatening condition and responsibility for his or her health may translate into the effectiveness of intubation . Difficult or failed tracheal intubation is a well-known cause of morbidity and mortality associated with anesthesia and emergency medicine . It has been proven that repeated intubation attempts are associated with an increased incidence of adverse events , transport delay, prolonged hospitalization, poorer neurological outcomes and increased mortality . In the hospital setting, video laryngoscopy has been shown to reduce the number of failed intubations, improve the view of the glottis, and reduce airway trauma . However, there are only a few heterogeneous studies comparing video laryngoscopy and direct laryngoscopy in the pre-hospital setting . Moreover, in pre-hospital care, the success of intubation depends not only on the type of laryngoscope used, but also on the training and experience of the healthcare provider with the device. All these factors result in prolonged intubation, when intubation in out-of-hospital conditions are performed by people with little experience . Therefore, it seems reasonable to search for a device whose use by people with little or minimal clinical experience will result in the most effective and quickest endotracheal intubation, and at the same time will result in the shortest learning effect in the event of potential failures . The aim of the study was to assess the possibility of using the following laryngoscopes, Macintosh, Miller, McCoy, Intubrite, VieScope and the I-View video laryngoscope, in simulated out-of-hospital conditions by providers without clinical experience, and to choose the laryngoscope among them that, in the case of a failed first intubation, offers the greatest possibility of successful second or third intubation as soon as possible. The secondary aim was to assess the learning and teaching aspect of laryngoscopy for paramedics regarding the third attempt of intubation using videodevices or other laryngoscopes. In the available literature, there are little data comparing intubation times in consecutive intubation attempts. It seems to us that there is quite a significant dependency conditioning the potential usefulness of a given device in medical rescue, especially when it is used by people without clinical experience, as repeated, prolonged intubation attempts are associated with a later poor prognosis in patients . 2. Materials and Methods 2.1. Materials In the study, we compared the majority of laryngoscopes available on the market that enable direct laryngoscopy, Macintosh (HEINE Optotechnik GmbH & Co. KG, Gilching, Germany), Miller (Scope Medical Devices Pvt. Ltd., Ambala City, India), McCoy (McCoy Truphatek, Jerusalem, Israel), Intubrite(r) (LLC; Vista, CA, USA), VieScope(r) (Adroit Surgical, Oklahoma City, OK, USA) with a dedicated 15 Fr Voir Bougie guidewire, and I-ViewTM VL video laryngoscope (Intersurgical Ltd., Wokingham, Berkshire, UK), in a simulated out-of-hospital setting when used by people with little clinical experience on a manikin model (Laerdal Airway Management Trainer Stavanger Norway manikin of universal difficulty) (Scheme 1.). Endotracheal tubes No. 7 were used for intubation. In each case, the endotracheal tubes and guides were covered with a standard lubricant dedicated to simulators. Simulated out-of-hospital conditions were created by placing the manikin in a neutral position at floor level. 2.2. Study Design The study was conducted from 21 February 2021 to 8 June 2021 at the Norbert Barlicki University Teaching Hospital No. 1 in Lodz. Sixty randomly selected students in the third year of Paramedic Science, full-time first-cycle studies at the Medical University of Lodz, qualified for the study. All students signed informed consent for voluntary participation in the study. The exclusion criterion was prior clinical experience with the laryngoscopes used in the study. All participants listened to a 45 min lecture on the construction of laryngoscopes and the principles of using them, as well as the anatomical structure and the method and technique of intubation. After the presentation, the instructor presented the correct intubation with each of the 6 tested laryngoscopes. Then, under the supervision of the teacher, the students participated in the workshop where they had the opportunity to intubate a manikin placed on the operating table at the optimal height for each participant with each of the tested laryngoscopes. After a month, 60 students took part in the actual study. 2.3. Study Protocol After signing their informed voluntary consent to participate in the study, the following demographic and medical data of the test participants were recorded in pseudonymized form:Sex Age Experience level: the number of dummy intubations performed so far by the subject and which laryngoscopes were used for previous intubations. Participants were asked to perform three endotracheal intubations on a certified airway training manikin (Laerdal Airway Management Trainer Stavanger Norway, universal difficulty) placed at floor level in a neutral position (out-of-hospital simulation), using each of the evaluated laryngoscopes. Each participant used all devices in random order in a crossover arrangement. The order in which the laryngoscopes were used was randomized using sealed opaque envelopes. The locked randomization strategy was generated using the Randomizer Program (randomizer.org). Flow diagram is presented in Figure 1. Timing began with taking the laryngoscope and ended with initial ventilation with a resuscitation bag after placement and sealing of the endotracheal tube. Intubation was considered successful after confirming the breathing movements of the manikin's lungs. The attempt was defined as a failure in the absence of manikin breathing movements or for an intubation time of more than 60 s. The criterion of over 60 s defining the intubation attempt as unsuccessful was adopted due to the fact that the study was to assess the usefulness of the devices by people without clinical experience in intubation. After each intubation attempt with a given laryngoscope, two subsequent intubation attempts with the same device were made. After the completion of three intubations with a given laryngoscope, there was a break of at least 2 h (in order to eliminate the impact of intubation with a given laryngoscope on the use of the next device). After the break, the subject proceeded to three intubations of the manikin with a randomly selected device. The subject assessed intubation with a given laryngoscope on the basis of a subjective assessment of tracheal intubation difficulty (number rating scale 0-10, 0: no difficulty, 10: highest difficulty). The following data were pseudonymously recorded for all simulations:Success of intubation, position of the tube: tracheal vs. esophageal (primary endpoint); Comparison of times to ventilation in the first, second, and third intubation attempts (secondary endpoint); Feelings of subjects (secondary endpoint). 2.4. Statistical Analysis The distribution of continuous data was checked with the Shapiro-Wilk test. As the average time of intubation has a distribution other than normal for at least one laryngoscope (p < 0.05), continuous data were presented as median with IQR. Furthermore, the dependencies between them were assessed with the Kruskal-Wallis test with Dunn's post hoc tests. Dependencies for dependent data (comparisons between approaches) were assessed with the usage of the t-student test for dependent data in the case of normal distribution and Wilcoxon's test in other cases. In both cases, the Bonferroni correction was used. Nominal data were present as n (% of total) and assessed with a test chosen based on the size of the smallest subgroup. The statistical analysis was performed using Statistica 13.1PL (StatSoft, Poland, Krakow). 3. Results 3.1. Demographic and Contextual Data The study included 60 third-year students of Paramedic Science (18 women and 42 men). The average age of the respondents was 22 years. Among the surveyed, 21 students had intubated the manikin fewer than 10 times so far, 22 students had performed between 10 and 20 only manikin intubations so far, and 17 students had performed more than 20 only manikin intubations. Before, everyone had used only the Macintosh laryngoscope for only manikin intubation. 3.2. Primary Endpoint For the first intubation, the highest success rate was observed for the I-View laryngoscope and the lowest for the Macintosh laryngoscope: 54 (90%) vs. 36 (60%; p < 0.001). In the case of the second intubation, the highest success rate was observed for the I-View laryngoscope and the lowest for the Miller laryngoscope: 57 (95%) vs. 40 (66.7%; p < 0.001). In the case of the third intubation, the highest success rate was again observed for the I-View laryngoscope, and the lowest this time for the Miller laryngoscope, McCoy laryngoscope and VieScope laryngoscope: 59 (98.33%) vs. 42 (70%; p < 0.001; see Table 1). There were no significant dependencies in the success rate between first and second attempts, second and third attempts, and first and third attempts . Comparing all laryngoscopes, the highest intubation efficiency was obtained for the I-View laryngoscope (90%, 95%, 98.33%), followed by the Intubrite laryngoscope (83.33, 88.3%, 91.67%) and the VieScope laryngoscope (65%, 80%, 70%). The effectiveness of the remaining laryngoscopes, Macintosh, McCoy and Miller, oscillated between 60% and 73.33% (see Table 1). An increasing learning curve in the use of the tested laryngoscopes was observed only for laryngoscopes I-View and Intubrite . 3.3. Secondary Endpoints There were significant differences between the mean time of intubation with the usage of the aforementioned laryngoscopes (p < 0.001). The statistically significant results of the performed post hoc Dunn's test are shown in Figure 3. A significant shortening of intubation time between the first and the third intubation was observed for the Macintosh laryngoscope (38.95 (IQR: 30.1-47.025) vs. 32.4 (IQR: 29-39.175), p = 0.0132), McCoy laryngoscope (39.3 (IQR: 31.1-48.15) vs. 28.75 (IQR: 26.475-35.7), p < 0.001), Intubrite laryngoscope (26.4 (IQR: 21.4-32.3) vs. 20.7 (IQR: 18.3-24.45), p < 0.001), and I-View laryngoscope (21 (IQR: 17.375-25.1) vs. 18 (IQR: 15.95-20.5), p < 0.001). Additionally, a significant shortening of intubation time between the first vs. second attempt and the second vs. third attempt was observed only for Intubrite and I-View laryngo scopes. In the case of the McCoy laryngoscope, a significant improvement was observed between the second and third approaches and the first and third approaches . According to the respondents, the easiest laryngoscope to use was the I-View laryngoscope, then the Intubrite, Macintosh, and McCoy, and finally the two laryngoscopes with straight blades: Miller and VieScope . 4. Discussion A significant reduction in intubation time between the first and third intubations was observed for the Macintosh laryngoscope, the McCoy, Intubrite laryngoscope and I-View laryngoscope. In addition, a significant reduction in intubation time between the first and second attempts and the second and third attempts was observed only with the Intubrite and I-View laryngoscopes. For the McCoy laryngoscope, there was a significant improvement in intubation times between the second and third attempts and the first and third attempts. The I-View laryngoscope turned out to be the easiest device to use in relation to the feelings of the subjects. This is probably due to the fact that there is no need to keep a straight line between the eyes of the professional and the glottis. In simulation, where the manikin was intubated at the floor level, the lack of the need to maintain this line is important because it does not require the intubating person to assume a more forced, bent body position, which is uncomfortable and non-ergonomic . In the case of the I-View laryngoscope, the possibility of evaluating the view of the glottis thanks to the device's monitor makes the assumed body position less bent and more friendly to the examined person . This is essential when a patient is intubated by people without experience in airway management. In this situation, if there is a choice between a Macintosh laryngoscope and video laryngoscopes, including I-View, some authors suggest choosing the latter . In the case of intubation by anesthesiologists, Wakabayashi believes that despite the fact that video laryngoscopes give better visibility of the glottis and are easier to use, the effectiveness and times of intubation with a classic Macintosh laryngoscope are at an acceptable level. This is vital given the widespread availability of Macintosh laryngoscopes and the still limited availability of video laryngoscopes . Among the video laryngoscopes, some authors suggest that the I-View laryngoscope is a suitable device for use in difficult conditions of pre-hospital care due to its ease and single use . In their study, Maritz et al. showed that the use of video laryngoscopy provided better intubation conditions, enabled better visualization of the glottis, and thus facilitated intubation when used not only by anesthesiologists with extensive experience in conventional and video laryngoscopy, but also paramedics with little previous experience in conventional and non-conventional experience in video laryngoscopy . Although the use of video laryngoscopes did not affect the success of intubation among anesthesiologists, in the hands of paramedics with little experience in intubation it reduced the failure rate from 14.8% for the conventional Macintosh laryngoscope to 3.7% for the video laryngoscope . The high position of the Intubrite laryngoscope is probably related to the new, ergonomic handle of this laryngoscope . The introduction of more ergonomic devices would reduce the professional's workload, which is an important factor determining patient safety . This applies in particular to people with little experience in intubation, in whom potential intubation difficulties may occur more often, especially in the group of obese patients. These patients, due to their physique and anatomy of the airways, may require greater strength to open the airways . According to J. Tesler and J. Rucker, when the Intubrite laryngoscope is used in out-of-hospital conditions the percentage of the need for repeated intubation attempts and the percentage of tooth damage decreased compared to the Macintosh laryngoscope . Similar results were obtained by T. Gaszynski, who stated that in the case of the Intubrite laryngoscope the patient's body is less traumatized compared to Macintosh laryngoscope . Macintosh and McCoy laryngoscopes in our study had similar first intubation success rates of 60% and 65%, respectively, second intubation success rates of 73.3%, and third intubation success rates of 73.3% and 70%, respectively. Furthermore, both laryngoscopes showed a significant improvement in intubation time between the first and third attempts. Moreover, McCoy laryngoscope enabled improvement between the second and third attempts. Therefore, in the case of failure of the first intubation, they give a chance for the correct placement of the endotracheal tube by people without clinical experience in subsequent attempts. However, in terms of average intubation times, both laryngoscopes were inferior to the I-View and Intubrite laryngoscopes, yet the Macintosh laryngoscope turned out to be easier to use in our study. There are different opinions in the literature regarding clinical situations in which one of these two laryngoscopes is more useful than the other. In a similar research model in which inexperienced medical students intubated manikins with Macintosh and McCoy laryngoscopes, Higashizawa found that the time needed to correctly position the endotracheal tube was similar with both laryngoscopes but the McCoy laryngoscope was more difficult to operate. The author suggested that the Macintosh laryngoscope is more useful for teaching inexperienced medical students , whereas Yildirim showed that the use of the McCoy laryngoscope shortens and provides easier intubation than the use of the Macintosh laryngoscope . However, Sethuraman came to different conclusions, stating that there is no advantage in using the McCoy laryngoscope over the Macintosh laryngoscope in the examination on manikins with difficult airways . In turn, in patients with limited mobility of the cervical spine, Uchida showed that the McCoy laryngoscope facilitates intubation compared to the Macintosh laryngoscope and it is also superior to some videolaryngoscopes . Similar conclusions were drawn by Gabbott and Maharaj . However, the latter author believes that, although the McCoy laryngoscope improves the visualization of the larynx more than the Macintosh laryngoscope in patients with both normal and difficult airways, reducing the number of intubation attempts and the number of optimization maneuvers required, it has proven to be more difficult and less reliable than the Macintosh laryngoscope . In patients with morbid obesity, Nandakumar et al. found the McCoy laryngoscope to be as effective as the Macintosh laryngoscope, and concluded that due to its widespread availability and familiarity the latter laryngoscope should be used in this group of patients . In our study, the successful first, second, and third intubation rates with the Miller laryngoscope were 73.3%, 66.7%, and 70%, respectively. There was no statistically significant reduction in intubation time between successive intubation attempts. It also turned out to be the most difficult laryngoscope to use among our subjects. Such a distant position of this laryngoscope in our list is probably due to the fact that the need to maintain a straight line between the subject's eye and the entrance to the airway in the case of intubation of a manikin lying at the floor level requires adopting the least comfortable position of the body. The lack of or little possibility of lifting the epiglottis when using this laryngoscope also affects the effort of the professional. Vidhya came to different conclusions, believing that the Miller's laryngoscope enables much better visualization of the larynx than the McCoy and Macintosh laryngoscope, even in patients with difficult airways . Similarly, Achen claimed that Miller's laryngoscope enabled better visualization of the airway entrance than the Macintosh laryngoscope, and therefore everyone should learn laryngoscopy using both laryngoscopes . This is important because, according to other authors, although the view of the glottis was better with the Miller laryngoscope than with the Macintosh laryngoscope, intubation conditions turned out to be better with the Macintosh laryngoscope . The Miller laryngoscope was superior to the Macintosh and McCoy laryngoscope for visualizing the glottis in children . The VieScope laryngoscope, a variant of the Miller laryngoscope requiring two-stage intubation, was found to be similarly effective during the first intubation as the McCoy and Macintosh laryngoscopes: 65%, 65%, and 60%, respectively. For the second intubation, its effectiveness increased to 80% and approached that of the Intubrite laryngoscope (88.3%), while during the third intubation, its effectiveness decreased to 70%. There was no statistically significant difference between intubation times in consecutive trials. According to the respondents, this device was also as difficult to use as the Miller laryngoscope. Such a low rank of this laryngoscope, and likewise the Miller laryngoscope, may result from the need to maintain the line of the intubating eye to the entrance to the airway and the need to adopt a more strenuous body position compared to the I-View, Intubrite, McCoy, and Macintosh laryngoscopes. The VieScope laryngoscope was originally designed for battlefield medicine, to facilitate the intubation of patients with difficult airways by being always ready for use and by focusing light on target tissues. This was confirmed in Maslanka's study, which showed that, taking difficult airways into consideration, the VieScope laryngoscope compared to the Macintosh laryngoscope had a shorter intubation time and a higher success rate on the first attempt . Similar conclusions were drawn by Wieczorek et al., who compared the use of bebe VieScope and direct laryngoscopy during emergency intubation on a model of a pediatric manikin performed by paramedics with and without personal protective equipment . In their prospective, multicenter, randomized study, Szarpak et al. proved that the VieScope laryngoscope enables more effective and faster intubation than the Macintosh laryngoscope in patients with suspected or confirmed diagnosis of COVID-19, who required pre-hospital cardiopulmonary resuscitation. In these studies, the study group consisted of paramedics with clinical experience and the ability to use various laryngoscopes. In our case, there was no scenario imitating difficult airways, which could result in the lack of advantage of this laryngoscope over other devices . Additionally, the study group consisted of people without clinical experience. Another difficulty for the participants in the study was the fact that it requires two stages to intubate, which can make it difficult for inexperienced people to use. This translated into a result similar to that of the Miller laryngoscope in terms of reported subjective intubation difficulties. Similar conclusions were reached by Ecker et al., who conducted their study on a manikin under simulated conditions of massive regurgitation. In the case of patients with lower esophageal sphincter insufficiency, intubation with the VieScope laryngoscope compared to the Macintosh laryngoscope turned out to be longer, similar to our study, and resulted in a greater amount of aspirated content into the airways. The study group consisted of experienced anesthesiologists, i.e., people who perform intubation on a daily basis and have experience in solving various situations that may occur during intubation . The longer intubation time of the VieScope laryngoscope compared to other airway devices was again noted by Ecker when he compared it to the Glidescope video laryngoscope in both simulated normal and difficult airways . The prolongation of intubation time using the VieScope laryngoscope was also found in the case of intubation of patients qualified for elective surgical procedures, with no advantage of this laryngoscope over the Macintosh laryngoscope in this group of patients . The study showed that it is necessary to constantly practice methods of airway management, including endotracheal intubation . It is particularly important to learn how to use multiple laryngoscopes, as it may be useful in unconventional situations requiring the modification of technique, equipment or body position . Each exercise in this area reduces the risk of making a mistake, reduces the stress of people performing a given procedure and, most importantly, increases the chance of survival of the patient and their return to the state before the event . A similar conclusion was drawn by Pieters et al. from their study comparing seven videolaryngoscopes in manikin settings . They compared the Macintosh classic laryngoscope, Airtraq, Storz C-MAC, Coopdech VLP-100, Storz C-MAC D-Blade, GlideScope Cobalt, McGrath Series5, and Pentax AWS. They observed 65 anesthetists, 67 residents in anesthesia, 56 paramedics and 65 medical students, intubating the trachea of a standardized manikin model. The results underline the importance of variability in device performance across individuals and staff groups, which has important implications for which devices hospital providers should rationally use. It is proven that videolaryngoscopes offer a better view of the entrance to larynx , and therefore reduce the risk of possible injuries related to intubation efforts ; however, training is still needed to avoid possible problems with the use of videolaryngoscopy . Using these tools for learning purposes for unexperienced providers, in addition, may provide greater applicability . The study has several limitations. Firstly, it was conducted on a manikin model, where simulated out-of-hospital conditions were created by placing the manikin at floor level, without the influence of other external factors affecting the effectiveness of intubation. Secondly, difficult airway scenarios were not also studied. Finally, the study group consisted of Paramedic Science students who, nevertheless, had little previous experience in intubating a dummy with a Macintosh laryngoscope due to their limited years of study. 5. Conclusions Taking into account the results of the study, the I-View and Intubrite laryngoscopes turned out to be the most useful devices for intubation in simulated out-of-hospital conditions by people with no clinical experience. They combined high efficiency of intubation with statistically significant shortening of intubation times between successive attempts. Due to the small study group and the manikin model, additional studies should be conducted on a larger group of subjects. Author Contributions Conceptualization, P.R.; methodology, P.R.; validation, P.R.; formal analysis, B.S.; investigation, P.K.; resources, P.K.; writing--original draft preparation, P.R., P.D. and B.S.; writing--review and editing, T.G. and P.D.; visualization, T.G., P.D. and B.S.; supervision, T.G.; project administration, P.R. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Bioethics Committee of the Medical University of Lodz (no. RNN/363/13/KB). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data available on request due to restrictions eg privacy or ethical. Conflicts of Interest The authors declare no conflict of interest. Figures, Scheme and Table healthcare-11-00661-sch001_Scheme 1 Scheme 1 From the left: Macintosh laryngoscope, McCoy laryngoscope, Miller laryngoscope, VieScope laryngoscope, Intubrite laryngoscope, I-View laryngoscope. Figure 1 Flow chart. Each participant performed intubation in all settings in a randomized controlled order. There were no drop-outs. Figure 2 Graph of the percentage success of intubation with a given laryngoscope in subsequent attempts. Figure 3 The mean time of intubation in different intubation approaches (Kruskal-Wallis test: p < 0.001, presented p are taken from the Dunn's test). Figure 4 Graph of mean intubation times with a given laryngoscope in subsequent intubation attempts. Figure 5 The feelings of the respondents (0--no difficulties; 10--maximum difficulties). healthcare-11-00661-t001_Table 1 Table 1 The comparison of success rates of intubation based on laryngoscopes and attempts. p-value of comparison of successful and unsuccessful attempts for each studied device. Laryngoscope Attempt Number Unsuccessful: Esophageal Position or Intubation > 60 s Successful: Tracheal Position p-Value Macintosh laryngoscope 1 24 (40%) 36 (60%) >0.05 2 16 (26.7%) 44 (73.3%) 3 16 (26.67%) 44 (73.33%) McCoy laryngoscope 1 21 (35%) 39 (65%) >0.05 2 16 (26.7%) 44 (73.3%) 3 18 (30%) 42 (70%) Miller laryngoscope 1 16 (26.67%) 44 (73.33%) >0.05 2 20 (33.3%) 40 (66.7%) 3 18 (30%) 42 (70%) VieScope laryngoscope 1 21 (35%) 39 (65%) >0.05 2 12 (20%) 48 (80%) 3 18 (30%) 42 (70%) Intubrite laryngoscope 1 10 (16.67%) 50 (83.33%) >0.05 2 7 (11.7%) 53 (88.3%) 3 5 (8.3%) 55 (91.67%) I-View laryngoscope 1 6 (10%) 54 (90%) >0.05 2 3 (5%) 57 (95%) 3 1 (1.67%) 59 (98.33%) Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000539 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050947 diagnostics-13-00947 Article Impact of Reduced Image Noise on Deauville Scores in Patients with Lymphoma Scanned on a Long-Axial Field-of-View PET/CT-Scanner Korsholm Kirsten Methodology Formal analysis Writing - original draft Writing - review & editing 1* Overbeck Nanna Data curation Writing - review & editing 1 Dias Andre H. Methodology Formal analysis Writing - review & editing 2 Loft Annika Conceptualization Methodology Investigation Writing - review & editing 1 Andersen Flemming Littrup Conceptualization Data curation Writing - review & editing 13 Fischer Barbara Malene Conceptualization Methodology Writing - review & editing 13 Glaudemans Andor W.J.M. Academic Editor Slart Riemer H.J.A. Academic Editor van Sluis Joyce Academic Editor 1 Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, 2100 Copenhagen, Denmark 2 Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, 8200 Aarhus, Denmark 3 Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark * Correspondence: [email protected] 02 3 2023 3 2023 13 5 94704 2 2023 24 2 2023 25 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Background: Total body and long-axial field-of-view (LAFOV) PET/CT represent visionary innovations in imaging enabling either improved image quality, reduction in injected activity-dose or decreased acquisition time. An improved image quality may affect visual scoring systems, including the Deauville score (DS), which is used for clinical assessment of patients with lymphoma. The DS compares SUVmax in residual lymphomas with liver parenchyma, and here we investigate the impact of reduced image noise on the DS in patients with lymphomas scanned on a LAFOV PET/CT. Methods: Sixty-eight patients with lymphoma underwent a whole-body scan on a Biograph Vision Quadra PET/CT-scanner, and images were evaluated visually with regard to DS for three different timeframes of 90, 300, and 600 s. SUVmax and SUVmean were calculated from liver and mediastinal blood pool, in addition to SUVmax from residual lymphomas and measures of noise. Results: SUVmax in liver and in mediastinal blood pool decreased significantly with increasing acquisition time, whereas SUVmean remained stable. In residual tumor, SUVmax was stable during different acquisition times. As a result, the DS was subject to change in three patients. Conclusions: Attention should be drawn towards the eventual impact of improvements in image quality on visual scoring systems such as the DS. LAFOV Deauville score lymphoma PET/CT reconstruction methods This research received no external funding. pmc1. Introduction Total-body positron emission tomography (PET) and long axial field-of-view (LAFOV) PET represent visionary innovations in clinical nuclear medicine with improved sensitivity compared to standard-axial field-of-view (SAFOV) PET. These new techniques enable either improved image quality, reduction in injected activity-dose, or decreased acquisition-time . The improved image quality is mainly a result of the extended axial FOV capturing more photon pairs and thus providing a higher detection efficiency and sensitivity gain of 5-10 x compared to the same detector SAFOV system , but also the state-of-art time-of-flight (TOF) resolution of 225 ps contributes to an increase in effective sensitivity . With PET/CT structural anatomy is combined with metabolic information, and this modality is commonly used in oncology, cardiology, rheumatology, and infectious diseases. The most widely used tracer in oncology is Fluorine-18-fluorodeoxyglucose ([18F]FDG), a glucose analogue providing a unique means of non-invasive assessment of tumor glucose metabolism. Malignant lymphomas comprise a heterogeneous group of cancers, and the risk of being diagnosed with lymphoma increases markedly with age. Hodgkin and Burkitt lymphomas dominate in younger ages, whereas follicular, marginal zone, mantle cell, and diffuse large B-cell lymphomas are more common with older age . [18F]FDG PET/CT has become the standard procedure for staging of disease in patients with FDG-avid lymphomas, as [18F]FDG-PET/CT is superior to CT alone in delineating extent of nodal/extranodal disease, including liver, spleen, and bone marrow involvement. During treatment of lymphoma, an interim [18F]FDG-PET/CT after two (1-4) cycles of chemotherapy can help assess early treatment response and thereby differentiate between patients needing escalated treatment regimens or reduced intensity protocols. In addition, [18F]FDG-PET/CT is used to evaluate status after end of treatment (EOT), with complete metabolic remission (CMR) at both interim and EOT predicting a better overall survival (OS) and longer progression-free-survival (PFS) . In 2009, the Deauville score (DS) was introduced . The DS ranges from 1 to 5 and scores the highest metabolic activity in (eventual) residual disease compared to metabolic activity in liver and mediastinal blood pool. The DS is now standard for reporting of clinical [18F]FDG-PET/CT scans. With the publication of the Lugano classification in 2014 , non-progressive disease could be divided into CMR in case of DS of 1, 2, or 3 with FDG-uptake equal to or less than liver-uptake or partial metabolic response (PMR) with a DS of 4 or 5--with reduced uptake compared with baseline. Stable disease or no metabolic response refers to a DS of 4 or 5 with no obvious change in FDG uptake, and progressive disease to a score of 4 or 5 in any lesion with an increase in intensity of FDG uptake from baseline (and/or new FDG-avid foci consistent with lymphoma). In recent years, new iterative reconstruction algorithms including point-spread-function (PSF) and TOF have been introduced. These new algorithms can significantly change maximal standardized uptake values (SUVmax) especially in small lesions compared to conventional reconstruction algorithms, however, only moderately affecting SUVmax in liver and vascular background . Accordingly, Quak and coworkers reported that the use of PSF could increase the lesion-to-liver ratio (based on SUVmax) with up to 31% . As the DS compares SUVmax in residual lymphoma to SUVmax of the mediastinal blood pool and the liver, these new reconstruction methods can have a considerable impact on the DS, as reported by various groups . With the new LAFOV PET/CT-scanner systems, the increased sensitivity can be exploited to either reduce acquisition time, injected radioactivity dose, or a combination of both. Alberts et al. demonstrated that their LAFOV PET/CT system could deliver images in less than 2 min with an image quality comparable to those from a SAFOV PET/CT obtained in 16 min. In addition, even shorter acquisition times (down to 0.5 min) allowed for adequate image quality with respect to lesion detection. Van Sluis et al. confirmed this ability to reduce scan time with a LAFOV PET/CT and they, too, reported a markedly reduced noise in the liver with increasing scan duration--especially when the reconstruction method included PSF. With our new LAFOV scanner, we also noticed a remarkably reduced image noise with increasing acquisition time, especially in the liver. Therefore, with this study, we seek to compare DS for different image acquisition times (90 s, 300 s, and 600 s) on the LAFOV Siemens Biograph Vision Quadra system, Siemens Healthineers, Knoxville, reconstructed with and without PSF to investigate if/how this might influence the DS in patients with lymphomas. We hypothesized that the reduced image noise, especially in the liver, could result in an increased tumor-to-liver ratio and thus a higher DS. 2. Materials and Methods 2.1. Patients Ninety-four consecutively referred patients with lymphoma referred for [18F]FDG PET/CT from 1 September 2021, until 31 January 2022 were included. Patients referred for assessment of treatment response (both interim and EOT) in follicular, Hodgkin, B-cell, and T-cell lymphoma were included in the study. Patients referred for initial staging of lymphoma disease, suspicion of recurrence, or unconfirmed suspicion of lymphoma were excluded (21 patients). Approval from the local Ethics Committee was not required as the project qualifies as a quality assurance study. The study was approved by the departmental review board (Ref. no 481_21), and all patients gave written and oral consent to participate in the study. 2.2. PET Acquisition and Reconstruction Parameters PET-scans were performed on a Biograph Vision Quadra PET/CT-scanner (Siemens Healthineers, Knoxville, TN, USA) in the Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, Copenhagen, Denmark according to the EANM guidelines for tumor imaging . Patients fasted for 4 h before injection of 3 MBq/kg [18F]FDG intravenously. All PET-studies were performed approx. 60 min after tracer injection. Patients were scanned from the base of the skull to mid-thighs. PET reconstructions were performed by two different methods: Ordered Subset Expectation Maximization (OSEM) or OSEM+PSF, termed TrueX by the vendor. Both methods included TOF and were reconstructed using 4 iterations of 5 subsets into 440 by 440 matrices (1.65 mm x 1.65 mm voxel size) with a slice thickness of 2 mm matching the CT. Data were acquired in list mode with full acceptance angel, for reconstruction a maximum ring difference (MRD) of 85 was used. Gaussian post-filters of 4 mm and 2 mm were used for OSEM and OSEM+PSF, respectively, and all data were reconstructed into static time frames with duration of 90 s, 300 s, and 600 s. Diagnostic CT with intravenously and orally administered contrast was performed when the indication was EOT; for interim treatment response, a low-dose CT was performed. Attenuation correction was based on a low-dose CT. 2.3. Clinical Evaluation A team consisting of a nuclear medicine specialist and an onco-radiologist evaluated all scans for clinical purposes on a Syngo.via workstation (Siemens Healthineers) before enrollment in the study. 2.4. Quantitative Evaluation For quantitation of FDG-uptake in the liver/mediastinum and in residual lymphomas, we used the medical imaging software Mirada DBx (version 1.2.0.59, Mirada Medical Limited, 2016, Oxford, UK). The metabolically most intense residual target lesion in each patient representing residual lymphoma was contoured (volume of interest, VOI); in addition, a banana-shaped VOI was drawn in the center of the right lobe of the liver and another VOI in the thoracic aorta avoiding the vessel wall and eventual calcifications (mediastinal blood pool, MBP) . The VOIs were saved as DICOM Radiotherapy structure sets (RTstructs). All VOIs were outlined on OSEM+PSF 90 seconds' reconstruction images and subsequently transferred to all other image reconstructions. The reconstructions of the two methods with three different frame durations were converted into MINC format (McConell Brain Imaging Centre, Montreal) and resampled to fit the CT slices. The RTstructs were converted into MINC format and used as a mask to retrieve the intensity values within the different VOIs. The mean, maximum, and standard deviation were retrieved for every VOI and converted into SUVs. All baseline scans were systematically reviewed to ensure initial involvement of the tumor site. No diffuse lymphoma-involvement of the liver was noticed in any of the patients. 2.5. Visual Evaluation Images reconstructed with respectively OSEM (90, 300, and 600 s) and OSEM+PSF (90, 300, and 600 s) were evaluated visually on two separate days by two experienced nuclear medicine physicians. DS was assigned as DS 1 (no visible lesion and no residual uptake), DS 2 uptake <= mediastinal blood pool, DS 3 > mediastinal blood pool <= liver, DS 4 uptake > liver, DS 5 uptake markedly (2-3 times) > liver. 2.6. Statistics Differences in SUVmax between different acquisition times within the same reconstruction method, and between reconstruction methods, were assessed using a one-tailed paired t-test. A p-value < 0.05 was considered statistically significant. Coefficient of variance (COV) was calculated for characterization of image noise (defined as the ratio of the standard deviation of SUV to the mean SUV in healthy liver tissue). All statistical procedures were performed using IBM(r) SPSS(r) Statistics. 3. Results Seventy-three patients were included; however, due to missing data, five patients were omitted from further analysis, ending up with 68 patients. Clinical characteristics of the patients including age, sex, and type of lymphoma are displayed in Table 1. 3.1. Visual Evaluation As expected, image noise was visually clearly reduced with increasing acquisition time, especially in liver parenchyma . DS of all patients for the different time series and reconstruction methods are displayed in Table 2. With OSEM+PSF reconstruction, the DS differed in three patients: Patient number 21 with refractory Hodgkin's lymphoma scored DS 4 on 90 s images and DS 5 on 300 and 600 s images due to visually clearly reduced noise in liver. Patients number 41 and 52, both with DLBCL, scored DS 3 on 90 s images and DS 4 on the longer reconstructions , also due to significant visual reduction of noise in the liver (see also Table S1, Supplementary material). Only one patient (no. 21) differed in DS within the different OSEM reconstructions with DS 4 at 90 s images and DS 5 at 300 and 600 s images. All other patients scored equally with OSEM reconstruction. 3.2. Clinical Implications In two patients scored with DS on OSEM+PSF, the difference in DS could have an implication on further treatment, as DS 3 is considered CMR (responder), whereas DS 4 is considered PMR (non-responder). With OSEM reconstruction, no impact on further treatment was observed as only one patient differed in DS (DS 4 to DS 5, both non-responder) for all acquisition times. 3.3. Quantitative Evaluation SUVmax and SUVmean of liver parenchyma for the different acquisition times for OSEM+PSF and OSEM reconstruction are displayed in Figure 2. There were significant differences in SUVmax between all acquisition times within both OSEM+PSF and OSEM reconstructions (p < 0.05); however, no significant differences were observed between SUVmean for the different acquisition times for either reconstruction method. The same pattern applies to MBP . The tumor SUVmax in OSEM+PSF and OSEM did not differ significantly between the different acquisition times . Comparing tumor SUVmax between reconstruction methods, we found a significant higher SUVmax (p < 0.05) when using PSF. Due to less noise in the liver, the tumor SUVmax/liver SUVmax ratio increased with increasing acquisition time ; however, the tumor SUVmax/liver SUVmean remained unchanged . 3.4. Image Noise Coefficient of variance (COV) decreased as expected with increasing acquisition time . A COV < 15% is considered an acceptable image noise level for clinical interpretation , and for 300 s images, all scans were below this level--except for two outliers. 4. Discussion In this study, we compared FDG-PET/CT scans with different acquisition times on a new generation LAFOV PET/CT scanner. The visually most convincing change in image quality was seen in the liver parenchyma with a remarkable reduction in image noise. Quantitatively, we observed that the liver SUVmax decreased significantly with longer acquisition times. This change in SUVmax in liver parenchyma can have different implications, among others in patients with malignant lymphoma, where the DS is defined as the ratio between tumor SUVmax and liver SUVmax. We did not see any change in tumor SUVmax between different acquisition times--neither for reconstructions with PSF nor without PSF. Due to decreasing SUVmax in liver, the DS changed with longer acquisition times in three patients, when reconstruction included PSF, two of these from DS 3 to DS 4, which could have an impact on further treatment. Without PSF, DS was only subject to change in one patient, from DS 4 to DS 5. Previously, Enilorac and coworkers reported that risk stratification of patients with lymphomas was not affected by choice of reconstruction method, although DS was re-classified due to reconstruction method in 14% (I-PET) and 8.4% (EOT) of their patients. Contrasting this, Ly and coworkers described that using different reconstruction methods (silicon-photomultiplier-based (SiPM) reconstruction, commercially sold as Q.Clear, versus OSEM), could have a large impact on DS as five non-responders (DS 4 and DS 5) in their study were reclassified as responders (<=D3). This was in agreement with Wyrzykowski and coworkers who report that the use of Q.Clear reconstruction algorithms caused an alteration in DS in 22 cases, of which 10 cases were converted to the non-responder group, in four cases with impact on treatment strategy. This was also in agreement with our findings, where the use of PSF generated more alterations in DS than when using OSEM. SUVmax in small lesions can differ between different reconstruction methods. This also applies to our study, where we found a significant higher tumor SUVmax in reconstructions with PSF compared to OSEM in concordance with previous studies . Two studies have previously evaluated the impact of reduced scan time on DS in patients with lymphoma and both reported no change in DS, when either reducing acquisition time from 120 s to 90 s per bed position or reducing total scan time from 15 min to 5 min using continuous-bed-motion . However, both studies were performed on Siemens Biograph Vision systems and not on a Biograph Vision Quadra PET/CT system, which provides an axial FOV of 106 cm, a higher spatial resolution, and a remarkably increased sensitivity, probably explaining the differences. Yet, they found that reduced acquisition time led to an increase in image noise, which is in line with our results and other studies . We found that liver SUVmean did not change significantly with changing acquisition time, whereas liver SUVmax decreased significantly with increasing acquisition time, explained by SUVmax being based on a single voxel and therefore more sensitive to noise. This supports previous findings and suggestions that liver SUVmean would perform better as reference instead of liver SUVmax. For example, Zwezerijnen et al. report that liver SUVmean is the most robust metric against VOI size, location, reconstruction protocol, and image noise level, and they propose to use liver SUVmean as reference for tumor assessment instead of SUVmax. Others take it further and propose to replace the visual Deauville scale by a quantitative method, such as qPET or DSUVmax, which minimizes the confounding factors of visual assessment . Furthermore, the aforementioned prefer using SUVmean of the liver as reference standard, as advanced images reconstruction methods may overestimate SUVmax compared to SUVmean. Another approach using a lesion-to-liver ratio (LLR) of SUVmax in EOT-PET/CT in patients with DLCBL was investigated by Li et al. . They compared the prognostic value of the DS with LLR and reported that a LLR > 1.83 exhibited higher specificity than DS 4-5 indicating superiority in defining patients with need for additional treatment after first line treatment. Others have explored different methods for predicting event-free survival including total metabolic tumor volume (TMTV) in patients with DLBCL and healthy organ uptake in patients with Hodgkin's lymphoma at baseline , the latter exploring the inverse correlation between FDG-uptake in cerebellum and liver and TMTV, which could be explained by a metabolic theft of FDG from large tumor masses leaving less FDG available for healthy organs. Detailed information on, e.g., tumor texture, shape, dissemination patterns or heterogeneity--also known as quantitative radiomics--can also help identifying patients at risk of relapse. In a large group of patients with DLCBL, combining the International Prognostic Index (IPI) with radiomics of metabolic tumor volume (MTV) and dissemination pattern significantly improved identification of patients with risk of relapse compared to IPI alone . However, reconstruction parameters are not the only source of variation in SUV and tumor-to-liver ratios, and especially patient preparation may have an influence. It has been reported that higher blood glucose levels are associated with increased FDG-uptake in liver , and it is recommended that patients are kept euglycemic, especially when the liver is the organ of interest . Moreover, in patients with fatty liver disease, which is an increasing problem worldwide, the hepatic fat content can affect the FDG-uptake in liver, as the hydrophilic FDG does not enter the fat droplets in the hepatocytes, resulting in a dilution of the signal . In addition, the FDG-uptake in liver in patients with overt hypothyroidism is increased compared to euthyroid individuals , whereas the opposite pattern is seen in patients with hyperthyroidism . Lastly, FDG-uptake in liver is also affected both by sex and age . As the Deauville score is a visual score, one could argue that what the eye sees, when looking at the liver is the average value of signal, that is, the liver SUVmean, and not the liver SUVmax. This could in theory mean that a visual evaluation would not be as affected by the change of acquisition times as would a quantitative assessment; however, still we find three patients with change in their (visual) DS due to increased scan duration. The new LAFOV PET/CT systems convey many improvements with possibilities of optimization of image quality or reduction in injected radioactivity or in acquisition time. This is beneficial to many patients, including, among others, patients with malignant lymphomas as they may be young and will undergo several PET/CT scans during their life. Moreover, in children and pregnant women, the possibilities of reducing PET acquisition time or injected activity-dose are remarkable , and in children, the reduced scan duration even allows for scanning without sedation . Furthermore, an unsolved clinical case was clarified within a 1 min scan on a LAFOV PET/CT-scanner, displaying giant cell arteritis and polymyalgia rheumatic , proving the capability of reducing acquisition time considerable. Others report that reducing PET acquisition time to 6 min in a LAFOV PET/CT scanner in patients with malignant melanoma was associated with absolutely no clinical potential consequences in the context of staging or restaging . Even ultrafast PET/CT with acquisition times reduced right down to 30 s have been proven feasible and is especially important for patients with claustrophobia or an inability to lie down . In research, LAFOV PET/CT gives many new opportunities, among others with long-life radionuclides such as Zirconium-89 (89Zr) used in immuno-PET, e.g., with 89Zr-trastuzumab in patients with HER2-positive breast cancer . The increased sensitivity of LAFOV PET/CT and thus a better signal-to-noise ratio enables a substantial reduction in the amount of administered dose rendering the method more operable with regard to radiation exposure . In addition, for short-lived radionuclides, e.g., 15O-H2O with a half-life of ~2 min, the LAFOV PET/CT gives opportunities for studying tracer uptake in all organs of interests, before the tracer decays, due to the long-axial FOV, thus avoiding repeated injection of the tracer. In addition, as one bed position can cover all organs of interest from vertex to mid-thigh, the LAFOV PET/CT gives the possibility of studying whole body dynamic PET without the need for arterial cannulation, in addition to studying connections between different organ systems such as the gut-brain axis . Furthermore, in the future, screening of healthy individuals with an increased risk of cancer might even be feasible. 5. Limitations Our study is a single-center retrospective analysis. Involving more patients and eventually other centers would have given a more robust result. In addition, a large part of our patients was assigned DS 1 with no measurable residual lymphomas, giving us fewer data to analyze. Thus, a validation of our results in a larger trial is recommended. 6. Conclusions The new LAFOV PET/CT systems present many new opportunities both in research and in clinical practice. However, the improvements in signal-to-noise ratio also convey changes that could have clinical implications not to be neglected, including impact on visual scoring systems. Attention should be drawn towards the potential reduction of noise in the liver parenchyma when increasing acquisition times, which can translate into a higher DS and thereby have clinical implications. In our study, the influence on DS was smaller and without clinical implications when using OSEM reconstruction. We believe that further studies are needed to decide which reconstruction method and acquisition time is optimal for assessing treatment response in patients with FDG-avid lymphomas. In our institution, we prefer using OSEM reconstruction of 300 s images for assessing DS to reduce the impact of noise on the DS. In the future, the SUVmean of the liver might be the preferred reference standard for assignment of DS. Supplementary Materials The following supporting information can be downloaded at: Figure S1: SUVmean and SUVmax in mediastinal blood pool; Figure S2: Tumor SUVmax for OSEM+PSF and OSEM; Figure S3: Tumor SUVmax/liver SUVmean ratio remains stable with increasing acquisition time for OSEM+PSF; Figure S4: Tumor SUVmax/liver SUVmean ratio remains stable with increasing acquisition time for OSEM; Table S1: Difference in Deauville score (DS) with OSEM+PSF reconstruction. Click here for additional data file. Author Contributions Conceptualization, B.M.F., A.L. and F.L.A.; methodology, B.M.F., A.L., A.H.D. and K.K.; formal analysis, A.H.D. and K.K.; investigation, A.L.; data curation, N.O. and F.L.A.; writing--original draft preparation, K.K.; writing--review and editing, B.M.F., A.H.D., A.L., N.O., F.L.A. and K.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical review and approval were waived for this study, as the project qualifies as a quality assurance study. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement Data cannot be made publicly available for ethical and legal reasons, as public availability would compromise patient confidentiality, and local (Danish) legislation prohibits public availability of the data. Conflicts of Interest The authors declare no conflict of interest. Figure 1 (A). OSEM+PSF reconstruction for acquisition times of 90 s (a), 300 s (b), and 600 s (c). Noise in liver is visually clearly reduced with longer scan times. (B). OSEM+PSF reconstruction for acquisition times of 90 s (a), 300 s (b), and 600 s (c). Patient with DLCBL; residual lymphoma in mediastinum is marked with a blue circle. Like in Figure 1A, noise in liver is visually clearly reduced with longer scan times with potential impact on visual scoring. Figure 2 SUVmax and SUVmean in liver; differences between acquisition times with and without PSF. SUVmax in liver decreases with increasing acquisition times, whereas SUVmean is stable over time. Figure 3 Tumor SUVmax/liver SUVmax ratio increases with increasing acquisition times due to decreasing SUVmax in liver. Figure 4 COV in liver parenchyma reduces with increasing acquisition time both for series with and without PSF. Two outliers were seen with both reconstruction methods. diagnostics-13-00947-t001_Table 1 Table 1 Clinical characteristics of the patients. Total number of patients 68 Male 38 Female 30 Mean age +- SD 63.4 years +- 16.9 Age range 23-86 years Diagnosis Hodgkin's lymphoma 9 DLBCL 35 Follicular lymphoma 8 T-cell lymphoma 4 B-cell lymphoma 9 Other non-Hodgkin's lymphoma 3 diagnostics-13-00947-t002_Table 2 Table 2 Visual analysis of the Deauville score (DS). OSEM+PSF 90 s OSEM+PSF 300 s OSEM+PSF 600 s OSEM 90 s OSEM 300 s OSEM 600 s DS 1 (N) 23 23 23 23 23 23 DS 2 (N) 17 17 17 20 20 20 DS 3 (N) 7 5 5 3 3 3 DS 4 (N) 8 9 9 9 8 8 DS 5 (N) 13 14 14 13 14 14 Total 68 68 68 68 68 68 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Alberts I. Hunermund J.-N. Prenosil G. Mingels C. Bohn K.P. Viscione M. 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PMC10000540 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050789 cells-12-00789 Article Myeloid-Derived Suppressor Cells (MDSC) in Melanoma Patients Treated with Anti-PD-1 Immunotherapy Tomela Katarzyna 12* Pietrzak Bernadeta 3 Galus Lukasz 4 Mackiewicz Jacek 4 Schmidt Marcin 3 Mackiewicz Andrzej Adam 15 Kaczmarek Mariusz 15 Tiso Natascia Academic Editor 1 Department of Cancer Immunology, Poznan University of Medical Sciences, 61-866 Poznan, Poland 2 Doctoral School, Poznan University of Medical Sciences, 60-812 Poznan, Poland 3 Department of Food Biotechnology and Microbiology, Poznan University of Life Sciences, 60-627 Poznan, Poland 4 Department of Medical and Experimental Oncology, Institute of Oncology, University of Medical Sciences, 60-355 Poznan, Poland 5 Department of Diagnostics and Cancer Immunology, Greater Poland Cancer Centre, 61-866 Poznan, Poland * Correspondence: [email protected] 02 3 2023 3 2023 12 5 78930 12 2022 18 2 2023 27 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Myeloid-derived suppressor cells (MDSC) are a subset of immature myeloid cells with suppressive activity well described in the context of cancer. They inhibit anti-tumour immunity, promote metastasis formation and can lead to immune therapy resistance. In a retrospective study, blood probes of 46 advanced melanoma patients were analysed before the first administration of anti-PD-1 immunotherapy and in the third month of treatment for MDSC, immature monocytic (ImMC), monocytic MDSC (MoMDSC) and granulocytic MDSC (GrMDSC) by multi-channel flow cytometry. Cell frequencies were correlated with response to immunotherapy, progression-free survival (PFS) and lactate dehydrogenase (LDH) serum level. Responders to anti-PD-1 therapy had higher MoMDSC levels (4.1 +- 1.2%) compared to non-responders (3.0 +- 1.2%) (p = 0.0333) before the first administration of anti-PD-1. No significant changes in MDSCs frequencies were observed in the groups of patients before and in the third month of therapy. The cut-off values of MDSCs, MoMDSCs, GrMDSCs and ImMCs for favourable 3-year PFS were established. Elevated LDH level is a negative prognostic factor of response to the treatment and is related to an elevated ratio of GrMDSCs and ImMCs level compared to patients' LDH level below the cut-off. Our data may provide a new perspective for more careful consideration of MDSCs, and specially MoMDSCs, as a tool for monitoring the immune status of melanoma patients. Changes in MDSC levels may have a potential prognostic value, however a correlation with other parameters must be established. melanoma immunotherapy anty-PD-1 MDSC National Science Centre, Poland2017/25/B/NZ5/01949 This work was supported by the National Science Centre, Poland (grant number 2017/25/B/NZ5/01949). pmc1. Introduction Myeloid-derived suppressor cells (MDSC) are described as a heterogeneous population of myeloid cells, immature states that originate from the bone marrow. Although the main characterization of these cells was strongly associated with pathological conditions such as cancer, autoimmune disease and infections due to their strong ability to suppress T-cells and other immune populations, MDSCs are also involved in non-pathological settings such as pregnancy. Their regulatory capacity plays an important role in almost any process in which the immune system is involved . Increased frequency of MDSC is observed in many cancer types, including renal cell carcinoma, non-small cell lung carcinoma (NSCLC), prostate cancer or melanoma . The villainous role of MDSC in cancer development results from immune suppression, tumour angiogenesis, drug resistance, and promotion of tumour metastases . Tumour metastasis is a process in which two main steps can be highlighted. Physical migration of cancer cells from the primary tumour to the distant organ is the first step, after that, cancer cell colonization of the organ begins and develops into metastases. The mechanisms by which MDSCs establish the pre-metastatic microenvironment in distant organs are mostly unknown, however, there is evidence that MDSCs play an essential role in metastasis formation . Otvos et al. in their study presented CSCs selectively MDSC-mediated immune suppression. In cytokine analysis, they revealed secretion by CSCs of multiple factors that promoted this process, including macrophage migration inhibitory factor (MIF), which was produced at high levels by CSCs . Three years after, Tanriover and Aytac reviewed a hypothesis about the bilateral effects of cancer stem cells (CSCs) and MDSCs in cancer development . MDSCs due to their heterogeneity can be divided into two main subtypes: monocytic (Mo/M-MDSCs) and granulocytic (Gr/PMN-MDSCs). However, there is another, third phenotype of MDSCs that lacks granulocyte or monocyte markers and so is considered as early (E-MDSCs) or immature monocytic cells (ImMC) . The immunosuppressive potential of particular cells was established by Nagatani et al. in an in vitro assay. Isolated MoMDSCs as well as GrMDSC released Interleukin 1RA (IL-1RA), and arginase and suppressed T-cell activation, in the presence of tumour cells. In contrast, early MDSCs did not show this immunosuppressive effect suggesting the different properties of these cells . The mechanisms of immune cell suppression are different in Mo and GrMDSCs; this is due to the production and secretion of different substances--nitric oxide synthase 2 (NOS2) by MoMDSCs and reactive oxygen species (ROS) by GrMDSCs. Moreover, suppression of T-cell proliferation is mediated by arginase 1 (ARG1) secretion which causes inhibition of expression of one of the CD3 chains leading to T-cell apoptosis . MDSCs produce cytokines such as transforming growth factor beta (TGF-b) or interleukin 10 (IL-10), prostaglandin E2 (PGE2) and secrete exosomes, all that results in T-cell and NK cell dysfunction but also Treg induction . MDSC can also encourage the spreading of cancer cells through angiogenesis promotion, epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) transition or secretion of tumorigenic factors such as TGFb, hepatocyte growth factor (HGF) and IL-6 . MDSCs are not only linked with cancer progression but also discussed as a factor of development of resistance to immunotherapy . Due to this fact, it is important to monitor changes in cell frequencies in order to recognize the occurrence of secondary resistance to therapy as soon as possible. Melanoma is one of the most fatal types of skin cancer. The number of people diagnosed with and dying from invasive melanoma is growing year by year and the highest mortality rate is referred to patients diagnosed at an advanced stage of the disease . In the last decade, the treatment of metastatic melanoma has improved significantly due to the application of immune checkpoint inhibitors (ICI). The mechanism of those agents is based on blocking co-inhibitory T-cells receptors: cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) or programmed cell death protein 1 (PD-1), respectively, for the immunotherapy agents: anti-CTLA-4 (ipilimumab) or anti-PD-1 (pembrolizumab, nivolumab) monoclonal antibodies which result in activation and proliferation of immune effector cells . Each of the indicated therapies has limited efficacy and secondary resistance develops over time. Ipilimumab treatment was referred to as effective in only 22% and PD-1 inhibitors up to 40-45% of patients with melanoma after 5-10 years of therapy . Due to the growing number of available types of therapeutic agents, as well as the approval of combination therapies, there is an understandable need for establishing the biomarkers of response to particular types of treatment to stratify the patients to the most promising therapy for them, based on scientific evidence. Various potential biomarkers of response to immunotherapy are currently in debate. In our previous paper, we comprehensively review a number of them presented from the tumour or host perspective and their correlation with immunotherapy effectiveness . In this study, we revealed the potential role of one of them: MDSCs including the subtypes of these immunosuppressive cells as a biomarker of response to anti-PD-1 therapy in advanced melanoma patients. The long-term PFS analysis is presented in the context of frequencies of MDSCs. Moreover, we analysed the changes in cell frequencies during the treatment and correlated our results with the serum level of lactate dehydrogenase (LDH), which has been previously related to the occurrence of response to immunotherapy . 2. Materials and Methods 2.1. Study Design, Samples and Ethical Statements In this retrospective study, we analysed the changes in the populations of MDSC in advanced melanoma patients before and during anti-PD-a therapy. Patients who were qualified for treatment with anti-PD-1 antibodies (pembrolizumab or nivolumab) at the Department of Medical and Experimental Oncology of Poznan University of Medical Sciences were invited to participate in the study without additional criteria. The dosage for patients treated with nivolumab was 480 mg infused in cycles every 4 weeks and for patients treated with pembrolizumab, it was 400 mg in cycles every 6 weeks. Samples of peripheral blood were obtained from patients with metastatic melanoma (n = 46) at two time points: at the time of initiation of therapy (baseline, BL) and in the 3 months of therapy (T3). T3 patients treated with nivolumab received 3 cycles of therapy and pembrolizumab, 2 cycles. Patients with infectious diseases were excluded from this study. The evaluation of response to anti-PD-1 treatment was assessed using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. in the third month of therapy. Patients with a partial response to the treatment (PR) and with stable disease (SD) were considered as responders (R), and patients with progressive disease (PD) as non-responders (NR) to anti-PD-1 antibodies in this study. Blood samples from healthy donors (HD) (n = 9) were obtained only once. Peripheral blood was obtained following written consent of participation. The study was approved by the Bioethics Committee of Poznan University of Medical Sciences (study number 402/18). Details on patients' characteristics are summarised in Table 1. 2.2. PBMC Separation and Cryopreservation Blood was collected in vacutainer tubes with an anticoagulant (heparin) (#367874, BD Biosciences). Peripheral mononuclear cells (PBMC) were isolated within 3 h of blood donation by standard gradient centrifugation in a Histopaque 1077 (#SD10771B, Sigma-Aldrich, St. Louis, MO, USA). Cells were cryopreserved using the CTL-Cryo TM ABC Media Kit (#CTLC-ABC, CTL, Cleveland, OH, USA), as described previously and stored in the vapour phase of liquid nitrogen until testing. Samples were frozen for a maximum duration of three years. Thawed and washed twice in phosphate-buffered saline (PBS) solution, the PBMCs pellet was used for further analyses. 2.3. Flow Cytometry for Myeloid-Derived Suppressor Cells and Subsets Cell immunophenotyping was performed by flow cytometry using the following monoclonal antibodies (mAbs): CD33-PE-CyTM7 (#333946, BD Biosciences, Franklin Lakes, NJ, USA), CD11b-APC (#550019, BD Biosciences, Franklin Lakes, NJ, USA), CD45-APC-CyTM7 (#557833, BD Biosciences, Franklin Lakes, NJ, USA) CD66b-FITC (#555724, BD Biosciences, Franklin Lakes, NJ, USA), CD14-PerCP-CyTM5.5 (#562692, BD Biosciences, Franklin Lakes, NJ, USA), HLA-DR-PE (#555812, BD Biosciences, Franklin Lakes, NJ, USA). Antibodies were added to the cytometric tubes containing PBMC pellets resuspended in 100 mL of PBS solution. Samples were mixed gently by vortex and incubated for 15 min at room temperature and protected from light. After this time, 500 mL of cell lysis solution (#349202, BD Biosciences, Franklin Lakes, NJ, USA) was added to the test tubes and the tubes were incubated for the next 10 min, followed by washing with 2 mL of PBS solution. Samples were centrifuged at 1500 rpm for 5 min at room temperature. The supernatants were discarded. This step was repeated twice. The cell pellets were resuspended in 200 mL of PBS solution. The samples were then acquired using a FACS Aria flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA). The obtained results were analysed with the FACS Diva software v. 6.1.3 (Becton Dickinson, Franklin Lakes, NJ, USA), integrated with the cytometer. For each examined antibody, the percentage of positive cells and mean fluorescence intensity (MFI) were determined. 2.4. Progression-Free Survival Analysis and Definition of Cut-Offs Patient progression-free survival (PFS) was measured starting the day of the first administration of anti-PD-1 until the occurrence of progression. As was mentioned before, the evaluation of response to anti-PD-1 treatment was assessed in the third month of therapy. For this reason, the length of PFS for responders exceeds 3 months, while for non-responders it is about 3 months maximum. Since the results of cytometric analyses showed a wide range of results for the group of responders, we determined cut-offs of those parameters and divided the responders into populations above or below the distinguished level, then compared their PFS. Cut-offs were determined to compare responders' PFS in the context of cell levels. The cut-off values were the median cell levels observed in R (MDSC total, GrMDSC and MoMDSC). However, ImMC distribution in R was different, due to the low level of these cells in both analysed groups, therefore the cut-off value for these cells was determined as a median cell level observed in NR group. PFS analysis was performed by using the Kaplan-Meier method and GraphPad Prism Software Prism 9.0 (La Jolla, CA, USA). Survival curves were compared using the log-rank (Mantel-Cox) test. 2.5. Statistical Analysis Statistical analyses were performed with GraphPad Prism Software Prism 9.0 (La Jolla, CA, USA) including parametric and non-parametric tests (Kruskal-Wallis test and t-Student test), p values <= 0.05 were considered statistically significant. 3. Results 3.1. Patients Characteristics The total number of advanced melanoma patients enrolled in the study was 46. Patients qualified for treatment with anti-PD-1 antibodies (pembrolizumab or nivolumab) at the Department of Medical and Experimental Oncology of Poznan University of Medical Sciences consented to participate in this study were enrolled without additional criteria. The mean age of melanoma participants was 63 +- 10.5 years, the youngest patient was 32 and the oldest 92 years old. Nineteen (41.3%) of the enrolled participants were female and twenty-seven (58.7%) were male. Over 95% of patients were diagnosed at the IV stage and only two of them (4.3%) at the III stage of disease. The type of therapy was decided by the patient's oncologist: 23 (50%) of the patients were treated with nivolumab and the other 23 received pembrolizumab. The length of the therapy cycle was various, nivolumab was given every 4 weeks and pembrolizumab was every 3 weeks. For 38 patients (82.6%) it was the first and for 8 (17.4%) the second line of treatment. This study enrolled nine healthy volunteers, four (44.4%) male and five (55.6%) female. The mean age of them was 52 +- 9.4 years, the youngest was 32 and the oldest 67 years old. Patients' and healthy volunteers' characteristics are summarized in Table 1. 3.2. Overall Clinical Response in Melanoma Patients Treated with Anti-PD-1 Immunotherapy Clinical response was evaluated after three cycles of anti-PD-1 therapy. The overall clinical response for both types of anti-PD-1 therapy (nivolumab and pembrolizumab) (n = 46) was as follows: 19 (41.3%) patients had a partial response (PR), 8 (17.4%) had stable disease (SD) and 19 (41.3%) a progressive disease (PD). In this study, we defined responders to anti-PD-1 therapy as patients with a PR and SD (n = 27), and non-responders as patients with PD (n = 19). More than half (58.7%) of patients experienced a progression of melanoma in 1 year. Then, we analysed the overall clinical response based on the type of anti-PD-1 therapy. The same number of patients in this study was treated with nivolumab (n = 23, 50%) or pembrolizumab (n = 23, 50%). Eight (34.8%) of the patients treated with nivolumab had a PR, five (21.7%) SD and ten (43.5%) had a PD. Over half (52.2%) of the patients treated with nivolumab experienced a progression within 1 year. Eleven (47.8%) of the patients treated with pembrolizumab had a PR, three (13.0%) SD and nine (39.1%) a PD to the therapy. We observed that patients treated with pembrolizumab were more likely to experience a progression within 1 year compared to nivolumab (65.2% and 56.5%, respectively). Patients with the clinical benefit of anti-PD-1 treatment statistically later experienced disease progression compared to non-responders. The median progression-free survival (PFS) for responders was 22 +- 9.6 and for non-responders 2.3 +- 0.6 months (p < 0.0001). 3.3. Levels of Circulating ImMC, GrMDSC, MoMDSC and MDSC Total Cells before the First Drug Administration We analysed the level of circulating myeloid-derived suppressor cells (MDSC) and their subpopulations in total peripheral mononuclear cells (PBMCs) of melanoma patients before anti-PD-1 therapy (baseline, BL). The gating strategy is presented in Figure 1. MDSC were defined as CD11b+/HLA-DR-/low/CD33+. Moreover, MDSC subsets were determined as immature MC (ImMC): CD14-/low/CD33low/CD11b+/HLA-DR-/low, monocytic MDSC (MoMDSC): CD14+/CD33high/CD11b+/HLA-DR-/low and granulocytic MDSC (GrMDSC): CD66b+/CD33dim/CD11b+/ HLA-DR-/low. The total MDSC for healthy controls (HC) comprised 5.3 +- 1.4% of all PBMC and for responders (R) and non-responders (NR) to anti-PD-1 therapy before the treatment (baseline, BL), was 7.1 +- 2.6% and 7.8 +- 3.7%, respectively . The levels of ImMC in HC were 0.2 +- 0.1%, the NR group was 0.4 +- 0.3% and the R was 0.6 +- 0.3% which was three-fold higher compared to HC (p = 0.0019). We observed no significant differences in GrMDSC level between analysed groups of patients, though melanoma patients had 3.0 +- 2.0% and 4.7 +- 4.0% (R and NR, respectively), compared to 2.0 +- 1.3% for HC. In contrast, the level of MoMDSC was significantly higher in R (4.1 +- 1.2%) compared to NR patients (3.0 +- 1.2%) (p = 0.0333). Individual dot plots of the data are presented in Figure 2. 3.4. Progression-Free Survival Analysis of Patients Depending on Myeloid-Derived Suppressor Cells Rate Due to the observation of relatively similar myeloid-derived suppressor cell distribution between groups of patients, we determined the cut-offs to differentiate responders with the upper level of analysed cells above the cut-off, and the lower level below the cut-off. We hypothesised a shortened PFS in responders with cell levels in the range of non-responders. We compared PFS between those responder groups and non-responders. The follow-up span allowed us to point out the 1-, 3-year PFS of responders, although most non-responders' PFS did not reach 3 months due to cases of death and patients' response determination at the 3rd month of therapy. Responders to anti- MDSC total below 7.1% had very similar 2-year PFS to patients with MDSC total above the cut-off (78.6 vs. 69.2% and 42.9 vs. 46.2%, respectively), however, the 3-year PFS for this group was 42.9 vs. 20.5% for responders with MDSC total below and above the cut-off, respectively. The lower level of ImMC (below the cut-off of 0.4%) in responders was related to longer PFS compared to ImMC above the cut-off: 78.6 vs. 69.2%, 50 vs. 38.5% and 33.3 vs. 23.1% for 1-, 3-year PFS, respectively. Additionally, the lower level of GrMDSC favoured the longer PFS for responders to anti-PD-1 therapy. Patients with baseline GrMDSC below and above the cut-off (3.0%) reached 76.5 vs. 70% 1-year PFS, 46.3 vs. 30% 2-year PFS and 35.7 vs. 20%, respectively. Analysis of 3-year PFS in responders did not reveal differences greater than 2% between responders below and above 4.1% of MoMDSC. Interestingly, the higher level of MoMDSC favoured the longer 2-year PFS than below the cut-off (58.3 vs. 33.3%) . 3.5. Levels of ImMC, GrMDSC, MoMDSC and MDSC Total Cells in HC Depending on the Age For comparative analyses of cell levels in healthy volunteers and melanoma patients, we use the average values for all nine healthy volunteers, signed as healthy control (HC). However, due to the age variation of the volunteers and the lower average age of them compared to the patients, we conducted an analysis in which we divided HC into two groups: under the age of 50 (the mean age 42 +- 7.75 years) and over 50 (the mean age 63 +- 6.16 years) and compared cell levels between them. We observed higher levels of MoMDSCs in the older (3.92 +- 0.62%) compared to the younger healthy donors (2.45 +- 0.63) (p = 0.0279). The levels of other MDSCs were at a similar level between the analysed groups . 3.6. Levels of Circulating ImMC, GrMDSC, MoMDSC and MDSC Total Cells Following Immunotherapy To determine how the levels of cells and subpopulations changed during therapy with anti-PD-1, we analysed PBMCs of melanoma patients at two time points: before the treatment (BL) and in the third month of therapy (T3). Responders to anti-PD-1 in the third month of therapy had higher levels of MDSC total cells compared to HC, 7.3 +- 2.2% and 5.3 +- 1.4%, respectively (p = 0.0433). The level of ImMC in responders in T3 was significantly higher compared to HC (0.5 +- 0.3 and 0.2 +- 0.1, respectively) (p = 0.0162). In the non-responders' group, we did not notice changes in this particular subpopulation of cells after 3 months of treatment. The level of MoMDSC cells in the third month of therapy in R was 39% higher than observed in HC (4.6 +- 1.3% and 3.3 +- 0.8%, respectively) (p = 0.0394). Interestingly, the level of MoMDSCs in the responders' group in T3 was 35% higher than BL in non-responders (p = 0.0022). During anti-PD-1 therapy, levels of GrMDSC decreased in melanoma patients compared to BL regardless of the occurrence of response to the treatment, nevertheless, these differences were not statistically significant . 3.7. Lactate Dehydrogenase Level in Responders and Non-Responders to Checkpoint Therapy Patients' serum LDH levels were measured before the first administration of anti-PD-1 therapy. We observed a 1.68-fold higher mean LDH concentration in a group of non-responders compared to responders to anti-PD-1 therapy (370.58 +- 194.94 and 220.85 +- 50.26 units/L, respectively, p = 0.0086). Eight of nineteen (42.11%) non-responders had LDH serum levels above 338 units/L (>1.5 x upper limit of normal concentration), and only two of twenty-seven (7.41%) responders exceeded that upper level . 3.8. Analysis of Myeloid-Derived Suppressor Cells in Relation to Elevated LDH Level We re-analysed the obtained results in the context of LDH serum level (not as previously, the occurrence of response to therapy). We compared the levels of circulating MDSCs, ImMCs, MoMDSCs and GrMDSCs between two groups of patients with LDH levels below 338 (n = 36) and above 338 units/L (n = 10). The cut-off value corresponded with a 1.5-fold exceeded norm of this parameter (225 units/L). Both groups included responders and non-responders to anti-PD-1 therapy. We observed no significant differences in the level of circulating MDSCs, MoMDSCs or GrMDSC cells between analysed groups of melanoma patients. However, the level of ImMCs was higher in the group of patients with LDH level > 338 units/L (0.78 +- 0.58%) compared to those with <338 units/L (0.42 +- 0.23%) (p = 0.0285) . Then, we analysed the percentage distribution of GrMDSCs and MoMDSCs in total MDSCs. Patients with LDH level below 338 units/L MDSCs consisted of 39.42 +- 19.07% GrMDSCs and 60.58 +- 18.96% MoMDSCs (p = 0.0002), patients with LDH above 338 units/L MDSCs: 49.28 +- 14.21% GrMDSC and 50.72 +- 14.25% MoMDSC . 4. Discussion In the present study, we evaluated the potential role of myeloid-derived suppressor cells as an immune signature of response to anti-PD-1 therapy in melanoma patients. We performed the analysis not only of the MDSCs but also included three subtypes of these cells. It allowed us to distinguish the relationship between them, indicate the role of each of them in developing a response to immunotherapy and verify the effect of the treatment on cell frequencies. The potential role of MDSCs as a biomarker of response to cancer immunotherapy stays in focus for many reasons. First of all, these inhibitory immune cells have a well-characterized role in modulating the response to cancer immunotherapies. The results of many studies, not only in melanoma, indicate their potential prognostic value. Moreover, the determination of blood parameters is convenient due to easy access and the ability to monitor multiple times during the treatment. In the current study, we observed a higher baseline MoMDSC level in responders to anti-PD-1 therapy, compared to non-responders. In a previous study, melanoma patients treated with anti-CTLA showed a similar frequency of this subset for both groups of patients, moreover, patients with lower MoMDSCs levels were more likely to benefit from this immunotherapy . These observations might result from the differences between types of ICI and require further investigation. The baseline MDSCs frequencies were similar for all melanoma patients, however, non-responders to anti-PD-1 were the group with a higher diversity of levels of these particular cells. Analysis of PFS showed a higher 3-year % for responders with MDSC levels above 7.1%. According to this, a low baseline MDSC level was associated with the highest probability of long-term survival in melanoma patients treated with ipilimumab . Higher CD66+/CD33dim cells frequency was observed for non-responders, and even though this was not a significant value, the same tendency was already reported for melanoma patients treated with various immunotherapies . Lower GrMDSC level was related to a higher 3-year PFS for responders to anti-PD-1. Krebs et al. reported higher 2-year survival rate in OS analysis for non-responders to immunotherapy with a GrMDSCs < 0.5% of PBMCs . Responders to anti-PD-1 had higher ImMCs level compared to non-responders, but we also observed that higher baseline frequencies of these cells were preferable in 3-years PFS analysis. Melanoma patients had a higher MDSCs frequency compared to healthy donors, but this difference is the most evident for immature monocytic cells. It was already reported that melanoma patients have higher MDSC levels than healthy controls, what is more, the frequency of circulating MDSC correlates with the tumour burden and disease stage. So, in patients with more advanced melanoma, but also NSCLC, pancreatic or bladder cancer higher frequencies of MDSC were detected in the peripheral. The level of these immune cells could be considered an indicator of other unfavourable parameters in cancers . However, we should keep in mind that circular MDSCs level may not reflect the exact tumour microenvironment (TME) infiltration status and that GrMDSCs and MoMDSCs in the TME are more suppressive than in peripheral lymphoid organs or peripheral blood. After migration to the tumour, conditions such as hypoxia stimulate the expression and secretion of various immunosuppressive molecules by MDSCs, resulting in a highly suppressive environment in tumours and preventing the rejection of tumours via immune-mediated mechanisms . It was already observed in a mouse model study, that splenic GrMDSCs strongly suppress CD4+ T-cell proliferation while the suppressive effect on CD8+ T cells is less pronounced compared to tumour GrMDSCs. Tumour-derived MoMDSCs produce more both tumour-derived subsets have enhanced arginase activity . Our results present no significant difference in MDSCs frequencies during the treatment regardless of the occurrence of response to the treatment. Similar findings were presented by Meyer et al. in a study of melanoma patients treated with ipilimumab . However, changes in frequencies of immunosuppressive cells following the administration of the immune checkpoint therapy were observed in other studies. Sun et al. in a comprehensive study on 128 advanced melanoma patients treated with immunotherapy described the significant increase in MDSCs in the second and third cycle of anti-PD-1 administration compared to baseline, however, it was not differentiated in the type of response to the treatment . For monitoring the dynamics of changes in peripheral MDSCs frequencies it is crucial to determine blood collection time points. Comparing the results from studies with different time points and other diversities, such as the stage of disease or the type of therapy can be very misleading. During a lifetime, the number of circulating MDSCs increases, and higher levels are observed in elderly people especially older than 65 years . This is due to chronic inflammation and a process of immunosenescence in which immune dysfunction develops during a life span, the resulting occurrence of autoimmune diseases or malignant tumours . In our study, the mean age of healthy volunteers, an informative control providing physiological MDSC levels, was on average 10 years younger than the mean age of patients in this study. This is one of the limitations of the study that we are aware of. Therefore, based on the previous studies suggesting that age-related increase in myelopoiesis can enhance the production of myeloid cells, including MDSCs , we analysed the distribution of MDSCs in smaller groups of healthy participants based on their age: below or above 50 years of age. In the group of older healthy volunteers, we observed higher levels of MDSCs and especially MoMDSCs. This result is only partially consistent with previous studies, in which an increase in the level of GrMDSC was observed with age. This may be due to the mean age differences of the studied groups. Verschoor et al. recruited much older participants (over 61 to 99 years old) , however, our results indicate some differences observed in younger groups of healthy participants which can also be informative. Our observations suggest that the age of participants (both, the control group and patients) should be as similar as possible. LDH is a well-known biomarker for poor outcomes in metastatic melanoma patients. Elevated LDH level is a negative prognostic factor regardless of the type of treatment and has been included in the current version of the AJCC staging system . Previous results have already confirmed this phenomenon, some of them pointed to the exact concentration of elevated LDH levels as a cut-off in the analysis of OS in melanoma patients . A strong correlation between low LDH levels and the occurrence of response to anti-PD-1 therapy was observed in this study. LDH serum level above 1.5 x upper limit of normal concentration correlated with no response to treatment. However, as we present, non-responders to anti-PD-1 had a wide range of LDH concentrations and only less than half of them had LDH levels high above the normal concentration. What is interesting, some of the patients whose LDH concentration exceeded 1.5-fold of the normal level still benefited from anti-PD-1 therapy. Nonetheless, according to previous studies, LDH serum levels before the first administration of anti-PD-1 in the group of responders' therapy were lower compared to non-responders . In this study, we did not observe different MDSC frequencies in PBMCs of patients with elevated LDH (above 1.5 x upper limit of normal concentration), although elevated levels of LDH correlated with poor response to anti-PD-1 therapy. These results are consistent with the results for melanoma patients treated with ipilimumab. Meyer et al. considered possible altered recruitment of MDSCs in the TME of patients with higher serum LDH levels that may remain undetectable in the peripheral blood . We found that an LDH level above the cut-off value was associated with elevated ImMC baseline levels. What is interesting, we did not observe high differences in the level of these particular cells in comparison between responders and non-responders. This may suggest a direction for further research in which this parameter would be investigated as a prognostic factor only in the context of the LDH level. Next, we observed a changed distribution of MDSCs populations (GrMDSCs and MoMDSCs) between groups with LDH levels below or above the cut-off level, regardless of the occurrence of response to therapy. Patients with lower LDH level had higher participation of MoMDSCs than GrMDSCs in the MDSC population, while elevated LDH level was related to a similar ratio of both subpopulations. Elevated levels of LDH as well as GrMDSCs have previously been indicated as negative prognostic factors in response to treatment and OS . As was presented before, melanoma among other solid tumours such as prostate cancer or multiple myeloma presents an expansion of MoMDSC over GrMDSCs in the peripheral, and this is in agreement with our results for the vast majority of our patients . Technical aspects of the study are also worth mentioning. The classification, method of phenotyping and definition of MDSC subpopulations is in debate. Characterization of MDSCs in this study was performed by common MDSCs surface markers: CD11b+, HLA-DR-/low and CD33+. MDSCs subsets were distinguished by specific markers: CD14+ and CD33high for monocytic MDSCs, CD66b+ and CD33dim for granulocytic MDSCs and CD14-/low and CD33low for ImMCs. The protocols used in studies differ, because of the analytic limitations of the cytometer used for work or gating strategies. For example, CD15+ is a popular marker of GrMDSCs, however, CD66+ does not differ in usefulness in this manner . The various protocols are currently in use; however, some certain elements are indicated as affecting the final result. Differences occur at many levels of the test, starting from the type of anticoagulant in the test tubes (heparin, EDTA, sodium citrate), through the method of performing the assay (whole blood or separated PBMC cells, type of reagents for PBMC cell separation), ending with the determination of selected surface markers and gating strategies of marked cells. The multicentre study on the influence of blood collection tube type and cell separation medium shows that certain conditions may increase the concentration of polymorphonuclear MDSCs . In recent years, there has been an increase in interest in MDSC due to its suppressive role in tumour progression. Due to the exponentially growing number of studies in this manner, Bronte et al. presented the recommendation of conditions for the analysis of MDSC . Although the flow cytometric analysis of cryopreserved blood cells is discouraged , it was practised in many studies . In addition, for us, it was not possible to perform analysis on fresh blood samples. To minimize the potential negative effect of cell cryopreservation, we carried out freezing using reagents of the manufacturer that ensures the preservation of cell properties and their surface markers after thawing the sample. Moreover, we have had a positive experience conducting analyses hereby in the past . In conclusion, searching for one particular blood-related parameter as a biomarker of response to melanoma immunotherapy could be ineffective and inconclusive. Especially when the differences in the level of the analysed parameters amount to a few percentages, their biological significance most likely results from the diversity of other parameters (biomarkers), which should be considered together. Due to it, Martens et al. proposed a combined analysis of the baseline frequencies of MDSCs, Tregs, LDH and routine blood counts with clinical characteristics as a tool for predicting outcomes following ipilimumab therapy for advanced melanoma patients . Although our study was retrospective and involved a relatively small number of patients and healthy controls, it suggests that MDSCs frequencies may not directly correlate with the outcome of anti-PD-1 treatment as was suggested before . Our results present new insight into monocytic MDSC as a possible biomarker, however more detailed and mechanistic studies are required to clarify this issue. Author Contributions Conceptualization, K.T. and M.K.; formal analysis, L.G., J.M. and M.K.; funding acquisition, M.S.; investigation, K.T. and B.P.; methodology, K.T. and M.K.; resources, L.G. and J.M.; supervision, M.K.; writing--original draft, K.T. and B.P.; writing--review and editing, M.S., A.A.M. and M.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the Bioethics Committee of Poznan University of Medical Sciences (study number 402/18). Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Representative flow cytometry gating for MDSCs as CD11b+/HLA-DR-/low/CD33+, immature MC (ImMC): CD14-/low/CD33low/CD11b+/HLA-DR-/low, monocytic MDSC (MoMDSC): CD14+/CD33high/CD11b+/HLA-DR-/low and granulocytic MDSC (GrMDSC): CD66b+/CD33dim/CD11b+/HLA-DR-/low. Figure 2 Myeloid suppressor cell (MDSC) levels prior to immunotherapy. Levels of circulating MDSC total, ImMC, GrMDSC and MoMDSC were evaluated as % of PBMC and analysed using Kruskal-Wallis and t-Student tests. Occurrence of the response to anti-PD-1 therapy was evaluated in the third month of treatment. Responders group (R) included patients with PR and SD, non-responders (NR)-PD. For progression-free survival (PFS) analysis of responders and non-responders to immune checkpoint inhibitor (ICI) therapy (log-rank (Mantel-Cox) test was performed. (A) Levels of total MDSC grouped by patients' response to anti-PD-1 therapy and the healthy control. The dashed line marks the median level for R (7.1%). Log-rank (Mantel-Cox) test, PFS analysis p (MDSC total, NR BL vs. R BL < 7.1%) < 0.0001, p (MDSC total, NR BL vs. R BL >= 7.1%) < 0.0001. (B) Levels of immature monocytic cells (ImMC), p (ImMC, HC vs. R BL) = 0.0019. The dashed line marks the median level for NR (0.4%). Log-rank (Mantel-Cox) test, PFS analysis p (ImMC, NR BL vs. R BL <= 0.4%) < 0.0001, p (ImMC, NR BL vs. R BL > 0.4%) < 0.0001, (C) granulocytic MDSC (GrMDSC). The dashed line marks the median level for R (3.0%). Log-rank (Mantel-Cox) test, PFS analysis p (GrMDSC, NR BL vs. R BL < 3.0%) < 0.0001, p (GrMDSC, NR BL vs. R BL >= 3.0%) < 0.0001 and (D) monocytic MDSC (MoMDSC), p (MoMDSC, R vs. NR) = 0.0333. The dashed line marks the median level for NR (4.1%). Log-rank (Mantel-Cox) test, PFS analysis p (MoMDSC, NR BL vs. R BL < 4.1%) < 0.0001, p (MoMDSC, NR BL vs. R BL >= 4.1%) < 0.0001. Data are shown as a mean +- SD, ** p < 0.02, *** p < 0.005. PR, partial response; SD, stable disease; PD, progressive disease. Figure 3 Levels of circula ting ImMC, GrMDSC, MoMDSC and MDSC total cells in HC depending on the age. Healthy volunteers were divided into two groups based on their age: <=50 (the mean age 42 +- 7.75 years) and >50 (the mean age 63 +- 6.16 years) and compared cell levels between them. MDSCs levels were evaluated as % of PBMC. Levels of (A) total MDSC, (B) immature monocytic cells (ImMC), (C) granulocytic MDSC (GrMDSC) and (D) monocytic MDSC (MoMDSC). Data are shown as a mean +- SD, * p <= 0.05. Figure 4 Levels of circulating MDSC total cells, ImMC, GrMDSC and MoMDSC following immunotherapy. Patients' MDSC levels were evaluated as % of PBMC and presented in the context of clinical benefit in two time points: baseline (BL) and third month of anti-PD-1 therapy (T3). Occurring response to therapy was measured in the third month of treatment. Responders group (R) included patients with PR and SD, non-responders (NR)- PD. (A) Levels of total MDSC grouped by patients' response to anti-PD-1 therapy. Levels of (B) immature monocytic cells (ImMC), (C) granulocytic MDSC (GrMDSC) and (D) monocytic MDSC (MoMDSC). Data are shown as a mean +- SD, * p <= 0.05, ** p < 0.02, *** p < 0.005. PR, partial response; SD, stable disease; PD, progressive disease. Figure 5 Levels of circulating MDSC total cells, ImMC, GrMDSC and MoMDSC in the context of serum lactate dehydrogenase level (LDH). Patients' MDSC levels were evaluated as % of PBMC. Patients were divided into two groups based on baseline LDH serum level: below 338 units/L (n = 36) and above 338 units/L (1.5 times elevated normal LDH serum level) (n = 10). The groups included both responders and non-responders to anti-PD-1 therapy. Levels of (A) total MDSC, (B) immature monocytic cells (ImMC), (C) granulocytic MDSC (GrMDSC) and (D) monocytic MDSC (MoMDSC). Correlation between lactate dehydrogenase (LDH) serum level and response to therapy. (E) Mean LDH concentration measured before first administration observed in non-responders was 1.68-fold higher compared to responders to anti-PD-1 therapy (370.58 +- 194.94 and 220.85 +- 50.26 units/L), p = 0.0086. Percentage distribution of GrMDSCs and MoMDSCs in total MDSCs in patients with LDH level < or > 338 units/L (F). Data are shown as a mean +- SD, * p <= 0.05, ** p < 0.02. cells-12-00789-t001_Table 1 Table 1 Demographic and clinical data for advanced melanoma patients included in the study and healthy volunteers. Patients Characteristics Responders (n = 27) Non-Responders (n = 19) Healthy Control (n = 9) Age (years) Mean 61.19 66.16 52 Median 63 66 51 Min, Max 32, 85 38, 92 32, 67 SD 11.44 9.01 9.43 Gender, n (%) Male 15 (55.56) 12 (63.16) 4 (44.44) Female 12 (44.44) 7 (36.84) 5 (55.56) Stage at diagnosis, n (%) III c 2 (7.41) 0 (0.00) IV total 25 (92.59) 19 (100.00) IV M1a 11 (40.74) 2 (10.53) IV M1b 4 (14.81) 3 (15.79) IV M1c 8 (29.63) 10 (52.63) IV M1d 2 (7.41) 4 (21.05) BRAF mutation status, n (%) BRAF - 16 (59.26) 7 (36.84) BRAF + 11 (40.74) 12 (63.16) Immunotherapy Nivolumab 13 (48.15) 10 (52.63) Pembrolizumab 14 (51.85) 9 (47.37) The line of treatment, n (%) I 22 (81.48) 16 (84.21) II 5 (18.52) 3 (15.79) Best overall response, n (%) Partial response (PR) 19 (70.37) 0 (0.00) Stable disease (SD) 8 (29.63) 0 (0.00) Progressive disease (PD) 0 (0.00) 19 (100.00) Progression within 1 year, n (%) Yes 8 (29.63) 19 (100.00) No 19 (70.37) 0 (0.00) Progression-free survival (months) Median 21.97 2.33 SD 9.66 0.64 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000541 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12050989 foods-12-00989 Article The Grade of Dried Jujube (Ziziphus jujuba Mill. cv. Junzao) Affects Its Quality Attributes, Antioxidant Activity, and Volatile Aroma Components Wu Zhengbao Conceptualization Methodology Project administration Funding acquisition 1+ Zhang Shuang Conceptualization Writing - original draft 2+ Liu Lingling Software Writing - review & editing 2 Wang Luyin Validation Visualization 3 Ban Zhaojun Formal analysis Writing - review & editing Supervision Project administration Funding acquisition 2* Pace Bernardo Academic Editor 1 Economic Forest Research Institute, Xinjiang Academy of Forestry Sciences, Urumqi 830000, China 2 Zhejiang Provincial Key Laboratory of Chemical and Biological Processing Technology of Farm Products, School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China 3 Aksu Youneng Agricultural Technology Co., Ltd., Aksu 843001, China * Correspondence: [email protected] + These authors contributed equally to this work. 26 2 2023 3 2023 12 5 98907 1 2023 09 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Jujube (Ziziphus jujuba Mill. cv. Junzao) has attracted a large number of consumers because it is rich in nutrients, such as carbohydrates, organic acids, and amino acids. Dried jujube is more conducive to storage and transportation, and has a more intense flavor. Consumers are affected by subjective factors, and the most important factor is the appearance of the fruit, including size and color. In this study, fully matured jujubes were dried and divided into five grades according to their transverse diameter and jujube number per kilogram. In addition, the quality attributes, antioxidant activities, mineral elements, and volatile aroma components of dried jujube were further analyzed. As the dried jujube grade increased, the total flavonoid content increased, which was positively correlated with the antioxidant activity. The results showed that small dried jujube had a higher total acidity and lower sugar-acid ratio than large and medium dried jujube, thus, large and medium dried jujube had a better flavor than small dried jujube. However, the antioxidant activity and mineral elements of medium and small dried jujube were superior to large dried jujube. From the edible value analysis of dried jujube, medium and small dried jujube were better than large dried jujube. Potassium is the highest among the measured mineral elements, with contents ranging from 10,223.80 mg/kg to 16,620.82 mg/kg, followed by Ca and Mg. Twenty-nine volatile aroma components of dried jujube were identified by GC-MS analysis. The main volatile aroma components were acids including n-decanoic acid, benzoic acid, and dodecanoic acid. The fruit size affected the quality attributes, antioxidant activity, mineral elements, and volatile aroma components of dried jujube. This study provided a piece of reference information for further high-quality production of dried jujube fruit. jujube grade mineral elements antioxidant activity volatile aroma components Forestry Development Subsidy of Xinjiang Uygur Autonomous RegionXJLYKJ-2021-12 Special Fund Project of Xinjiang Jujube Industry Technology SystemXJCYTX-01-02 National Natural Science Foundation of China32172268 Key Research and Development Program of Zhejiang Province2022C04039 Research Project on Postgraduate Teaching Reform of Zhejiang University of Science and Technology2020yjsjg03 Key Laboratory of Storage of Agricultural Products, Ministry of Agriculture and Rural AffairsKf202208 This research was funded by the Forestry Development Subsidy of Xinjiang Uygur Autonomous Region (Grant No. XJLYKJ-2021-12), the Special Fund Project of Xinjiang Jujube Industry Technology System (Grant No. XJCYTX-01-02), the National Natural Science Foundation of China (Grant No. 32172268), the Key Research and Development Program of Zhejiang Province (Grant No. 2022C04039), the Research Project on Postgraduate Teaching Reform of Zhejiang University of Science and Technology (Grant No. 2020yjsjg03), and the Key Laboratory of Storage of Agricultural Products, Ministry of Agriculture and Rural Affairs (Grant No. Kf202208). pmc1. Introduction Jujube (Ziziphus jujuba Mill.) is a plant of the genus Ziziphus in the family Rhamnaceae. It has been cultivated for a long time and has many varieties in China . Jujube contains numerous essential nutrients, vitamins, and minerals, and also has high medicinal value, with anti-obesity , antioxidative , antibacterial, and anti-hepatoma activities . Jujube fruit can be eaten not only fresh, but also dried. In addition, jujube is one of the highest yield dried fruits in China . Junzao, as a kind of dried jujube, has been high-profiled due to its high yield, outstanding tolerance, and excellent taste. In 2018, China produced 8.5 million tons of jujube and nearly 5.47 million tons of dried jujube. Among them, Junzao accounted for about 37% of the total dried jujube production . The flavor of fruit is perceived mainly through taste and smell . Therefore, the combination of sugars, acids, and volatile aroma compounds in jujube forms the flavor of jujube, which affects the quality of jujube fruit. Jujube fruit contains antioxidant compounds that can ameliorate the oxidative damage caused by free radicals. Previous studies have investigated the antioxidant compounds (such as total phenols, total flavonoids, and ascorbic acid) and antioxidant activities of different tissues of jujube . Drying is an effective method to prevent food from microbial decay, and hot air drying and natural sun drying are traditional drying methods . Among them, hot air drying is the most common drying method in food processing, which is easy to operate and is not affected by climate . Dried jujube is more conducive to storage and transportation, and has a more intense flavor, so it is very popular in the market . Moreover, it possesses abundant nutrition elements and is commonly used as a food ingredient and food seasoning all over the world . Shi et al. found that dried Junzao fruit by hot air was rich in phenolic metabolites and had extensive antibacterial activities . In addition, the drying process altered the composition of phenolic compounds and volatile organic compounds with the fruit aroma . Jujube fruit has a unique aroma, which is due to the participation of fruit volatiles in the characterization of fruit aroma characteristics and flavors . The effect of a volatile compound on the final aroma depends on its concentration and the perceived threshold of the specific compound . Previous studies identified aldehydes and acids as the main volatile organic compounds in jujube fruit, such as 2-hexenal, 2-octenal, benzaldehyde, acetic acid, and caproic acid, and low temperature and vacuum drying can retain more volatile aroma components in jujube fruit . Consumers are greatly influenced by subjective factors when purchasing, and fruit appearance phenotype is an important factor, including fruit size, shape, and color . However, there are significant differences in the size of jujube fruit under natural conditions, and the correlation between the size and quality of dried jujube has not been reported. At present, the evaluation standard of jujube fruit grade is mainly based on the transverse diameter, longitudinal diameter, single jujube fruit weight, the number of jujube fruit per kilogram, and so on. In this study, we divided the dried jujube into five grades according to their transverse diameter and the jujube number per kilogram, and analyzed the quality attributes, antioxidant activity, mineral elements, and volatile aroma components. The aim of this study was to understand the components of dried jujube and the quality, antioxidant activity, mineral content, and volatile aroma components of different sized dried jujube at the same maturity. 2. Materials and Methods 2.1. Materials and Treatments Jujube fruits (Ziziphus jujuba Mill. cv. Junzao) were hand-harvested at the commercial maturity stage at a local farm (Xinjiang, China) and dried in a ventilated oven (GZX-9240MBE, Boxun Co., Shanghai, China) at 45 degC for 72 h. According to the transverse diameter and the number of jujube fruits per kilogram, we divided the dried jujube without diseases and pests into five grades (G1, G2, G3, G4, and G5, respectively), as shown in Table 1, and then 500 g of jujube was randomly selected from each group for further experiments. Three biological replications were carried out. 2.2. Shape Index and Moisture The shape index of jujube was the ratio of the longitudinal diameter to the transverse diameter. Moisture content was determined according to the method described by Ajayi et al. with some modifications and was expressed as %. Briefly, 2 g of a jujube fruit sample was dried it in the oven at 105 degC for 2 h, transferred to a desiccator, and cooled for 0.5 h; the above operation was repeated until the sample weight was constant. 2.3. Total Soluble Solids (TSS) and Total Acidity (TA) The jujube fruit were frozen with liquid nitrogen ground to a powder, followed by ultrasonic extraction with distilled water and centrifugation with a centrifuge (5810R, Eppendorf, Hamburg, Germany). TSS was determined by reference to Gao et al. with some modifications. TA was determined based on previously reported methods with some modifications and was expressed as g/kg . 2.4. Total Phenolics (TP) and Total Flavonoids (TF) After grinding in liquid nitrogen, we weighed 1 g of the sample and added 25 mL 75% ethanol solution to the extract for 60 min. The TP content was determined using the Folin-Ciocalteu procedure described by Jimenez-Munoz et al. with some modifications. Absorbance was measured with a microplate reader (Infinite M200 Pro, Tecan, Mannedorf, Switzerland) at 765 nm. The TP concentration in the sample was calculated by drawing a standard curve with the gallic acid standard. The result of the TP was expressed based on the fresh weight as g/kg. The TF content was determined according to the method described by Kou et al. with some modifications. Absorbance was measured with a microplate reader at 500 nm. The TF concentration in the samples was calculated by drawing a standard curve with the rutinum standard and was expressed as g/kg. 2.5. Ascorbic Acid (AsA) The analysis of the AsA content was determined according to the 2,6-dichlorophenolindophenol method described by Kou et al. with some modifications, and was presented in mg/kg. We added 10 mL of 2% oxalic acid solution to 1 g of the jujube fruit sample and ground it to a homogenate. We diluted 5 mL of filtered solution with 2% oxalic acid to 50 mL, took 10 mL of the solution, and titrated it with 0.2 g/L 2,6-dichlorophenolindophenol to the endpoint. The 2,6-dichlorophenolindophenol solution was calibrated with 1 mg/mL AsA standard solution. 2.6. Cyclic Adenosine Monophosphate (cAMP) The content of cAMP was determined with the high performance liquid chromatography method . The 5 g jujube fruit samples were extracted by adding 20 mL of methanol/0.05 mol/L monopotassium phosphate solution (1/4, v/v) for 40 min, and centrifuged. Then, the supernatant was passed through a 0.22 mm water-phase filter membrane, and assessed by high performance liquid chromatograph (Waters e2695, Waters, Milford, MA, USA). 2.7. Antioxidant Activity A sample extract was obtained by weighing 0.3 g of sample powder, adding 10 mL of 50% methanol solution, and extracting for 30 min . The analyses of the free hydrophilic antioxidant fraction were conducted using the 2,2-diphenyl picrylhydrazyl (DPPH) method, whereas the bound antioxidant fraction was analyzed with the ferric reducing antioxidant power (FRAP) method. The result of DPPH radical scavenging activity was expressed as a %. The result of FRAP was expressed as g of Trolox equivalents (TE)/kg. 2.8. Mineral Elements The contents of potassium (K), calcium (Ca), magnesium (Mg), zinc (Zn), and copper (Cu) in jujube fruit were determined by atomic absorption spectrometry (pinAAcle900T, Perkin Elmer, Massachusetts, USA) according to the method described by Mattila et al. with some modifications, and were presented in mg/kg. After digestion, the absorbance of the samples was determined at 766.5 nm, 422.7 nm, 285.2 nm, 213.9 nm, and 324.8 nm by atomization. The absorbance value of mineral elements within the right concentration range was positively proportional to the content of mineral elements, and the content was determined by comparing with the standard series ratio. 2.9. Volatile Aroma Components Analysis The method of analysis and determination of volatile aroma components of dried jujube was modified with reference to Bi et al. . The determination was carried out by solid phase microextraction (SPME, AOC5000, CTC Analytics AG, Zwingen, Switzerland) and gas chromatography-mass spectrophotometry (GC-MS, QP2010Plus, Shimadzu, Tokyo, Japan). The volatile aroma components of the sample were exacted with 50/30 mm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fibers, then used for GC-MS analysis. The injection temperature was 250 degC, the carrier gas was Helium, and the flow rate was 1.0 mL/min. The column temperature was held at 50 degC for 5 min, and the temperature was increased to 150 degC at a rate of 3 degC/min, then increased to 250 degC at a rate of 10 degC/min and maintained at 250 degC for 2 min. 2.10. Statistical Analysis All experiments were performed with three biological replications and three technical replications. Results are presented as mean +- standard deviation (SD). One way analysis of variance (ANOVA) and the Duncan's test were used to determine the differences among the means. Correlations between parameters were examined using the Pearson correlation. Differences were considered statistically significant at p < 0.05. 3. Results and Discussion 3.1. The Quality Attributes of Dried Jujube Fruit shape index is one of the important commodity quality indexes . As the grade of dried jujube increased, the fruit shape index decreased from 1.66 to 1.39 and gradually approached 1, which indicated that the shape of small dried jujube was more circular than that of medium and large dried jujube . After the same drying conditions, the moisture content of the five grades of jujube was different. In Figure 1B, the moisture content of dried jujube in G1 group was the lowest (9.2%), but it had no significant difference with that in the G4 and G5 (p > 0.05) groups. The moisture content of dried jujube seriously affected the quality and shelf life. Our results indicated that compared with medium dried jujube, large and small dried jujube were more favorable for long-term storage, especially the G1 group. TSS and TA content determine the taste and flavor of dried jujube. In Figure 1C, The TSS content of dried jujube ranged from 81.8% to 72.2%, and the smallest jujube (G5) had the lowest TSS content. However, The TA content of dried jujube increased from 4.58 g/kg to 6.45 g/kg with the increase of grade from G1 to G5 . The sugar-acid ratios the of five grades if dried jujube were 169.4%, 178.4%, 165.6%, 118.6%, and 111.9%, respectively. These indicated that dried jujube of G2 have a sweeter texture and a more intense flavor. Li et al. studied the five cultivars of Chinese jujube and pointed out that the sugar content and composition of jujube with different varieties and growing environments vary widely. Chen et al. also proposed that the TSS of fresh Junzao fruit from four different cultivation districts varied from 27.2% to 30.6%. However, the TSS of dried jujube was even higher. The trend of moisture content in dried jujube was similar to that of the TSS content, which indicates that moisture content in dried jujube may be related to TSS content. When the content of TSS is low, and the water in the fruit is easy to spread during drying, and the drying efficiency is high, the moisture content is low. In addition, except the G1 group, the change trend of moisture content in the other four groups was the same as that of fruit shape index, which indicated that the drying effect was related to fruit shape, and the grade of dried jujube affected the moisture content. Khalid et al. found that mandarin fruit size is inversely proportional to TA content, which is similar to our conclusion. Similarly, they pointed out that a lower sugar-acid ratio is recorded in small sized fruit in contrast to medium and large sized fruit . 3.2. TP and TF of Dried Jujube Phenolics are the most common secondary metabolites in fruit, and they influence the quality, color, and flavor of fruit . The composition and content of phenolics in fruit varies with the variety, texture, and processing of fruit. In Figure 2A, the TP content of dried jujube in different grades was similar, ranging from 8.54 g/kg to 9.14 g/kg. Wojdylo et al. found 25 phenolic compounds in Spanish jujube, and total phenolic compounds (especially polymer proanthocyanin and quercetin derivatives) and ascorbic acid contributed significantly to the antioxidant capacity of jujube. The growth and development of jujube affected the TP content . The maturity of different graded jujube was the same, which may be the reason for the little difference in the TP content. Barbagallo et al. analyzed the TP content of grapes with different fruit size and found that the TP content decreased with grape weight and was affected by environment, region, climate, and other factors, thus, the phenomenon of TP content variation in this experiment could be explained. Flavonoids are phenolic compounds that are widely found in fruits and are particularly important for human health . Jujube is rich in flavonol glycosides composition, and the difference in variety and maturity can lead to differences in the flavonoid content in jujube . In Figure 2B, the TF content of dried jujube increased from 2.95 g/kg to 6.14 g/kg with the increase in grade of G1 to G5. These results indicated that fruit enlargement accelerated the consumption and decreased the accumulation of flavonoids. Barbagallo et al. pointed out that the TF amount increased with grape size, which was similar to our results. TP and TF contents of fruit in different parts was also different. Zhang et al. found that the peel of all jujube species had the highest antioxidant capacity, reflecting the highest levels of total phenols, flavonoids, and anthocyanins in peel. 3.3. AsA and cAMP of Dried Jujube AsA has the effect of antioxidation and scavenging of free radicals, which widely exists in fruit and vegetables, and has a high content in jujube . In Figure 2C, the AsA content of dried jujube increased gradually from G1 to G3, and then decreased. AsA content ranged from 51.71 mg/kg to 90.80 mg/kg, which was higher than that of pear-jujube at different ripening stages, as previously reported. The AsA content of G3 was the highest, being 1.76 times that of G1. This conclusion was partly similar to the findings of Wu et al. , who found that the AsA content decreased during pear-jujube ripening. In addition, the results of AsA and moisture were similar, which may be related to the fact that AsA is a water-soluble and heat-sensitive compound . cAMP is a physiologically active substance involved in the regulation of material metabolism and biological functions in cells, and plays an important role in the regulation of sugar, fat metabolism, nucleic acids, and protein synthesis. In Figure 2D, the cAMP content of dried jujube increased gradually from G1 to G4, but the cAMP content of G5 decreased. The cAMP content in different grades of dried jujube reached the peak at G4 (363.55 mg/kg), and the cAMP content of G1 of dried jujube was the lowest (210.26 mg/kg). The cAMP content of dried jujube was similar to that of moisture content and AsA content, except at the highest point. The cAMP content of jujube fruit was higher than that of most fruits . There were significant differences in the cAMP content of different cultivars and cultivation areas in jujube fruit. Zhang et al. pointed out that many factors, such as sample collection period and extraction method, would affect the content of cAMP, which might lead to the results of our experiment. Chen et al. found that the cAMP content of fresh Junzao jujube in the Kashi district was the lowest (50.31 mg/kg), while that in the Aksu district was 87.90 mg/kg. Different processing methods can also affect the cAMP content of jujube. Previous studies have shown that the cAMP content of dried jujube increases while that of steamed jujube decreases . 3.4. The Antioxidant Activity of Dried Jujube Free radicals induce the oxidation of lipids, proteins, and DNA, which can lead to adverse events, thus, free radical scavenging is one of the important functions of antioxidants . We quantified the antioxidant activity of five grades of dried jujube by DPPH and FRAP methods. In Figure 2E, the DPPH radical scavenging activity of dried jujube increased with grades, and the difference between groups G3 and G4 was more pronounced, with a 7.84% increase in DPPH radical scavenging activity in G4. The DPPH radical scavenging activities of G4 and G5 were higher than those of the other three groups. In Figure 2F, the FRAP of dried jujube also increased with grades, and the FRAP of G1 was the lowest in the five grades at 0.43 g TE/kg. These results indicated that the small dried jujube had a higher antioxidant activity measured from the DPPH method, and medium and small dried jujube had higher antioxidant activity measured from the FRAP method. The change trend was similar to the TF content, and the accumulation of flavonoids increased the antioxidant activity of dried jujube. This conclusion was similar to Li et al. , who point out that DPPH radical scavenging activity and FRAP were positively correlated with rutin and other flavonoid metabolites through correlation analysis. 3.5. The Mineral Elements of Dried Jujube The results of the analysis of the mineral contents of dried jujube were summarized in Table 2. Potassium regulates intracellular osmotic pressure and the acid-base balance of body fluids, and is also involved in the metabolism of intracellular sugars and proteins. In addition, potassium was the predominant mineral in the five grades of dried jujube. The K contents ranged from 10,223.80 mg/kg to 16,620.82 mg/kg, and the richest source of K in this study was G5. Calcium helps to lower blood pressure, regulate the nervous system, and participate in muscle contraction. From the statistical analysis, the Ca content of the five grades of dried jujube were significantly different (p < 0.05), and the richest source of Ca in this study also was G5. Magnesium is an activator of enzymes, which participates in the normal life activities and metabolic processes of organisms. The Mg contents ranged from 206.35 mg/kg to 253.37 mg/kg, and the richest source of Mg in this study was G4. The five grades of dried jujube contained relatively low amounts of Zn and Cu, which are important because Zn is nutritionally essential for all organisms and Cu participates in numerous enzyme-catalyzed oxidation-reduction reactions and processes . Regarding Zn content, the highest value was found in G3 (4.10 mg/kg), followed by G5 (3.75 mg/kg), and G4 (3.63 mg/kg). There were also significant differences in the Cu content of the five grades of dried jujube, in which the highest Cu content was found in G5 (3.06 mg/kg) and the lowest Cu content was found in G3 (1.70 mg/kg). The content of mineral elements is influenced by many factors, such as jujube cultivar, development stage, soil, and climate in the cultivation area. Li et al. measured the mineral content of five cultivars of jujube in their experiment, and found that the Ca content of Junzao jujube (1179.88 mg/kg) was higher than that of the other four cultivars of jujube (Jinsixiaozao, Yazao, Jianzao and Sanbianhong), but Mg content was the lowest (246.12 mg/kg). 3.6. The Correlation Analysis of Dried Jujube In order to understand more fully the correlation between the quality attributes, antioxidant activity, and mineral elements, we carried out a correlation analysis of the above indicators. In Table 3, a significant positive correlation between shape index and TSS content was noted in our results (R2 = 0.526, p < 0.05). However, the shape index was negatively correlated with some indicators (TA, R2 = -0.777, p < 0.01; TF, R2 = -0.808, p < 0.01; DPPH, R2 = -0.720, p < 0.01; K, R2 = -0.640, p < 0.05; Ca, R2 = -0.748, p < 0.01; Zn, R2 = -0.569, p < 0.05; Cu, R2 = -0.710, p < 0.01). The results showed that TSS content increased with the increase in the ratio of the longitudinal diameter to transverse diameter, but the antioxidant activities and mineral contents decreased. Therefore, the taste of large dried jujube is better than that of small dried jujube, but the quality of small dried jujube is better than that of large dried jujube, which is similar to previous studies . Barbagallo et al. pointed out that the fruit composition varies greatly with the fruit size, and the influence of fruit size should be considered, as well as the influence of other environmental factors, on fruit composition. Our results indicated a positive correlation between antioxidant activity and TF (DPPH, R2 = 0.912, p < 0.01; FRAP, R2 = 0.575, p < 0.05), which was consistent with other reported results . DPPH radical scavenging activity also was highly positively correlated with TA, cAMP, and mineral element contents (TA, R2 = 0.982, p < 0.01; cAMP, R2 = 0.597, p < 0.05; K, R2 = 0.921, p < 0.01; Ca, R2 = 0.647, p < 0.01; Mg, R2 = 0.593, p < 0.05; Zn, R2 = 0.619, p < 0.05; Cu, R2 = 0.697, p < 0.01). In addition, the FRAP was positively correlated with moisture, AsA, cAMP, and some mineral element contents (moisture, R2 = 0.674, p < 0.01; AsA, R2 = 0.658, p < 0.01; cAMP, R2 = 0.786, p < 0.01; Mg, R2 = 0.654, p < 0.01; Zn, R2 = 0.845, p < 0.01). 3.7. The Volatile Aroma Components of Dried Jujube The main volatile aroma components of dried jujube are shown in Table 4; among these, the highest volatile aroma components of dried jujube were acids (n-decanoic acid, benzoic acid, and dodecanoic acid). In Table 4, the relative content of benzoic acid, n-decanoic acid, dodecanoic acid, benzoic acid, and octanoic acid were the highest among the five grades of dried jujube (up to 17.19%, 16.37%, 18.85%, 22.63%, and 17.94%, respectively). The relative content of 2-octenoic acid, methyl (Z)-9-hexadecenoic acid, methyl dodecanoic acid, and methyl myristoleate of the G2 dried jujube reached the maximum in the five grades. Among the five grades of dried jujube, the relative contents of five volatile aroma components (1-octadecene, dibutyl phthalate, dodecanoic acid, hydrocinnamic acid, octadecane) reached a peak in the G3 dried jujube, and the relative contents of the other five volatile aroma components (acetic acid, benzaldehyde, heptanoic acid, nonanoic acid, and octanoic acid) were the highest in the G5 dried jujube. In addition, the relative contents of 6,10,14-trimethyl-2-pentadecanone and benzoic acid of the G4 dried jujube were the highest in the five grades. This was similar to the previous conclusion . However, Wang et al. identified 31, 31, 32, and 32 volatile aroma components from Tangzao, Muzao, Lizao, and Qingrunhongzao, respectively, and pointed out that aldehydes were the main volatile aroma components in jujube. Bi et al. found that after drying, the relative content of aldehydes in jujube decreased, but the content of alkanes and ketones increased. The volatile aroma components of dried jujube are very complex. Spadafora et al. pointed out that many factors, such as fruit maturity, storage temperature, and processing process, can affect the volatile aroma components. These may account for the results. 4. Conclusions Consumers are influenced by subjective factors when buying dried jujube, and the most important factor is the fruit appearance. This study found that fruit size had effects on quality attributes, antioxidant activity, mineral elements, and volatile aroma components of dried jujube. From the flavor analysis of dried jujube, the flavor of large and medium dried jujube was better than that of small dried jujube. The correlation analysis showed that the TF content of dried jujube was positively correlated with antioxidant activity, and AsA content was positively correlated with cAMP content. However, from the analysis of edible value, medium and small dried jujube had a higher antioxidant capacity. Potassium, as an essential element in organisms, was the highest of the measured mineral elements of dried jujube. The volatile aroma components of dried jujube were complex, among which the relative content of acid was the highest. This study provided a reference for the evaluation of dried jujube fruit quality and the improvement of grading standards, which aimed to improve the commercial value and market competitiveness of dried jujube. Author Contributions Conceptualization, Z.W. and S.Z.; Methodology, Z.W.; Software, L.L.; Validation, L.W.; Formal Analysis, Z.B.; Writing--Original Draft Preparation, Z.W. and S.Z.; Writing--Review & Editing, L.L. and Z.B.; Visualization, L.W.; Supervision, Z.B.; Project Administration, Z.W. and Z.B.; Funding Acquisition, Z.W. and Z.B. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Data is contained within the article. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The quality attributes of dried jujube. The analysis of (A) shape index, (B) moisture, (C) total soluble solids (TSS), and (D) total acidity (TA) of dried jujube. The dried jujubes were arranged in the order from large to small, which were G1, G2, G3, G4, and G5 groups, respectively. Data are expressed as means +- standard deviation (SD) from three replications. Means with different letters are significantly different (p < 0.05). Figure 2 The contents of (A) total phenolics (TP), (B) total flavonoids (TF), (C) ascorbic acid (AsA), (D) cyclic adenosine monophosphate (cAMP), (E) 2,2-diphenyl picrylhydrazyl (DPPH) radical scavenging activity, and (F) ferric reducing antioxidant power (FRAP) of dried jujube. The dried jujube were arranged in the order from large to small, which were G1, G2, G3, G4, and G5 groups, respectively. Data are expressed as means +- standard deviation (SD) from three replications. Means with different letters are significantly different (p < 0.05). foods-12-00989-t001_Table 1 Table 1 The grading standard of dried jujube. Grade G1 G2 G3 G4 G5 Transverse diameter (mm) >=32 >=30, <32 >=28, <30 >=26, <28 >=24, <26 Number of jujube per kilogram <=70 71-85 86-105 106-125 126-150 foods-12-00989-t002_Table 2 Table 2 The mineral element contents of dried jujube. Grades Contents (mg/kg) K Ca Mg Zn Cu G1 13,485.13 +- 393.24 b 149.89 +- 5.45 d 206.35 +- 9.22 b 0.88 +- 0.03 d 1.97 +- 0.06 b G2 10,223.80 +- 648.03 a 174.40 +- 11.05 c 222.01 +- 14.06 b 2.30 +- 0.14 c 1.80 +- 0.12 bc G3 12,308.21 +- 701.14 b 196.10 +- 11.15 b 225.97 +- 13.00 b 4.10 +- 0.23 a 1.70 +- 0.09 d G4 15,442.79 +- 895.98 a 177.62 +- 10.33 bc 253.37 +- 14.63 a 3.63 +- 0.21 b 2.01 +- 0.12 b G5 16,620.82 +- 788.23 a 308.67 +- 14.64 a 216.99 +- 10.31 b 3.75 +- 0.17 b 3.06 +- 0.15 a The dried jujube were arranged in the order from large to small, which were G1, G2, G3, G4, and G5 groups, respectively. Data are expressed as means +- standard deviation (SD) from three replications. Means with different letters are significantly different (p < 0.05). foods-12-00989-t003_Table 3 Table 3 The correlation analysis of dried jujube. Shape Index Moisture TSS TA AsA cAMP TP TF DPPH FRAP K Ca Mg Zn Cu Shape index 1 Moisture 0.236 1 TSS 0.526 * 0.776 ** 1 TA -0.777 ** -0.284 -0.491 1 AsA -0.202 0.48 0.056 0.288 1 cAMP -0.335 0.344 -0.068 0.537 * 0.811 ** 1 TP -0.401 0.318 0.269 0.697 ** 0.396 0.512 1 TF -0.808 ** -0.081 -0.485 0.928 ** 0.499 0.611 * 0.638 * 1 DPPH -0.720 ** -0.249 -0.434 0.982 ** 0.405 0.597 * 0.734 ** 0.912 ** 1 FRAP -0.374 0.674 ** 0.144 0.377 0.658 ** 0.786 ** 0.502 0.575 * 0.36 1 K -0.640 * -0.525 * -0.542 * 0.899 ** 0.184 0.29 0.581 * 0.773 ** 0.921 ** -0.011 1 Ca -0.748 ** -0.065 -0.349 0.709 ** 0.159 0.106 0.528 * 0.817 ** 0.647 ** 0.352 0.621 * 1 Mg -0.219 0.337 0.16 0.535 * 0.585 * 0.898 ** 0.679 ** 0.468 0.593 * 0.654 ** 0.31 -0.013 1 Zn -0.569 * 0.373 -0.204 0.595 * 0.838 ** 0.804 ** 0.501 0.822 ** 0.619 * 0.845 ** 0.357 0.573 * 0.546 * 1 Cu -0.710 ** -0.4 -0.448 0.769 ** -0.152 -0.077 0.504 0.716 ** 0.697 ** 0.028 0.780 ** 0.898 ** -0.059 0.258 1 TSS, Total soluble solids; TA, total acidity; TP, total phenolics; TF, total flavonoids; AsA, ascorbic acid; cAMP, cyclic adenosine monophosphate; DPPH, 2,2-diphenyl picrylhydrazyl radical scavenging activity; FRAP, ferric reducing antioxidant power. * p < 0.05; ** p < 0.01; ns, not significant. foods-12-00989-t004_Table 4 Table 4 The analysis of volatile aroma compounds of dried jujube. Compounds Relative Content (%) Evolution G1 G2 G3 G4 G5 1-Octadecene 0.79 +- 0.04 cd 1.05 +- 0.13 bc 2.18 +- 0.15 a 1.29 +- 0.33 b 0.61 +- 0.1 d 1-Pentadecene 0.35 +- 0.08 a 0.4 +- 0.01 a 0.2 +- 0.04 b 0.37 +- 0.06 a 0.33 +- 0.03 a 2-Octenoic acid 2.66 +- 0.04 b 3.31 +- 0.11 a 2.36 +- 0.32 d 2.51 +- 0.01 bc 2.66 +- 0.03 b 2-Pentadecanone, 6,10,14-.59 +- 0.04 c 0.96 +- 0.05 b 0.95 +- 0.08 b 1.26 +- 0.2 a 0.52 +- 0.22 c 2-Undecanone, 6,10-.85 +- 0.19 b 1.16 +- 0.08 a 0.37 +- 0.13 c 0.91 +- 0.13 ab 0.99 +- 0.17 ab 9-Hexadecenoic acid, methyl ester, (Z)- 0.40 +- 0.05 c 1.30 +- 0.13 a 0.76 +- 0.08 b 0.19 +- 0.04 d 0.20 +- 0.08 d Acetic acid 8.13 +- 1.06 b 6.38 +- 0.8 c 5.23 +- 0.68 cd 4.66 +- 0.87 d 10.88 +- 0.87 a Benzaldehyde 0.52 +- 0.05 b 0.39 +- 0.05 c 0.28 +- 0.07 c 0.38 +- 0.03 c 1.37 +- 0.12 a Benzoic acid 17.19 +- 2.47 b 13.23 +- 0.29 c 17.07 +- 1.13 b 22.63 +- 1.49 a 0 +- 0 d Benzoic acid, 2-ethylhexyl ester 0.55 +- 0.12 a 0 +- 0 b 0.66 +- 0.24 a 0.43 +- 0.14 a 0.15 +- 0.06 b Decanoic acid, ethyl ester 0.71 +- 0.11 b 0.92 +- 0.03 b 1.39 +- 0.3 a 1.42 +- 0.24 a 0 +- 0 c Dibutyl phthalate 0.30 +- 0.03 b 0.34 +- 0.04 b 1.12 +- 0.34 a 0.22 +- 0.06 b 0.12 +- 0.05 b Dodecanoic acid 11.99 +- 1.23 bc 12.25 +- 1.3 b 18.85 +- 2.37 a 8.72 +- 1.69 cd 7.83 +- 2.15 d Dodecanoic acid, methyl ester 1.82 +- 0.52 b 2.38 +- 0.11 a 0.67 +- 0.36 c 1.39 +- 0.12 b 1.33 +- 0.09 b Ethyl 9-hexadecenoate 1.33 +- 0.13 b 2.02 +- 0.18 a 1.73 +- 0.24 a 0.27 +- 0.07 c 0.40 +- 0.15 c Heptadecane 0.57 +- 0.17 a 0 +- 0c 0.70 +- 0.13 a 0.51 +- 0.12 ab 0.31 +- 0.04 b Heptanoic acid 5.78 +- 0.52 bc 4.8 +- 0.21 c 2.55 +- 0.57 d 7.66 +- 0.52 b 10.17 +- 2.21 a Hexadecane 0.60 +- 0.15 b 0.61 +- 0.02 b 0 +- 0 c 1.11 +- 0.14 a 1.36 +- 0.24 a Hexadecane, 2,6,10,14-.54 +- 0.14 ab 0 +- 0 c 0.73 +- 0.20 a 0.50 +- 0.21 ab 0.26 +- 0.07 bc Hexadecanoic acid, methyl ester 0.26 +- 0.02 ab 0.30 +- 0.02 a 0.23 +- 0.04 bc 0.18 +- 0.03 c 0.06 +- 0.02 d Hexanoic acid 6.75 +- 0.44 ab 5.73 +- 0.44 b 2.88 +- 0.38 c 5.75 +- 0.55 b 7.56 +- 1.66 a Hydrocinnamic acid 0.76 +- 0.08 b 0.76 +- 0.02 b 2.03 +- 0.4 a 0.83 +- 0.05 b 0.50 +- 0.04 b Methyl myristoleate 0.90 +- 0.08 b 1.47 +- 0.1 a 0.47 +- 0.08 c 0.33 +- 0.06 cd 0.32 +- 0.09 d n-Decanoic acid 14.35 +- 0.69 ab 16.37 +- 0.71 ab 16.57 +- 1.69 a 13.28 +- 0.83 b 15.10 +- 2.83 ab Nonanoic acid 1.65 +- 0.05 b 1.47 +- 0.03 c 0.91 +- 0.07 d 1.72 +- 0.06 b 1.87 +- 0.04 a Octadecane 0.47 +- 0.09 b 0 +- 0 d 0.68 +- 0.06 a 0.41 +- 0.1 b 0.21 +- 0.06 c Octanoic acid 4.55 +- 1.04 b 5.24 +- 0.52 b 1.91 +- 0.39 c 5.52 +- 0.44 b 17.94 +- 0.28 a Pentadecane 0.61 +- 0.09 a 0.48 +- 0.02 ab 0.44 +- 0.13 b 0.46 +- 0.08 ab 0.55 +- 0.02 ab Pentadecane, 2,6,10,14-.63 +- 0.21 a 0 +- 0 b 0.68 +- 0.28 a 0.49 +- 0.19 a 0.33 +- 0.15 ab The dried jujube were arranged in the order from large to small, which were G1, G2, G3, G4, and G5 groups, respectively. 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PMC10000542 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050887 diagnostics-13-00887 Article Syndrome Pattern Recognition Method Using Sensed Patient Data for Neurodegenerative Disease Progression Identification Anjum Mohd Conceptualization Methodology Software Validation Writing - original draft 1 Shahab Sana Conceptualization Methodology Software Validation Resources Data curation Writing - original draft Writing - review & editing Visualization 2 Yu Yang Validation Formal analysis Writing - review & editing Visualization 3* Orozco-Arroyave Juan Rafael Academic Editor 1 Department of Computer Engineering, Aligarh Muslim University, Aligarh 202001, India 2 Department of Business Administration, College of Business Administration, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia 3 Centre for Infrastructure Engineering and Safety (CIES), University of New South Wales, Sydney, NSW 2052, Australia * Correspondence: [email protected] 26 2 2023 3 2023 13 5 88713 1 2023 22 2 2023 24 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Neurodegenerative diseases are a group of conditions that involve the progressive loss of function of neurons in the brain and spinal cord. These conditions can result in a wide range of symptoms, such as difficulty with movement, speech, and cognition. The causes of neurodegenerative diseases are poorly understood, but many factors are believed to contribute to the development of these conditions. The most important risk factors include ageing, genetics, abnormal medical conditions, toxins, and environmental exposures. A slow decline in visible cognitive functions characterises the progression of these diseases. If left unattended or unnoticed, disease progression can result in serious issues such as the cessation of motor function or even paralysis. Therefore, early recognition of neurodegenerative diseases is becoming increasingly important in modern healthcare. Many sophisticated artificial intelligence technologies are incorporated into modern healthcare systems for the early recognition of these diseases. This research article introduces a Syndrome-dependent Pattern Recognition Method for the early detection and progression monitoring of neurodegenerative diseases. The proposed method determines the variance between normal and abnormal intrinsic neural connectivity data. The observed data is combined with previous and healthy function examination data to identify the variance. In this combined analysis, deep recurrent learning is exploited by tuning the analysis layer based on variance suppressed by identifying normal and abnormal patterns in the combined analysis. This variance from different patterns is recurrently used to train the learning model for maximising of recognition accuracy. The proposed method achieves 16.77% high accuracy, 10.55% high precision, and 7.69% high pattern verification. It reduces the variance and verification time by 12.08% and 12.02%, respectively. neural data neurodegenerative disease pattern recognition recurrent learning Princess Nourah bint Abdulrahman University ResearchersPNURSP2023R259 This research was supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R259), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. pmc1. Introduction Neurodegenerative diseases (NDDs) are a disorder resulting from the progressive loss of function of selective neurons in the nervous system. As a result, one of the most significant impacts of these diseases is on motor function, which progressively declines . In some cases, the motor function may be affected by paralysis. Therefore, the progressive decline of motor function is one of the major characteristics of neurodegenerative diseases . NDDs are challenging and complex to understand as they involve determining the precise causes of these diseases, identifying optimal approaches for early detection, and developing the most effective treatments. The causes of NDDs are not well understood, but many factors are believed to contribute to the development of these conditions . Some researchers believe genetics play a major role in developing NDDs . However, others believe that environmental factors , such as exposure to toxins or traumatic brain injury , abnormal medical conditions and ageing contribute to the development pf NDDs. Other concerns are the efficacy of different treatment approaches, with some researchers advocating for more pharmaceutical interventions and others focusing on lifestyle changes and alternative therapies . Many issues exist related to the diagnostic criteria used to identify these diseases. There are established clinical criteria for many NDDs, such as Alzheimer's disease (AD), Amyotrophic Lateral Sclerosis, and Multiple Sclerosis . Some researchers believe that these criteria are not sensitive enough and may miss early-stage disease . Ongoing research concerns the best methods for tracking disease progression and developing effective treatments . There are also questions regarding the reliability and validity of various diagnostic tools, such as biomarkers and imaging techniques used to track disease progression. Identifying and monitoring the progression of NDDs is necessary for healthcare systems . Early detection and accurate tracking of NDDs can lead to more effective treatments and improved patient outcomes . It can also help healthcare providers better understand the disease and develop more effective strategies for managing and preventing it . Various techniques and methods are used to identify NDDs . Some of these techniques include brain imaging , cerebrospinal fluid analysis , genetic testing , and cognitive assessments . Each method has its strengths and weaknesses and is often used in combination with others to increase the accuracy and reliability of the diagnosis. Additionally, machine learning (ML) algorithms and artificial intelligence (AI) models are being developed to aid in the identification and progression monitoring of these diseases . A monitoring system is used to identify the progression of the NDD by monitoring patients' conditions and behavioural features. This system detects pathological conditions and collects data necessary for identifying and progressing NDDs. . This system includes monitoring a patient's cognitive and physical abilities , as well as using medical imaging techniques such as magnetic resonance imaging (MRI) or positron emission tomography scans to detect changes in the brain . In addition, biomarkers such as levels of certain proteins or other molecules in the blood or cerebrospinal fluid can be used to indicate the presence or progression of a NDD . A feature space regression model is employed to identify the disease. This model detects spatial and temporal features, increasing clinical accuracy in further processes . Additionally, the model reduces the time and energy consumption in the disease identification process and improves the performance and effectiveness of prediction and identification . Pattern recognition is one of the techniques used to identify specific patterns associated with NDD. By analysing patterns in patient data, such as changes in behaviour, cognitive function, and other physiological factors, healthcare professionals detect the presence and progression of NDD. ML algorithms and other advanced analytical tools are effectively used to help with pattern recognition and the identification of NDD . These algorithms analyse large amounts of data and identify patterns not easily discernible by human observation. These techniques improve the overall accuracy and efficiency of the diagnosis process for NDD . The progression pattern recognition method is utilised to detect NDD by identifying spatial and temporal features of the disease that provide important information for the detection process. To improve the accuracy of predictive models for the risk of NDDs, authors in employ a recurrent neural network with long-short time memory to incorporate temporal information from patients' medical records into the models. This method involves analysing how a patient's medical history changes over time and identifying patterns or trends that can be used to predict future disease risks. By incorporating this temporal information, the models can provide more accurate and personalised patient predictions and improve the diagnosis process's performance . Sequential pattern mining is used to identify relevant patterns and features associated with NDDs . Analysing sequential data collected from individuals over time, such as sensor data, medical records or behavioral data, provides valuable insights into the underlying dynamics of diseases . Disease progression patterns contain important features that provide useful information for detection, prediction and diagnosis. Sequential pattern mining can be used to identify key progressive patterns of behavioural deficits in individuals with NDD . Sequential pattern mining helps improve the diagnosis process's accuracy by providing supporting evidence for clinical decision-making . ML methods and algorithms are increasingly being used to detect and predict NDDs. These methods effectively analyse patient data, such as medical imaging, genetic data, clinical records, or behavioural data, to identify patterns or features indicative of an NDD . This analysis can include identifying abnormal protein deposits in the brain, changes in brain structure or function, or genetic markers associated with a higher risk of developing NDD . These methods improve the accuracy of pattern recognition, increasing the performance and feasibility of the diagnosis process . These methods have revolutionised the diagnosis and treatment of these diseases in several ways, such as early detection and diagnosis, prediction of disease progression, drug discovery, personalised treatment, monitoring disease progression and treatment effectiveness. Nowadays, deep learning (DL), a subset of ML that involves artificial neural networks, is also increasingly used in the detection and prediction of NDDs . DL algorithms analyse large and complex datasets, such as medical imaging data, to identify subtle patterns or features of these diseases. Convolutional neural networks are the most commonly used algorithm in DL for pattern recognition. These algorithms utilise image data to learn patterns and apply classification techniques to classify patterns based on types and features . They detect spatial and temporal features from the database, maximising the feasibility of the recognition process . Overall, ML methods and algorithms are a promising approach to the detection and prediction of NDDs, and have the potential to improve the accuracy and speed of diagnosis and facilitate the development of new treatments and therapies . Early and precise detection and timely commencement of appropriate therapies, such as medication or behavioral interventions, are critical for improving patient outcomes and quality of life in NDDs . This detection requires an intensive analysis of a range of clinical data, which can be facilitated by data-driven approaches such as ML. This clinical data must be carefully collected and analysed to identify patterns related to NDD . The progression and reversal of disease depend on the underlying cause of the disease, as well as the timing and efficacy of interventions and individual patient characteristics . In some cases, interventions may slow or halt disease progression, while in others, interventions may be less effective . Therefore, identifying neurodegenerative disorders often requires the integration of multiple sources of data, including visual and statistical data, as well as input from physicians and other healthcare providers. By combining these different sources of information, it is possible to identify the most recent symptoms and track the progression of the disease through different stages. AI, ML, DL and other data-driven solutions can potentially transform the diagnosis and treatment of NDD by providing more accurate and personalised care . Identifying the progression of NDD is crucial as it can lead to severe consequences if left untreated. Early detection and monitoring of these diseases can help prevent or slow down the progression of symptoms. Therefore, healthcare systems need to have efficient and effective methods for identifying the progression of NDD. By incorporating advanced AI, ML, DL and other data-driven technologies into healthcare systems, early detection can be improved, and the diagnosis and treatment of the disease can be optimised. This research paper presents a novel Syndrome-dependent Pattern Recognition Method (SPRM) for early detection and progression monitoring of NDD, which aims to identify variance between normal and abnormal intrinsic neural connectivity data by using both previously collected data and data from healthy function examination, then combine them and apply deep recurrent learning for analysis of the data. The authors have employed tuning of the analysis layer, based on variations in the data. to suppress and recurrently use those variations to train a learning model for maximising recognition accuracy. This proposed method improves recognition accuracy by suppressing variations in the data. It is a novel approach in the field of NDDs for early detection and progression monitoring using precise identification of physical attributes. Nowadays, these attributes can be easily sensed and observed through wearable sensors. The main contributions of this article are listed below. A pattern recognition method is designed based on disease-specific syndromes to identify their intensity and provide an appropriate diagnosis. Disease progression is identified in the diagnosis stages to improve the medication and reduce unnecessary clinical recommendations in order to retain health stability. Data analysis is performed using different metrics to validate the proposed methods' consistency and performance. This research paper is structured in five sections, starting with an introduction in Section 1, which provides background information and sets the context for the research. In Section 2, the paper presents an overview of related work in the field, discussing previous methods and studies that have been conducted on the topic. Section 3 presents the proposed SPRM, describing the method in detail and explaining its key features. Section 4 provides the results and discussion, demonstrating accuracy, precision, pattern verification, variance, verification time, analysis of the method's performance, and discussion of its results. Finally, in Section 5, the paper concludes by summarising the main findings and contributions of the research. 2. Related Work Recently, there has been a growing interest in NDD identification and progression. Various methods and techniques have been proposed in the literature to improve the accuracy and efficiency of the diagnosis process. This focus is driven by the need to improve the diagnosis and treatment of NDD, which can have severe and debilitating effects on patients if left untreated. Some of the research in this area has focused on using advanced techniques such as AI, ML, DL and other data-driven models to analyse large amounts of data and identify patterns and features indicative of disease progression. Other research has aimed to develop new imaging techniques and biomarkers that can help detect these diseases early. Some recent research works propose and implement sophisticated AI, ML, DL and other data-driven models for NDD identification and progression. These works are explained as follows. Amyotrophic Lateral Sclerosis is a devastating NDD with no cure, which causes rapid degeneration of motor neurons and can result in death by respiratory failure. Non-invasive Ventilation is an effective treatment that can prolong survival and improve quality of life. Predicting the need for Non-invasive Ventilation is crucial for timely administration and better patient outcomes. In , the authors applied itemset and sequential pattern mining to identify disease presentation and progression patterns, respectively, and trained the prognostic models that incorporate static and temporal features. The case study outcomes showed promising results, with bulbar function, phrenic nerve response amplitude, and respiratory function identified as significant features. These findings align with clinical knowledge regarding relevant biomarkers of disease progression towards respiratory insufficiency. Predicting the long-term progression of AD is also a crucial aspect of disease management. The literature analysis uncovers that the existing methods have focused on predicting cognitive scores. Therefore, Zhao et al. proposed a framework that used a 3D multi-information generative adversarial network to predict an individual's whole brain appearance at future time-points, along with a 3D DenseNet-based multi-class classification network to determine the clinical stage of the estimated brain. The results show that the proposed framework outperforms the existing methods, with a high structural similarity index between the generated and real MRI images, and the use of focal loss improves accuracy in determining the clinical stage. The proposed framework has the potential to provide more information for accurate long-term disease progression prediction and, ultimately, to improve AD patient management. Peng et al. proposed white-matter features from positron-emission tomography-based progression for mild cognitive impairment to AD. The proposed approach involves an ML model for detecting disease progression and utilises multivariate logistic regression to assess the relevant characteristics and features of the detection process. The proposed model predicts the white matter changes in the brain, reducing the error rate in diagnosis and identification processes. Johnson et al. developed a multi-modal quantitative approach (MMQA) for predicting the progression of NDD. The proposed multimodal identifies key anatomical and metabolic changes that correlate with the progression of pathological and behavioural deficits in NDDs. By monitoring 144 parameters longitudinally using non-invasive neuroimaging modalities and kinematic gait analysis, the researchers developed a highly sensitive platform that can be used for preclinical studies. The results of this study suggest that this approach has the potential to be a powerful tool for clinicians in the future, providing valuable insights into the progression of NDDs. De Vos et al. introduced an ML-based method for detecting progressive supranuclear palsy using random forest and logistic regression algorithms. The proposed method also distinguished progressive supranuclear palsy from Parkinson's disease (PD) by classifying patterns based on specific conditions. An array of wearable sensors was used to create the dataset for the ML model. The introduced method improves the overall accuracy of progressive supranuclear palsy detection, increasing the effectiveness and reliability of the system. Kmetzsch et al. proposed a new framework for computing a disease progression score from cross-sectional multimodal data. A supervised multimodal variational autoencoder was used to infer a meaningful latent space, where latent representations were placed along a disease trajectory, and orthogonal projections computed a score onto this path. The framework was evaluated with multiple synthetic and real datasets, and results demonstrated better performance than state-of-the-art approaches. The proposed framework can objectively measure disease progression with potential applications in clinical trials. Zhao et al. designed a multimodal gait recognition for NDDs (MGR-ND). The proposed novel hybrid model learnt gait differences between three NDDs, PD severity levels, and healthy individuals. The model fused and aggregated data from multiple sensors and applied a spatial feature extractor and a new correlative memory neural network architecture to capture temporal information. A multi-switch discriminator was then used to associate observations with individual state estimations. The proposed framework outperformed several state-of-the-art techniques in classification accuracy. Alorf et al. presented a new approach to the multi-label classification of AD's stages using resting-state functional MRI and deep learning. The proposed model extracted the brain's functional connectivity networks from resting-state functional MRI data and utilised Stacked Sparse Autoencoder and Brain Connectivity Graph Convolutional Network deep learning approaches to solve the multi-class classification problem. The proposed models achieved an average accuracy of 77.13% and 84.03% for multi-label classification using Stacked Sparse Autoencoders and Brain Connectivity Based Convolutional Networks, respectively. The study also identified significant brain regions of interest by analysing the network's learned weights. Dentamaro et al. developed a method for discriminating NDD patterns by analysing human gait with 2D cameras. The proposed method used the kinematic theory of rapid human movements and other spatiotemporal features to model the human gait movement pattern. The results demonstrated the effectiveness of this approach in describing neurodegenerative patterns, achieving 99.1% accuracy when used in conjunction with state-of-the-art pose estimation and feature extraction techniques. In , an AI and wavelet coherence (AI-WC) based model was proposed. This model comprised a convolutional neural network and wavelet coherence spectrogram of gait synchronisation to classify NDDs based on gait force signals. The algorithm was evaluated using an existing online database, and the results showed that the proposed method effectively differentiates gait patterns between healthy control and NDD patients, with an overall sensitivity of 94.34%, specificity of 96.98%, the accuracy of 96.37%, and AUC value of 0.97 using 5-fold cross-validation. The proposed algorithm has the potential to aid physicians with screening for NDDs for early diagnosis, efficient treatment planning, and monitoring of disease progression. Lei et al. implemented an adaptive feature learning framework using multiple templates for the early diagnosis of NDDs. The proposed method was validated on AD and PD databases and outperformed the state-of-the-art methods. Different features were extracted and fused, and a feature selection was applied with an adaptively chosen sparse degree. In addition, linear discriminative analysis and locally preserving projections were integrated to construct a least square regression model. The proposed method demonstrated that accurate feature learning facilitates the identification of highly relevant brain regions with significant contributions to the prediction of disease progression. Bi et al. established a knowledge base to systematically understand the heterogeneity of the risk factors associated with different NDDs, which they refer to as pan-NDDs. This knowledge base aims to facilitate personalised and knowledge-guided diagnosis, prevention, and prediction of NDDs. The authors outlined the knowledge base's structure and content, including information on the epidemiology, genetics, environmental and lifestyle factors, clinical and neuropathological features, and treatment options for NDDs. The potential applications of the knowledge base are also discussed, including its use in clinical decision-making, drug development, and public health policies. Overall, the knowledge base is intended to provide a valuable resource for researchers, clinicians, and patients in the field of NDDs. Beyrami et al. proposed a new approach based on statistical and entropic features of vertical ground reaction forces of gait and sparse coding classification techniques. The study explored the effect of individual differences on the proposed and standard ML methods, emphasising the severity and duration of diseases and the right and left foot parameters. The study results indicated that, using left or right foot features, the proposed algorithm could identify all NDDs at early and advanced stages. Van Veen et al. used F-fluorodeoxyglucose positron emission tomography and Principal Component Analysis to identify disease-related brain patterns in neurodegenerative disorders. Nevertheless, they found that Principal Component Analysis has limitations in discriminating between different conditions. To overcome this, Generalized Matrix Learning Vector Quantization was applied to F-fluorodeoxyglucose positron emission tomography scans of healthy controls and patients with AD, PD, and Dementia with Lewy Bodies. The study demonstrated that Generalised Matrix Learning Vector Quantization is a more advanced ML algorithm that can provide a solution to discriminate between different neurodegenerative conditions. The literature analysis shows that recent research in neurodegenerative disease identification and progression has focused on developing sophisticated AI and ML models and algorithms that can accurately and efficiently detect, track and predict the progression of these diseases. Some examples include developing models that can predict the need for non-invasive Ventilation and using ML to classify patterns and features of the disease. Researchers have also been exploring the use of multimodal approaches that combine multiple imaging modalities, such as MRI, functional MRI and positron emission tomography, to gather more comprehensive information for diagnosis and classification. Various algorithms, such as random forest, logistic regression, and generative adversarial networks, have been used to classify the patterns and improve the diagnosis process. 3. Proposed Syndrome-Dependent Pattern Recognition Method This research article introduces an SPRM for the early and progressive detection of NDD. This method determines the variance between normal and abnormal intrinsic neural connectivity data. Pattern recognition also helps classify unknown data, improves the accuracy of predictions, and allows for the identification of learning techniques. This method can also generate predictions for unknown data and helps in practical decision-making. It can acknowledge and associate an object at various distances. The proposed method utilises recurrent learning, a commonly used method for handling sequential data before developing attention models. Recurrent learning is used to predict the problems in the method and recognise the speech that may be given as the input in the method. The workflow diagram of the proposed model is presented in Figure 1. Here in this method, the patient data is given as the input to recognise the patterns. Then it is checked with the data already stored. After identifying the patterns of the neural data, it is classified as unknown data or normal data. Unknown data is that found anew, without matching the existing data. Then, the acquired normal data is that which retains the previous value of the patients, and matches the previous data. It can be used as input for the training process. The results are analysed from the received unknown data using deep recurrent learning. This can also help recognise the data pattern by using the learning technique to identify the results. It can help generate divinations of unknown data and helps in preparing practical decisions. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. The variance is suppressed by identifying normal and abnormal patterns in the combined analysis. Variance can be both high and low, depending on the data pattern, to determine the accuracy of the patients' disease level. If variance occurs, then separate training will be given with the normal data pattern to reduce the variance. This variance from different patterns is recurrently used for training the learning model to maximise recognition accuracy. The variance is the difference from the previously acquired data. If there is an increase in the variance, then the intensity of the neurodegenerative disease should be identified with the recognised data pattern. The output of the variance is represented as the progression. From this output, the abnormality of the patient's disease can also be recognised, and processes can be carried out to reduce the abnormality. Abnormal results are those that are determined from the unknown data from the data pattern. The patients' data, which is observed at different times, is given as the input for the process to recognise the data pattern. The process of fixing the patient data, which is observed at different times as the input for the further procedure, is explained by the following Equation (1):(1) Aa={ 0, if a=0s(Aa-1,Xa), otherwise where (Aa) is denoted as the patient's data which is represented as the input, (Xa) is denoted as the observation time, and (s) is denoted as the calculation of the data in different observation times. Now the patient's data input is sent to recognise the pattern. The patient data is given as the input to recognise the pattern. Then it will be checked with the already stored data. The input neural data is sent to the pattern recognition process to identify whether it is unknown data or normal. The given input is checked with the stored data of the patient. This process is used to investigate whether the given input data matched the existing data of the patients. This pattern recognition is used to predict the present state of the patient's disease, and to identify the variance which results in progression. The recognition of the neural data is used to check the availability of the data which is already stored with the information. The input patient data is checked with the existing stored data to determine the matching. The input given is observed at different times and sent to settle the data pattern. This data pattern recognition is used to identify the difference between normal and abnormal connectivity. The already stored data contains the exact information about the patient's disease and the state of the disease. By checking with the stored data, the similarity of the input data can be established. After recognising the patterns of the neural data, it is classified as unknown data or normal data. It is also used to verify the pattern of the data. After recognising the data pattern of the patients' neurodegenerative disease, it can be classified into two types: unknown data, determined newly, and normal data, which match the stored data. This technique is used to determine the accuracy of the disease. The process of recognising the data pattern is explained by the following Equation (2):(2) As=s(WXa+SAa-1) where (W) is denoted as the process of data pattern recognition, and (S) is denoted as the existing stored data of the patients. Now, the data pattern recognising process identifies the unknown and normal data. The unknown data which is acquired from the process of data pattern recognition is the one that is newly received without any matching with the existing stored data. This is the data pattern recognised newly from the patient's disease. After recognising the patterns of the neural data, it is classified as unknown data or normal data. Unknown data is that which is found anew, without matching the existing data. The previous data does not match the acquired data. These are the data determined newly after the process of data pattern recognition. This process results in obtaining the unknown data pattern from the patients' neural data. This results in analysis of the unknown results by using recurrent learning to identify the progression results of the disease. After the process of data recognition, the data are categorised into unknown data and normal data. The unknown data do not match the stored data of the patients. Those data are observed at different times. This method is used to determine the variance that appeared in the training period by using the normal data, which matches the existing stored data. These data produce abnormal detection of the patients' neurodegenerative disease and produce unknown results. This will not be similar to the state of the stored patients' data and does not match those values of the disease. These unknown data are used in the procedure of analysing the operation, whereas normal data is used in training to deliver the perfect progression result concerning the patient's disease and its state. The results are analysed from the received unknown data using deep recurrent learning. It can also be helpful in recognising the data pattern to identify the results using the learning technique. The observed data is combined with previous and healthy function examination data to identify the variances. The process of determining the unknown data from the data pattern recognition procedure is explained by the following Equation (3):(3) Q(X1,X2,....Xn)D(X1)...D(Xn|X1....Xn-1) where (Q) is denoted as the unknown data, and (D) is denoted as the unknown data pattern of the acquired data. After recognising the patterns of the neural data, it is classified as unknown data or normal data. The patient data is given as the input to recognise the pattern. Then it will be checked with the already stored data. The data pattern recognition process results show that normal data can be determined. Then the acquired normal data is that which retains the previous value of the patients, which matches the previous data. It can be used as input for the training process. These data retain the previous value of the previous patients' neural disease reports. These match the already existing stored data of the patient. These data can be used as the input for the training. This can help detect the variance between the connectivity. The schematic diagram of data recognition from the distinguishable data (patterns) is presented in Figure 2. The sequence X1 to Xn-1 (leaving out the next W) from Aa is observed through Xa. In this observation instance, the sW is classified for ph and D for preventing V overlaps. The normal data is recognised from the data pattern recognition procedure. This is the one which matches the stored data already existing in the process. This procedure has complete information on patients' NDD, as shown in Figure 2. The process of acquiring the normal data from the data pattern recognition process is explained by the following Equation (4):(4) V Xn|X1,....Xa-1)=ph(Aa) where (V) is denoted as the normal data obtained from the data pattern recognition process, and ( ph(Aa)) is denoted as the calculation of the similarities of the found data with the stored data of the patients' neural diseases. Now the normal data is used as the input of the training to detect the variance. The unknown data was used for the analysis process by using deep recurrent learning. It can also be helpful in recognising the data pattern to identify the results by using the learning technique. It generates divinations of unknown data and helps in preparing practical decisions. The recurrent learning technique is used to predict decisions concerning the accuracy of the connectivity. It is also used to determine the abnormality of the disease by using unknown data from the data pattern recognition process. This analysis process helps to identify the unknown results which are produced by the unknown data from the process. It does not match any of the stored data, and it does not retain the observed values of the patients. This learning is used to predict the problems in the method and gives perfect solutions to resolve those abnormalities. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. From the training process, the variance is detected with the help of the normal data. Variance is the difference between the previous data and the present data. The process of analysis by using deep recurrent learning is explained by the following Equation (5) :(5) Aa=BaD (Ca)Ba=th (Woi Xa+WoA Aa-1+WoC Ca)Ca=iaC^a+DaCa-1Da=th ( WFiXa+WFAAa-1+WFCCa-1 )} where (Ba, Da, Ca) is denoted as the analysing process with the help of the unknown data which produces the unknown results, (th) is denoted as the dissimilar data acquired, (F, i) is denoted as the process of combined analysis, and () is denoted as the values of the disease. Now the normal data is used as the training input, which helps detect the variance. Variance is the difference occurring between the previous and the acquired data. This learning technique is used to determine the high variance and the low variance. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. Variance can be both high and low, depending on the data pattern, to determine the accuracy of the patients' disease level. If variance occurs, then separate training will be given with the normal data pattern to reduce the variance. The occurrence of variance causes the abnormal detection of the patient's disease and needs separate training to resolve the abnormalities. It can produce both a high and low variance depending on the state of the patient's disease. It also identifies abnormalities if they occur in the process of detecting the accuracy of the disease. This variance from different patterns is recurrently used for training the learning model for maximising recognition accuracy. The variance is the difference from the previously acquired data. The process of detecting the variance from the analysis procedure by using the unknown data and normal data in training is explained by the following Equations (6) and (7):(6) F(Ai)={(Ai), if Ai>0gi(Ai), if Ai<=0 (7) F(Ai)=l(0, F(Ai)l(0,(Ai)} where (F(Ai)) is denoted as the process of determining the variance, and (l) is denoted as the connectivity. From the result of the variance, high and low variances can be found. If there is an increasing order of variance, then the intensity of the disease should be identified to eliminate the abnormalities. This is the divergence between the present and the existing data. It is used to combine the observed data with the previous healthy functions to detect the variances in the process and further steps provided to reduce the variance. Separate training is given to reduce the variance with the help of the normal data, which is given as the input. The combined analysis based on the similarity process is displayed in Figure 3. The variance can be high or low according to the similarities of the data. Then separate training is given to reduce the variance with the help of the normal data, which is given as the input of the training. Based on this variance, the analysis process is done by using deep recurrent learning. This helps in identifying the intrinsic connectivity variances under two-layers. In the first layer, the possibilities for D and i are extracted for checking Aa and th combinations. These two processes are consequent such that the learning process discussed above is analysed using two layers, one for variance and the other for l estimation, as depicted in Figure 3. The first layer defines the F(Ai) for different variances; the next function is the th for identifying similarity. This function is different from the previous layer by identifying the remaining iterations and distinguishable F. The learning process is deployed for classifying normal and abnormal variances from the observed data. This classification is performed to prevent unidentified data features from influencing the analysis process without increasing the variance. The process of finding the variance between the normal and abnormal neural data connectivity is explained by the following Equations (8)-(10) :(8) G(Ai)=l(0, (Ai))+gils(0,(Ai)) (9) Rgi=AiLF(Ai)F(Ai)gi (10) F(Ai)Gli={0, if Ai>0I(Ai), if Ai<=0 where (G(Ai)) is denoted as the process of finding the variance between the neural data connectivity, and (Rgi) is denoted as the process of determining the observed data combined with the health function examination data. Now, from the variance output, the abnormality can be identified and resolved. The observed data is combined with previous and healthy function examination data to identify the variances. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. In Figure 4, the abnormality detection using the learning process is presented. The l is estimated between two sequences from the second R for (F,i). In the G(Ai) extraction the R segregates l and e i from ls. In the g* ls assessment of the input F(Ai) identifies abnormalities through recurrent iterations, as displayed in Figure 4. The abnormalities are found by the unknown data and results which do not match the previous data stored. With the help of the variance, the accuracy of the disease state and the abnormalities that occurred in it can be identified. Further steps such as more training can be performed to reduce the abnormalities. The process of acquiring the abnormality from the output of the variance can be explained by the following Equation (11):(11) RU=iuiRU(Ai)F(Ai)g where (RU) is denoted as obtaining the abnormality from the output of the analysing process and variance. Now, the progress report of the situation of the patient's disease is made by the output of the variance between the normal and abnormal intrinsic neural data connectivity. If the progression is abnormal, further steps are taken to reduce the abnormalities in the patient's disease report. The process of providing the progression report by the output of the variance is explained by the following Equations (12)-(14):(12) NGgi=lNGgi+NGgiRgi (13) Ai^=Ai-NGgiJ[Ai]Z[Ai] (14) Z[Ai]=aiDi^+J[Ai] where (NGgi) is denoted as the output of the variance detecting process, (J) is denoted as the intrinsic neural data connectivity, and (Z[Ai]) is denoted as the process of determining the progress report of the patients' neurodegenerative disease. The progression detection using the variance is presented in Figure 5. The progression is extracted by correlating J and from the G(Ai) estimation. Considering the ph(Aa) and th between Aa and RU, the variance is computed. The learning segregates the V and l for ease of progression detection. Compared to the available stored data, if varies to an extreme value, then progression is measured, as shown in Figure 5. This research article discussed SPRM for the early and progression detection of NDD. Pattern recognition also helps in classifying unknown data. It makes valuable predictions and identifies the learning techniques. The observed data is combined with previous and healthy function examination data to identify the variances. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. This variance from different patterns is recurrently used for training the learning model to maximise recognition accuracy. 4. Results and Discussion This section is divided into model analysis and comparative analysis to illustrate the quantitative work using the dataset. The self-analysis involves analyzing the matching features extracted using the clinical observation discussed in the proposed method. This real-time data analysis is performed using the representation and the observation sequences. The patterns observed in the sequences are correlated with the proposal for verifying its efficiency and validating the statistical performance. In contrast, the comparative analysis continues the self-analysis and the representations depicted in the subsequent subsections. Besides self-consistency, out-of-box verification is required to prove the stability of the proposed concept. Therefore, the results associated with the data features are comparatively analyzed. Alongside the metrics, the process features such as time, variances observed, and their impact on the proposed method are elaborated. 4.1. Dataset Description and Model Analysis The analysis for identifying disease prediction is performed using PD progression data . This source provides observed information from 42 human subjects for detecting PD progression. A total of 16 fields correlating personal and medical information are recorded for the corresponding progression detection. The motor operations, harmonics, fluctuation, entropy, jitter, testing time, etc., are the features used for detecting progression. A total of 5876 records are used for analysis of the patterns and progression. The progression is observed through 120-148 sensing instances at different intervals. These patterns for the known and unknown sequences are extracted as presented in Figure 6. The sequence variance determines its need for unknown detection. The observations identify Unified Parkinson's Disease Rating Scale (UPDRS) and shimmer during the first and normal test times. Contrarily, if a difference due to fitter and shimmer is observed, then it is a variance. This requires Noise-to-Harmonics Ratio (NHR), Recurrence Period Density Entropy (RPDE), and Detrended Fluctuation Analysis (DFA) observations (additional) during the next sequence. In this case, the unknown pattern features are identified in the (next) successive observation, as depicted in Figure 6. The variance is estimated using different ranges as defined by the disease correlation values. Say, for example, the DA (different amplitude) between two successive sequences ranges between 0.4 and 0.6. The exceeding range (beyond 0.6) is termed a variance. Therefore, the "Jitter" and "Shimmer" above 0.6 is marked as unknown. The additional NHR, RPDE, and DFA are observed to prevent disease progression detection errors. Therefore, the number of additional observations required among the 42 patients between 120 and 148 sequences is presented in Figure 7. The observation of patterns and variations for different sequences is presented in Figure 7. The pattern across different observations is validated if any unknown information is sensed. Therefore, the analysis is performed to extract abnormalities under varying sequences. Hence, the consecutive training iteration relies on analysis other than classification. This is validated until NHR (or) RPDE (or) DFA clarifies the patterns from the observed patient data. The intense assessment is concluded if the variance (between sequences) is stabilised. The variance achieves its maximum output without increasing/decreasing, as interpreted from Figure 7. The variations are identified from the ph and V patterns based on l for which G(Ai) is computed. The variance for progression estimation is set as 0.06 (from the Jitter RPP) (max), and therefore the decision is performed. This average progression value varies with the patient's physical attributes (age, disorder, healthy level, etc.). The different (mean) variation across the different patterns is analysed in Figure 8. The F(Ai) analysis is presented in Figure 8 for the varying patterns. This analysis considers the varying patients and (Q,V) depending on the l. The l for the observable r(Aa) achieves less f(Ai); this is true under less available patient data. Contrarily, if Rri is required variation (function verification), then the F(Ai) increases such that Xa requires a new instance. Therefore, the RU is the consecutive derivative function for abnormality detection. In this process, the learning process identifies the F(Ai) suppression condition for maximising precise Z(Ai). Now, the progression classification based on D is performed as presented in Figure 9. The progression is analysed from F(Ai)=true condition till a r(Aa) is observed. Therefore Z[Ai] is the combination of (F,i) and G(Ai) between two consecutives l. Hence a new observation is required to prevent false progression detection. Considering the differences across various Xa, the th and Rri are utilised for l verification and eri assessment, as shown in Figure 9. 4.2. Comparative Analysis This section presents the discussion of comparative analysis by performing comparison of proposed SPRM with the existing methods--MMQA , MGR-ND , and AI-WC . This analysis computes the performance matrices' accuracy, precision, pattern verification, variance, and verification time. From the data source, the inputs are varied from 500 to 5000, and the patterns are varied from 2 to 32. 4.2.1. Accuracy The accuracy of the recognition process is efficacious in this method by using the SPRM. After recognising the patterns of the neural data, it is classified as unknown data or normal data. The results are analysed using deep recurrent learning from the unknown data. It can also help recognise the data pattern to identify the results by using the learning technique. It generates divinations of unknown data and helps in preparing practical decisions. This method identifies the variance between normal and abnormal intrinsic neural connectivity data. The variance is the difference from the previously acquired data. If there is an increase in the variance, then the intensity of the neurodegenerative disease should be identified with the recognised data pattern. The output of the variance is represented as the progression. From this output, the patient's disease's abnormality can also be recognised, and processes can be carried out to reduce the abnormality. Through this process, the accuracy of the recognition is increased. Figure 10 depicts the comparison of accuracy for implemented SPRM, and existing MMQA, MGR-ND, and AI-WC for different data inputs and patterns. 4.2.2. Precision The precision is high in this process using the SPRM and the deep recurrent learning technique. At first, the data pattern is recognised with precision, and then it is classified into unknown data and normal data. It is determined by the patients' neural data, which is observed at different times. This method identifies the variances in different observation intervals. The observed data is combined with previous and healthy function examination data to identify the variances. In this combined analysis, deep recurrent learning is exploited by tuning the analysis layer based on variance. The variance is suppressed by identifying normal and abnormal patterns in the combined analysis. This is the divergence between the present and the existing data. It is used to combine the observed data with the previous healthy functions to detect the variances. Based on this variance, the analysis process is carried out by using deep recurrent learning. This helps in identifying the intrinsic connectivity using the variances in each observation instance. Figure 11 shows the comparison of precision for implemented SPRM, and existing MMQA, MGR-ND, and AI-WC for different data inputs and patterns. 4.2.3. Pattern Verification The pattern verification is highly accurate using the SPRM and the recurrent learning technique. The patient data is given as the input to recognise the pattern. Then, it will be checked with the already stored data. Based on the data features and variances, the progression is identified in this proposed method. The variances indicate the chances of the risks by estimating precise patient behavior. This behavior varies with the actual body conditions of either risk or nil risks. The input neural data is sent to the pattern recognition process to identify whether it is unknown data or normal. The given input is checked with the stored data of the patient. This process is used to investigate whether the given input data matched the existing data of the patients. This pattern recognition predicts the present state of the patient's disease. This is also used to identify the variance which results in progression. By checking with the stored data, the similarity of the input data can be established. After recognising the patterns of the neural data, it is classified as unknown or normal data. It is also used to verify the pattern of the data. After recognising the data pattern of the patients' neurodegenerative disease, it can be classified into two types: unknown data, which is determined newly, and normal data, which matches the stored data. Figure 12 displays the comparison of pattern verification for implemented SPRM, and existing MMQA, MGR-ND, and AI-WC for different data inputs and patterns. 4.2.4. Variance The occurrence of variance is less in this process using deep recurrent learning. The normal data is used as the input to the training process, which helps in detecting the variance. Variance is the difference that occurs between the previous and the acquired data. This method identifies the different variances across distinguishable patterns. This learning technique is used to determine the high variance and the low variance. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. Variance can be both high and low depending on the pattern of the data in determining the accuracy of the patients' disease level. If variance occurs, then separate training will be given with the normal data pattern to reduce the variance. The occurrence of variance causes the abnormal detection of the patient's disease, and this needs extra separate training to resolve the abnormalities. This variance from different patterns is recurrently used for training the learning model to maximise recognition accuracy. Figure 13 shows the comparison of variance for implemented SPRM, and existing MMQA, MGR-ND, and AI-WC for different data inputs and patterns. 4.2.5. Verification Time Data pattern verification and variance occurrence are less in this method using SPRM and learning techniques. This method identifies the variance between normal and abnormal intrinsic neural connectivity data. This learning technique is used to determine the high variance and the low variance. Based on this variance, the analysis process is carried out using deep recurrent learning. Now, from the variance output, the abnormality can be identified and resolved. The observed data is combined with previous and healthy function examination data to identify the variances. This combined analysis exploits deep recurrent learning by tuning the analysis layer based on variance. The output makes the progression report concerning the situation of the patient's disease based on the variance between the normal and abnormal intrinsic neural data connectivity. If the progression is abnormal, further steps are taken to reduce the abnormalities in the patient's disease report. Figure 14 compares verification time for implemented SPRM and existing MMQA, MGR-ND, and AI-WC for different data inputs and patterns. Table 1 and Table 2 summarise the comparative analysis of results obtained from the implemented SPRM, and existing MMQA, MGR-ND, and AI-WC. The above results are presented by observing the cumulative progression of data inputs and the patterns from the inputs. Considering the cumulative mean value of the existing methods, the proposed method is validated in terms of ratio. Summary: The proposed method achieves 13.15% high accuracy, 11.84% high precision, and 8.44% high pattern verification. It reduces the variance and verification time by 12.6% and 10.39%, respectively. Summary: The proposed method achieves 16.77% high accuracy, 10.55% high precision, and 7.69% high pattern verification. It reduces the variance and verification time by 12.08% and 12.02%, respectively. 5. Conclusions This article introduces an SPRM for identifying neurodegenerative disease progression. The progression is identified using clinical and patient-observed data across multiple instances. The data correlation is based on different patterns exhibited by the input data and is combined for unknown patterns and dissimilarity analysis. The connectivity and variance metrics are validated in this analysis to prevent observation function overflows. The process is extended using deep recurrent learning to identify consecutive sequential abnormalities. The identified abnormalities are validated for the intrinsic data connectivity for progress estimation. The accuracy and precision features are consistently retained from successive iterations by mitigating the abnormalities. Further data analysis is resolved through the same kind of process; therefore, the healthy (previous) and the observation instance data are jointly used for analysis to prevent variance verification. This guides the identification of new unclassified patterns; this unclassified data is normalised using precise data computation for which the new variance is estimated. The unidentified instances generate a chance of causing variations that are suppressed by training from the previous consecutive intervals. The difference between successive variance pronounces the disease progression, correlated to the clinical values. The proposed method achieves 13.15% high accuracy, 11.84% high precision, and 8.44% high pattern verification. It reduces the variance and verification time by 12.6% and 10.39%, respectively. The implemented SPRM has significantly improved the accuracy and efficiency of NDD diagnosis, ultimately leading to better patient outcomes. Despite significant achievements in disease progression identification, the proposed method lags in identifying and slagging missing data. This issue may generate high variances across different observation intervals that impact the accuracy. Therefore, a modified missing value substitution method can be proposed to extend the current work. This work will either reduce the errors or identify the error-causing sequences. Author Contributions Conceptualisation, M.A. and S.S.; methodology, M.A. and S.S.; software, M.A. and S.S.; validation, M.A., S.S. and Y.Y.; formal analysis, Y.Y.; resources, S.S.; data curation, S.S.; writing--original draft preparation, M.A. and S.S.; writing--review and editing, S.S. and Y.Y.; visualisation, S.S. and Y.Y. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement We have provided data web link in ref. and cited in text. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The proposed Syndrome-dependent Pattern Recognition Model. Figure 2 Schematic diagram of data recognition. Figure 3 Combined analysis process. Figure 4 Learning for abnormalities. Figure 5 The variance-based progression detection process. Figure 6 Unknown sequence pattern features. Figure 7 Observation analysis. Figure 8 F(Ai) analysis. Figure 9 Progression classification. Figure 10 Accuracy analysis. Figure 11 Precision analysis. Figure 12 Pattern verification analysis. Figure 13 Variance analysis. Figure 14 Verification time analysis. diagnostics-13-00887-t001_Table 1 Table 1 Summary of data inputs. Metrics MMQA MGR-ND AI-WC SPRM Accuracy 82.44 86.91 90.02 93.034 Precision 0.784 0.841 0.895 0.9584 Pattern Verification 7 12 21 27 Variance 0.232 0.187 0.108 0.0497 Verification Time (s) 6.16 5.02 3.32 1.821 diagnostics-13-00887-t002_Table 2 Table 2 Summary of patterns. Metrics MMQA MGR-ND AI-WC SPRM Accuracy 81.46 83.65 90.79 93.683 Precision 0.788 0.849 0.904 0.9525 Pattern Verification 8 13 21 26 Variance 0.236 0.174 0.112 0.0532 Verification Time (s) 6.12 5.08 3.24 1.343 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000543 | Tumor metabolism characterized by aerobic glycolysis makes the Warburg effect a unique target for tumor therapy. Recent studies have found that glycogen branching enzyme 1 (GBE1) is involved in cancer progression. However, the study of GBE1 in gliomas is limited. We determined by bioinformatics analysis that GBE1 expression is elevated in gliomas and correlates with poor prognoses. In vitro experiments showed that GBE1 knockdown slows glioma cell proliferation, inhibits multiple biological behaviors, and alters glioma cell glycolytic capacity. Furthermore, GBE1 knockdown resulted in the inhibition of the NF-kB pathway as well as elevated expression of fructose-bisphosphatase 1 (FBP1). Further knockdown of elevated FBP1 reversed the inhibitory effect of GBE1 knockdown, restoring glycolytic reserve capacity. Furthermore, GBE1 knockdown suppressed xenograft tumor formation in vivo and conferred a significant survival benefit. Collectively, GBE1 reduces FBP1 expression through the NF-kB pathway, shifting the glucose metabolism pattern of glioma cells to glycolysis and enhancing the Warburg effect to drive glioma progression. These results suggest that GBE1 can be a novel target for glioma in metabolic therapy. glucan branching enzyme 1 Warburg effect glucose metabolism fructose-bisphosphatase 1 NF-kB National Natural Science Foundation of China82103216 81820108011 82271345 Zhejiang Provincial Natural Science Foundation of ChinaLQ20H090005 This research was funded by the National Natural Science Foundation of China (No. 82103216, 81820108011 and 82271345) and the Zhejiang Provincial Natural Science Foundation of China (LQ20H090005). pmc1. Introduction Gliomas are the most common malignant tumors in the central nervous system and are divided into circumscribed gliomas and diffuse gliomas, according to WHO CNS5 in 2021 . Glioblastoma (GBM), the most common and fatal diffuse glioma, accounts for 57.3% of gliomas . Treatment of GBM is often unsatisfactory due to the limited extent of surgical resection and the presence of the blood-brain barrier (BBB) and the complex tumor microenvironment, with a median survival of fewer than two years and only 6.9% of patients who survive more than five years after diagnosis . Therefore, studying the pathogenesis of glioma and finding the factors driving tumorigenesis and progression are essential for treating glioma. The Warburg effect endows tumor cells with the ability to use aerobic glycolysis to meet their high-metabolite needs, but it also makes tumor metabolism a unique target for targeted therapy. Studies have found that the Warburg effect promotes tumor progression in multiple ways, including by reducing toxic metabolites , methylating tumor suppressor genes , and inhibiting immune responses . Thus, targeting tumor metabolism may inhibit tumor progression from multiple aspects. A recent study found that inhibition of the basic leucine zipper and W2 domain 1 (BZW1) suppresses pancreatic cancer cell proliferation by inhibiting glycolysis under oxygen and glucose deprivation conditions . Ovo Like Zinc Finger 2 (OVOL2), a transcription factor, inhibits the Warburg effect and breast cancer progression by suppressing the expression of glycolytic genes . Moreover, in ovarian cancer, fibrillin-1 (FBN1) knockdown enhances cisplatin sensitivity by inhibiting glycolysis and angiogenesis . Furthermore, the disruption of glycolysis in gliomas suppressed intracranial tumors and prolonged the median survival time of mice . The loss of function of glycogen branching enzymes (GBE1) is the cause of glycogen metabolic disorders such as Glycogen Storage Disease IV (GSD-IV) and Adult Polyglucosan Body Disease (APBD) . However, an increasing number of studies have shown its relevance to cancer. On the one hand, GBE1 is highly expressed in acute myeloid leukemia (AML) and maintains abnormal tumor cell proliferation by inhibiting AMPK activity . GBE1 expression is also elevated in lung adenocarcinomas and is associated with worse survival . On the other hand, GBE1 expression is decreased in ovarian cancer, and GBE1 downregulation is correlated with poor clinical outcomes . These studies demonstrate that GBE1 plays different roles in different tumors. However, there has not been enough significant research on GBE1 in gliomas. Herein, we evaluated GBE1's role in gliomas, confirming that the expression of GBE1 is elevated in gliomas and correlates with a poor prognosis. We then demonstrated through cellular and animal experiments that GBE1 influences FBP1 expression through the NF-kB pathway, which affects the glucose metabolism pattern of glioma cells and promotes the Warburg effect to drive tumor progression. This study provides a potential target for glioma metabolic therapy. 2. Materials and Methods 2.1. Cell Culture Human glioma cell lines U87, ln229, and U251; HEK-293t engineered cells, as well as human umbilical vein endothelial cells (HUVECs), were purchased from the Shanghai Institute of Biosciences and Cell Resources Center (Chinese Academy of Sciences, Shanghai, China) and cultured in Dulbecco's Modified Eagle Medium (DMEM, Gibco, C11995500BT, Waltham, MA, USA) supplemented with 5% fetal bovine serum (FBS, Gibco, 16000044, Waltham, MA, USA) and 1% penicillin-streptomycin (Gibco, 15070063, Waltham, MA, USA) in an incubator at 37 degC, 5% CO2. 2.2. Plasmid Construction and Lentiviral Transfection Plasmid construction and lentiviral transfection were performed as previously described . Oligonucleotides targeting the following mRNA sequences were synthesized by Sangon Biotech (Shanghai, China) (sh-GBE1-1: AAAGGTAGTTATTACTAGTAAA, sh-GBE1-2: TTCGCTACAAGTTCCTAAATAA, and sh-FBP1: TACCAACGTGACAGGTGATCAA) and integrated into a lentiviral vector expressing mCherry fluorescent protein. oe-FBP1 and oe-NC plasmids were provided by Youze Bio (Guangzhou, China). Recombinant plasmids (sh-GBE1, sh-FBP1, and oe-FBP1) and empty plasmids (sh-NC and oe-FBP1) were co-transfected with packaging plasmids (pRSV-Rev, pMDLg pRRE, and VSV-G) into HEK-293t cells to produce lentiviral particles. Glioma cells were infected with the supernatant containing lentiviral particles for 24 h. Infected cells were screened by the BD FACSAria cell sorter (BD, Franklin Lakes, NJ, USA) according to the expression of mCherry. 2.3. RNA Extraction and Real-Time Quantitative PCR (qRT-PCR) The total RNA of glioma cells was extracted by Trizol (Thermo Scientific, 15596018, Waltham, MA, USA), and then the cDNA libraries were constructed using the RevertAid RT reverse transcription kit (Thermo Scientific, k1691, Waltham, MA, USA). qRT-PCR was performed with the following program for 40 cycles: 95 degC/15 s, 60 degC/15 s, and 72 degC/45 s. The cycle threshold (CT) value of the target RNA was normalized to that of GAPDH. The relative expression was finally calculated by the 2-^^CT method. The qRT-PCR primer sequences were as follows: GBE1-Forward: 5'-GGACTTCCAGCGCAGGTATAA-3', GBE1-Reverse: 5'-ATCAGCACATCTGTGGACGC-3', FBP1-Forward: 5'-CCTACTGCCCTCTCTTGCCG-3', FBP1-Reverse: 5'-CCATGACGAAGCGGGTCAG-3', GAPDH-Forward: 5'-TGACATCAAGAAGGTGGTGAAGCAG-3', GAPDH-Reverse: 5'-GTGTCGCTGTTGAAGTCAGAGGAG-3'. 2.4. Protein Extraction and Western Blot (WB) The total protein of glioma cells was extracted with RIPA lysis solution (Thermo Scientific, 89900, Waltham, MA, USA) containing a protease phosphatase inhibitor cocktail (Beyotime, p1045, Shanghai, China) and phenylmethanesulfonyl fluoride (PMSF, Beyotime, p1045, Shanghai, China). Protein concentration was determined using a BCA protein assay kit (Thermo Scientific, 23227, Waltham, MA, USA). Protein samples were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride membranes (PVDF, Merck Millipore, IPFL85R, Darmstadt, Germany). They were then blocked with a TBST (TBS, 0.1% Tween) solution containing 5% skimmed milk for 2 h at room temperature and incubated with primary antibodies overnight at 4 degC. Finally, they were incubated with horseradish peroxidase (HRP) conjugated secondary antibodies for 1 h at room temperature. Protein bands were developed using an ECL luminescence reagent (Meilunbio, MA0186, Dalian, China). Details of the antibodies are as follows: Anti-GBE1 (Abcam, ab180596, 1:1000, Cambridge, UK), Anti-FBP1 (Affinity, DF7325, 1:1000, Suyang, China), Anti-HIF1a (CST, 36169, 1:1000, Boston, MA, USA), Anti-MMP9 (Affinity, BF0560, 1:1000, Suyang, China), Anti-VEGFA (Abcam, ab46154, 1:1000, Cambridge, UK), Anti-Bcl-2 (Affinity, AF6139, 1:1000, Suyang, China), Anti-Bax (Affinity, AF0120, 1:1000, Suyang, China), Anti-Caspase-3 (Abcam, ab32351, 1:1000, Cambridge, UK), Anti-Cyclin D1 (Affinity, AF0931, 1:1000, Suyang, China), Anti-Cyclin D1 (Affinity, AF0931, 1:1000, Suyang, China), Anti-p65 (Affinity, AF5006, 1:1000, Suyang, China), Anti-Phospho-p65 (Affinity, AF2006, 1:1000, Suyang, China), Anti-GAPDH (Affinity, AF7021, 1:1000, Suyang, China), Anti-beta-Tubulin (Abcam, ab78078, 1:1000, Cambridge, UK), Goat Anti-Mouse IgG (Biosharp, BL001A, 1:5000, Hefei, China), Goat Anti-Rabbit IgG (Biosharp, BL003A, 1:5000, Hefei, China). 2.5. Cell Proliferation Assay and Colony Formation Assay Cell proliferation assays were performed using Cell Counting Kit-8 (CCK-8, MCE, HY-K0301, Monmouth, NJ, USA). Briefly, a CCK-8 reagent was added to the culture medium according to the instructions, then placed in an incubator at 37 degC with 5% CO2 in the dark for 2 h. Finally, the absorbance at 450 nm was measured using a microplate reader. U87 cells (1000 per well), ln229 cells (2000 per well), and U251 cells (2000 per well) were seeded in 6-cm dishes and then cultured in an incubator at 37 degC with 5% CO2. A fresh complete medium was replaced every 3 days. After 14 days of culture, cells were fixed with 4% paraformaldehyde (Solarbio, p1110, Beijing, China) and stained with 2.5% crystal violet (Meilunbio, MA0148, Dalian, China). Pictures were finally taken with a digital camera by a researcher who was blinded to the group allocation to calculate the colony formation rate. Colony formation rate = amount of colonies/number of seeded cells. 2.6. Cell Cycle Analysis and Apoptosis Detection The cell cycle was detected using the DNA content quantification assay (Solarbio, CA1510, Beijing, China). Briefly, cells were fixed with 75% alcohol overnight at 4 degC after digestion with trypsin (Gibco, 25200072, Waltham, MA, USA). RNase A was used the next day to remove RNA. Then PI staining solution was added, and the cells were incubated for 30 min in the dark at 4 degC. The cell cycle was finally detected using Beckman Coulter Cytoflex (BeckmanCoulter, Brea, CA, USA). Apoptosis was detected using an Annexin V-FITC apoptosis detection kit (Solarbio, CA1020, Beijing, China). Briefly, cells were digested with an EDTA-free trypsin (Gibco, 15050057, Waltham, MA, USA) and resuspended in a 1x binding buffer. FITC-labeled anti-Annexin V was added for 5 min at room temperature in the dark. Finally, the PI staining solution was added, and cell apoptosis was detected using Beckman Coulter Cytoflex (BeckmanCoulter, Brea, CA, USA). 2.7. Wound Healing Assay and Transwell Assay Once 90% cell confluence was reached, a wound was created with a 200 mL pipette tip, and floating cells were washed. Fresh serum-free DMEM was added, and three locations were randomly selected and photographed under a microscope (Olympus, Tokyo, Japan) to record the initial wound area. The cells were then incubated at 37 degC with 5% CO2 to continue the culture. Photographs were taken at the same location every 12 h, and the area of scratch reduction was counted as the wound healing area. All the measurements were performed by a researcher who was blinded to group allocation. Transwell chambers (Corning, 3422, New York, NY, USA) were used to further assess cell migration and invasion capabilities. For the migration assay, after 24 h of serum-free starvation, cells were resuspended in serum-free DMEM and seeded at a density of 2 x 105/mL in the upper chamber and in the lower chambers with a complete medium containing 10% FBS. The chambers were then placed in a 37 degC, 5% CO2 incubator for another 24 h. The transwell chambers were coated with Matrigel (Corning, 354234, New York, NY, USA) for the invasion assay. After cells were serum-free starved for 24 h, they were resuspended in serum-free DMEM and seeded at a density of 4 x 105/mL in the upper chamber and the lower chamber with a complete medium containing 10% FBS. The chambers were then placed in a 37 degC, 5% CO2 incubator for 48 h. Cells were fixed with 4% paraformaldehyde after culture, stained with crystal violet after scratching off the upper chamber cells, and finally photographed for counting under a microscope (Olympus, Japan, Tokyo, Japan) by a blinded researcher. 2.8. Oxygen Deprivation Assay and Tubule Formation Assay Glioma cells (1 x 104 per well) were seeded in 96 well plates and incubated at 37 degC in a 5% CO2 incubator for 24 h. The entire fresh medium was replaced before hypoxia. The plates were then incubated at 37 degC in a hypoxia incubator (5% CO2, 95% N2) for another 24 h, and cell proliferation was detected by CCK-8 reagent every 8 h. U87 (1 x 107 per dish), LN229 (5 x 106 per dish), and U251 (5 x 106 per dish) cells were seeded in 10 cm dishes. After 24 h of normal culture, cells were changed to serum-free DMEM and placed in a 37 degC hypoxia incubator (5% CO2, 95% N2) for another 24 h. The supernatant was collected and purified as conditioned medium (CdM). GFP-labeled HUVEC cells (8 x 104 per well) were seeded in Matrigel-coated 96-well plates after resuspension with CdM. The cells were then placed in an incubator at 37 degC with 5% CO2 for 12 h, and pictures were taken under a fluorescence microscope (Leica, Wetzlar, Germany) every 3 h to record tubule formation. All measurements and observations of tubule formation assays were performed by an investigator blinded to group allocation. 2.9. Immunofluorescence Staining and Immunohistochemistry Staining For immunofluorescence staining, glioma cells were blocked with 5% bovine serum albumin (BSA, Beyotime, ST023, Shanghai, China) in PBST solution (PBS, 0.4% Triton) for 1 h at room temperature after fixation with 4% paraformaldehyde. The primary antibodies were then added for overnight incubation at 4 degC. The next day, cells were incubated with fluorescence-conjugated secondary antibodies for 1 h at room temperature, and finally, the nuclei were stained with a DAPI staining solution (Solarbio, S2110, Beijing, China). Images were acquired using a fluorescence microscope (Leica, Wetzlar, Germany) by a blinded researcher. For immunohistochemical staining, tumor and adjacent tissues from three glioblastoma patients were collected at the Department of Neurosurgery in the First Affiliated Hospital of Wenzhou Medical University. Tissue sections were dewaxed and hydrated and then soaked in 3% H2O2 for 10 min to remove endogenous catalase. The antigen was then repaired with a citrate-EDTA antigen recovery solution (Beyotime, P0086, Shanghai, China). Tissue sections were then blocked with 5% BSA in PBST for 1 h at room temperature and incubated with primary antibodies overnight at 4 degC. The following day, tissue sections were incubated with HRP-labeled secondary antibodies at 37 degC for 1 h and then developed with the DAB Color Development Kit (Beyotime, P0202, Shanghai, China) for 5 min. Finally, the nuclei were stained with hematoxylin (Beyotime, C0107, Shanghai, China). All measurements and observations were performed by a blinded investigator. The collection of human specimens was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University (Ethics number: KY2021-R129). The antibody details are as follows: Anti-KI67 (Abcam, ab16667, 1:1000, Cambridge, UK), Anti-GBE1 (Abcam, ab180596, 1:1000, Cambridge, UK), Dylight 488, Donkey anti-rabbit IgG (EarthOx, E032221, 1:500, Millbrae, CA, USA), Goat anti-rabbit IgG (Biosharp, BL003A, 1:5000, Hefei, China). 2.10. Glycolytic Stress Test and Mitochondrial Stress Test Glioma cells (2 x 104 per well) were seeded in Seahorse XF 96-well culture plates (Agilent, 102601, Santa Clara, CA, USA) and incubated at 37 degC in a 5% CO2 incubator for 24 h. For the glycolytic stress test, cells were changed to detection medium (XF base medium, 2 mM glutamine) the next day, and the change in extracellular acidification rate (ECAR) after the sequential addition of glucose, oligomycin, and 2-Deoxyglucose (2-DG) was detected with the Seahorse XF Pro analyzer (Agilent, Santa Clara, CA, USA). For the mitochondrial stress test, cells were changed to detection medium (XF base medium, 1 mM sodium pyruvate, 2 mM glutamine, and 10 mM glucose) the next day. Then, the change in cellular oxygen consumption rate (OCR) after the sequential addition of oligomycin, FCCP, and rotenone/antimycin A was detected with a Seahorse XF Pro analyzer (Agilent, Santa Clara, CA, USA). 2.11. Intracranial Tumor Formation A total of 10 BALB-c/nude male mice aged 4 to 6 weeks were purchased from the Shanghai Charles River Experimental Animal Limited Liability Company (Shanghai, China) and housed under specific pathogen-free conditions (SPF) (20-23 degC, 55-60% humidity) at the laboratory animal center, the First Affiliated Hospital of Wenzhou Medical University. Lentivirus (sh-NC or sh-GBE1) infected U87 cells carrying luciferase reporters were prepared. Nude mice were sequentially numbered and randomly divided into two groups (n = 5). Then, 5 x 105 cells were transplanted into the striatum of nude mice according to the mouse brain anatomical atlas accessed on 5 May 2022). The optical density values of xenografts were measured every seven days using the IVIS in vivo optical imaging system (PerkinElmer, Waltham, MA, USA). The natural death time of nude mice was recorded for survival analysis. All measurements and observations were performed by a blinded researcher. All animal experiments were approved by the animal ethics committee of Wenzhou Medical University (Ethics number: WYYY-2021-0214). 2.12. Bioinformatics Analysis Based on Public Databases We performed differential expression analysis and Kaplan-Meier survival analysis of GBE1 by gene expression profiling interactive analysis (GEPIA). To further analyze the association of GBE1 expression with glioma grade, IDH mutation, and 1p/19q co-deletion, we obtained RNA-seq and clinical data from 584 glioma patients from the Cancer Genome Atlas (TCGA), including 441 low-grade gliomas (LGG) and 143 glioblastomas. RNA expression profiles were presented as fragments per kilobase of exon model per million mapped fragments (FPKM). Moreover, we obtained the data of 686 glioma patients from the Chinese glioma Genome Atlas (CGGA) and did the same analysis for further demonstration. Finally, based on the TCGA database, ROC curves were generated according to the expression of GBE1 in LGG and GBM. 2.13. Statistical Analysis All statistical analyses of this study were performed using GraphPad Prism 9. Student's t-test was used to determine whether differences between two data groups conformed to the normal distribution, and variance analysis was used to compare data among multiple groups. The homogeneity of variance was tested by the Leneve test. Kaplan-Meier survival curves were compared using the Log-rank (Mantel-Cox) test. Data are presented as mean +- standard deviation (SD), and a two-tailed p-value < 0.05 was considered statistically significant. 3. Results 3.1. GBE1 Expression Was Associated with Glioma Malignancy GBE1 was overexpressed in a variety of tumors. To investigate GBE1 expression in gliomas, we performed a differential expression analysis through the GEPIA database (gepia2.cancer-pku.cn) and found that its expression was significantly higher in both LGG and GBM samples compared to normal samples . Additionally, the overall survival and disease-free survival of patients in the GBE1 high-expression group were significantly lower than those in the low-expression group . The mRNA expression profiles and clinical information of 584 glioma samples from the TCGA database and 686 glioma samples from the CGGA database revealed a significant positive correlation between GBE1 expression and WHO grade of gliomas . Further, we subdivided the glioma samples according to IDH mutation status and 1p/19q deletion status and found higher GBE1 expression in IDH wild-type gliomas compared to IDH mutant ones . As well as the higher expression of GBE1 in intact 1p/19q samples compared to co-deleted samples . Furthermore, the results of IHC staining of tumor tissues and adjacent normal tissues from three glioma patients confirmed the higher expression of GBE1 in glioma samples . These results suggested that GBE1 expression parallels the malignancy of gliomas. Subsequently, we evaluated the performance of GBE1 in distinguishing glioma grades by ROC curve. Its area under the curve (AUC) was 89.15% compared to 74.21% of KI67 , indicating that GBE1 can be considered a discriminator of glioma malignancy. 3.2. GBE1 Knockdown Inhibited Glioma Cell Proliferation and Induced Cell Cycle Arrest and Apoptosis Bioinformatics analysis showed a strong association of GBE1 with glioma. To further investigate the role of GBE1 in gliomas, stable GBE1 knockdown and negative control U87, ln229, and U251 cells were constructed by sh-GBE1-1, sh-GBE1-2, and sh-NC lentiviruses, and the knockdown efficiency was verified by qPCR and WB . Since sh-GBE1-1 and sh-GBE1-2 exhibited almost identical knockdown efficiencies, we selected sh-GBE1-1 for subsequent experiments. The cell counting kit-8 assay was then used to detect cell proliferation. The results showed that the proliferation of all three glioma cell lines was inhibited in the GBE1 knockdown group compared with the negative control . Moreover, cell cycle analysis showed that GBE1 knockdown caused a decrease in cells at the G2/M phase while causing a significant increase in cells at the G0/G1 phase , indicating that GBE1 knockdown arrested the cell cycle at the G0/G1 phase. Furthermore, the results of apoptosis analysis showed that GBE1 knockdown induced apoptosis in all three glioma cell lines . These results indicate that GBE1 knockdown inhibits glioma cell proliferation, and this kind of inhibition results from cell cycle arrest coupled with increased apoptosis. 3.3. GBE1 Knockdown Affected Various Biological Behaviors of Glioma Cells To investigate whether GBE1 knockdown has additional effects on glioma, we assessed the alterations of glioma cells in biological behaviors such as migration, invasion, colony formation, and angiogenesis after GBE1 knockdown. First, a wound-healing assay was performed to assess the migration ability of glioma cells. Since the U87 cells grow in a grid-like pattern and it is difficult to form a dense cell monolayer, U251 cells and LN229 cells were selected for this assay. We found that the healing rate of ln229 and U251 cells was slowed after GBE1 knockdown compared with the negative control . Since the wound healing assay cannot evaluate tumor invasion, a more comprehensive detection of invasion and migration is necessary. Therefore, we performed transwell assays using Matrigel to mimic the extracellular matrix. The results showed that the number of all three glioma cells that successfully crossed the transwell membrane was significantly decreased after GBE1 knockdown compared with the negative control, indicating that both the migration and invasion abilities of glioma cells were inhibited after GBE1 knockdown . Furthermore, the colony formation assay results showed that the colony formation ratios of all three glioma cell lines decreased significantly after GBE1 knockdown compared to the negative control . Moreover, real-time recorded images of the tube formation assay showed that conditioned medium (CdM) from GBE1 knockdown glioma cells made HUVECs form fewer tubules compared with the negative control, indicating that GBE1 knockdown impaired the ability of glioma cells to promote angiogenesis . GBE1 is involved in multiple biological behaviors of glioma cells, including migration, invasion, colony formation, and promotion of angiogenesis, and knockdown of GBE1 will impair these biological behaviors. 3.4. GBE1 Knockdown Affected the Biological Behavior of Glioma by Regulating Various Proteins and Affected the Expression of FBP1 through the NF-kB Pathway KI67 is strongly downregulated in resting G0 cells , making it a classic indicator of cell proliferation. The immunofluorescence staining of KI67 showed that after GBE1 knockdown, the resting cells with low KI67 expression in all three glioma cell lines increased significantly , which was consistent with the results of cell cycle analysis. Since U251 cells exhibited more conspicuous and stable effects in most of the phenotypic experiments, including the CCK-8 assay, apoptosis detection, wound healing assay, and transwell invasion assay, this suggests that U251 cells were more vulnerable to GBE1 in cell proliferation, apoptosis, migration, invasion, and other classical phenotypes. Hence, we opted for U251 cells to further validate the expression of these phenotype-related proteins. We extracted the total protein of the GBE1 knockdown group and the negative control for western blot analysis. Cyclin D1 is a cell cycle-related protein whose reduced expression will lead to cell cycle arrest in the G1 phase . Compared to the negative control, the expression of cyclin D1 was significantly reduced after GBE1 knockdown, which further proved that GBE1 knockdown could transform glioma cells into a resting state and inhibit proliferation . The WB results also showed that GBE1 knockdown caused the downregulation of the invasion-related protein MMP9, the angiogenesis-related protein HIF1a, VEGFa, and the apoptosis inhibitor protein Bcl-2, and increased the expression of Bax and Cleaved-Caspase-3, further confirming the node role of GBE1 in the regulation of the biological behavior of glioma . GBE1 was found to cause promoter methylation of the FBP1 gene in lung adenocarcinoma cells through the NF-kB pathway, which decreased the expression of the FBP1 protein . In glioma, we also observed that knockdown of GBE1 significantly inhibited the phosphorylation level of p65 protein, accompanied by elevated FBP1 expression . To further investigate the relationship between GBE1, the NF-kB pathway, and FBP1, an NF-kB inhibitor was used to treat U251 cells to mimic NF-kB inhibition caused by GBE1 knockdown, and the expression of FBP1 after treatment was examined. QNZ, a neuroprotective inhibitor of the SOC channel, strongly inhibits NF-kB transcriptional activation . The results of WB showed that QNZ (1 mM) decreased the level of phosphorylated p65 protein in U251 cells, while the total amount of p65 remained unchanged. And FBP1 levels were significantly elevated after QNZ treatment compared to vehicle control , which paralleled the effect of GBE1 knockdown, indicating that the conclusion that GBE1 regulates FBP1 expression through the NF-kB pathway is also applicable in gliomas. 3.5. FBP1 Suppressed Malignant Phenotypes of Glioma Cells As a tumor suppressor, FBP1 plays a critical role in the progression of multiple tumors . Given that previous results showed GBE1 negatively regulated FBP1 expression in U251 cells , to further verify the role of FBP1 in gliomas, we constructed U251 cells with FBP1 knockdown (sh-FBP1) and FBP1 overexpression (oe-FBP1). The knockdown and overexpression efficiencies were detected by Western blot . The results of the CCK-8 assay showed that FBP1 knockdown accelerated U251 cell proliferation, while FBP1 overexpression inhibited the proliferation of U251 cells . Additionally, wound healing assays showed that, compared to the sh-NC group, FBP1 knockdown significantly accelerated U251 cell migration and nearly closed the wound after 48 h migration. Conversely, compared to the oe-NC group, FBP1 overexpression significantly slowed the wound healing rate . Further, transwell assays also showed that FBP1 knockdown significantly increased the number of cells that crossed the transwell membrane, enhancing U251 cell migration and invasion abilities, while FBP1 overexpression inhibited U251 cell migration and invasion . These results indicate that FBP1 is an unfavorable factor for glioma cell proliferation, migration, and invasion. Increasing FBP1 expression helps to suppress these malignant phenotypes in glioma cells. 3.6. FBP1 Knockdown Reversed the Glioma Inhibition Caused by GBE1 Knockdown To investigate whether GBE1 regulates glioma progression through FBP1, we constructed U87 and U251 cell lines in which both GBE1 and FBP1 were knocked down and observed whether the inhibition of glioma by single GBE1 knockdown could be reversed. The knockdown efficiency was verified by qPCR and WB, which showed that in the GBE1 and FBP1 knockdown group of U251 cells, the mRNA and protein content of FBP1 returned to the levels of the negative control . In U87 cells, it was even lower than the negative control . The results of the CCK-8 assay showed significantly enhanced cell viability in the group with knockdowns of both GBE1 and FBP1 compared with the single GBE1 knockdown group, even exceeding the negative control . Meanwhile, the results of cell cycle analysis and apoptosis analysis revealed that the knockdown of FBP1 could reverse the cell cycle arrest and apoptosis caused by GBE1 knockdown, indicating that FBP1 knockdown significantly promoted tumor proliferation, demonstrating the powerful tumor suppressive effect of FBP1 . Further studies revealed that glioma cells with knockdowns of both GBE1 and FBP1 showed a significant rebound in migration, invasion, vascularization, and colony formation ability compared with single GBE1 knockdowns . Furthermore, the results of WB from U251 cells showed that changes in proteins related to tumor biological behaviors caused by single GBE1 knockdown were also reversed after FBP1 knockdown, which was paralleled to the alterations in tumor phenotypes . These results suggest that the glioma suppressive effect caused by GBE1 knockdown is associated with increased expression of FBP1, and that knockdown of FBP1 will greatly impair this effect. 3.7. Elevated FBP1 Expression Caused by GBE1 Knockdown Induced Metabolic Reprogramming of Glioma Cells To further investigate why FBP1 inhibited glioma progression, considering the important role of FBP1 in glucose metabolism, we speculated that the glucose metabolic system of glioma cells was affected after GBE1 knockdown, which in turn inhibited glioma progression. Herein, we examined the extracellular acidification rate (ECAR), which reflects the glycolysis level of cells, using the Agilent Seahorse cell metabolic analysis system. The results showed that the basal glycolysis level and the glycolytic reserve capacity of U87 and U251 cells were inhibited after GBE1 knockdown. However, the knockdown of FBP1 reversed the inhibition of glycolysis caused by GBE1 knockdown, indicating that the increased expression of FBP1 is an important reason for the impaired glycolysis of glioma cells caused by GBE1 knockdown . In addition, to evaluate the respiratory capacity of mitochondria, we also detected the cellular oxygen consumption rate (OCR). The results showed that GBE1 knockdown increased the basal respiration level and spare respiration capacity of mitochondria in both glioma cell lines. However, FBP1 knockdown had a limited effect on mitochondrial respiratory function, suggesting that other substances in addition to FBP1 are involved in the elevated mitochondrial respiration caused by GBE1 knockdown . To further verify the alteration of the metabolic pattern of glioma cells caused by GBE1 knockdown, we performed oxygen deprivation assays in U87 and U251 cells. According to the results of the CCK-8 assay, after 24 h of hypoxia, the viability of U87 cells in the control group decreased by 7.74%, whereas that of U87 cells in the GBE1 knockdown group decreased by 29.15%. Additionally, the viability of U251 cells in the control group decreased by 18.25%, compared to a 33.79% decrease in the viability of U251 cells in the GBE1 knockdown group. These results showed that after GBE1 knockdown, the tolerance of glioma cells to an anoxic environment was significantly reduced, which reflected the transformation of cellular metabolic patterns from glycolysis to oxidative phosphorylation after GBE1 knockdown . These results indicate that GBE1 knockdown changes the metabolic mode of glioma cells from glycolysis to mitochondrial oxidative phosphorylation, and increased expression of FBP1 plays an important role in weakening the glycolysis level of glioma cells. 3.8. GBE1 Knockdown Significantly Inhibited the Growth of Glioma Xenograft In Vivo To further investigate the effect of GBE1 knockdown on the growth of glioma cells in vivo, U87 cells carrying a luciferase reporter were transplanted into the striatum of nude mice at day four after sh-GBE1 or sh-NC lentivirus infection. The optical density values of xenografts were recorded every seven days by IVIS in vivo optical imaging system measurements . The results of the bioluminescence imaging showed that the elimination of GBE1 significantly inhibited the growth of U87-derived xenografts and conferred a significant survival benefit compared to negative controls . These results demonstrated that GBE1 knockdown effectively inhibited glioma growth in vivo and improved animal survival. 4. Discussion Due to the heterogeneity of tumor cells, targeting molecules are not expressed in all tumor cells, making targeting therapies impaired and often unsatisfactory. However, metabolic abnormalities are a common feature of tumor cells , making targeting tumor metabolism a different idea for treating glioma. Our study found elevated expression of GBE1 in gliomas and a correlation with a poor prognosis. Furthermore, our findings validated the mechanism by which GBE1 affects glucose metabolism patterns for the first time in glioma . As one of the causes of glycogen metabolic diseases, recent studies have revealed that GBE1 affects the development and progression of a variety of tumors, such as leukemia, lung adenocarcinoma, and ovarian cancer . However, the role of GBE1 in glioma is still unclear. Therefore, we analyzed TCGA and CGGA data and found that GBE1 expression was elevated in gliomas and correlated with a poor prognosis. Furthermore, GBE1 was more reliable than KI67 in predicting glioma grade. This was demonstrated when using respective cut-off values for both indexes; GBE1 showed a 20.59% higher specificity than KI67, although both had a sensitivity of 79.72%. In vitro, we found increased apoptosis, arrested cell cycle, and suppressed cell proliferation in glioma cells with GBE1 knockdown. Additionally, GBE1 knockdown also affected glioma cell migration, invasion, colony formation, and angiogenesis abilities. The impairment of these biological behaviors greatly affected the progression of glioma. FBP1, the rate-limiting enzyme of gluconeogenesis, is generally considered a tumor suppressor and shows decreased expression in various tumors, such as renal, prostate, liver, and breast cancer . In lung adenocarcinomas, GBE1 methylates the promoter of FBP1 through the NF-kB pathway and therefore decreases FBP1 expression . Our results showed that the NF-kB pathway was inhibited following GBE1 knockdown in glioma cells, accompanied by elevated FBP1 expression; this paralleled the effects of single NF-kB pathway inhibitors, suggesting that regulation of FBP1 expression by GBE1 via NF-kB is also applicable in glioma. Despite the inhibitory effects of FBP1 on various tumors, it has also been shown that reduced FBP1 expression inhibits ovarian cancer formation and cisplatin resistance in vivo . Furthermore, FBP1 promotes the proliferation, migration, and invasion of esophageal cancer cells by regulating fatty acid metabolism . This suggests that the effects of FBP1 on tumors are multifaceted. Our study confirmed that in glioma cells, FBP1 expression was significantly elevated after GBE1 knockdown. Recently, a study by Son B et al. found that radiation-induced downregulation of FBP1 expression promotes GBM cell migration . Our study found that knockdown of FBP1 promoted the proliferation, migration, and invasion of glioma cells, while overexpression of FBP1 in glioma cells significantly inhibited the malignant phenotype of glioma cells, which paralleled the previous study. In contrast, knockdown of the elevated FBP1 based on GBE1 knockdown restored glioma cell proliferation and impaired tumor biological behavior. The inhibition of glioma caused by GBE1 knockdown was reversed. The above results illustrated that NF-kB pathway inhibition by GBE1 knockdown resulted in elevated FBP1, leading to glioma suppression. The Warburg effect, characterized by aerobic glycolysis, promotes cancer progression and generates many glycolytic intermediates that satisfy multiple anabolic reactions in cells . Based on these theories, many studies targeting aerobic glycolysis have shown good tumor suppressive effects , exhibiting the potential of targeting tumor metabolism in tumor therapy. Our study found that FBP1 elevation by GBE1 knockdown suppressed the basal glycolytic rate and the glycolytic reserve capacity of glioma cells; this parallels a previous study on lung adenocarcinoma . Hypoxia is one of the characteristics of the tumor microenvironment. GBE1 knockdown glioma cells in a hypoxic environment exhibit a malfunction in converting oxidative phosphorylation to glycolysis and a decreased tolerance to a hypoxic environment. However, unlike lung adenocarcinoma, GBE1 knockdown increased oxidative phosphorylation in glioma cells and was difficult to reverse with FBP1 knockdown. This phenomenon has also been found in colon cancer and melanoma. Knockdown of glucose-6-phosphate isomerase caused glycolytic inhibition in colon cancer and melanoma cells while elevating the level of oxidative phosphorylation, which investigators consider to be a compensatory response of cells to glycolytic inhibition . However, studies have found a direct inhibition of fructose-1,6-bisphosphate (F16bp), a substrate of FBP1, in rat liver mitochondria . Although this explains the elevated oxidative phosphorylation caused by GBE1 knockdown, it cannot explain the inability to reverse this elevation by the knockdown of FBP1. Therefore, further investigation is needed to determine whether the increased level of oxidative phosphorylation caused by GBE1 knockdown is a compensatory response of cells to the inhibition of glycolysis or the influence of other factors. However, it is undeniable that the elevation of oxidative phosphorylation increases the dependency of glioma cells on oxygen and impairs their tolerance to hypoxia, which is beneficial for the treatment of glioma. Furthermore, the intracranial tumor formation assay also validated the inhibitory effect of GBE1 knockdown in a complex tumor microenvironment. Additionally, GBE1 knockdown conferred a significant survival benefit compared to controls. 5. Conclusions Our study found that GBE1 expression was significantly elevated in gliomas and was correlated with a poor prognosis. GBE1 downregulates FBP1 expression through the NF-kB pathway, causing a shift in the glucose metabolism pattern of glioma cells to glycolysis, enhancing the Warburg effect, and promoting the development of glioma. These findings provide a new potential target for glioma treatment in the metabolic field. Acknowledgments The authors thank the Scientific Research Center of Wenzhou Medical University for the consultation and availability of the instruments that supported this work. The authors would like to thank all the researchers who participated in this study. Supplementary Materials The following supporting information can be downloaded at: Figure S1: FBP1 knockdown in U87 cells reversed the tumor suppression caused by GBE1 knockdown. Figure S2: Original western blots. Click here for additional data file. Author Contributions Z.C., L.X., H.B., J.L. and P.Z. performed main experiments, and analyzed the data, under the direction of Q.Z. and J.Y.; H.W., X.H. and Y.Z. performed part of experiments. Q.Z. and J.Y. designed experiments and supervised the study. Z.C. and J.Y. wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement This study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University (protocol code: 2021 Research Ethics Review No. (R129) and date of approval: 29 November 2021). The animal study protocol was approved by the Ethics Committee in Animal of the First Affiliated Hospital of Wenzhou Medical University (protocol code: 2021-0214, date of approval: 19 July 2021). Informed Consent Statement Written informed consent has been obtained from the patients to publish this paper. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest The authors declare no potential conflicts of interest. Figure 1 GBE1 expression was associated with the malignancy of gliomas. (A) Differential expression analysis of GBE1 in gliomas according to the GEPIA database (n-LGG = 518; n-GBM = 163; n-Normal = 207). (B) Overall Survival and (C) Disease-Free Survival of patients with GBE1-Low and GBE1-High gliomas according to the GEPIA database (n-low = 338; n-high = 338). GBE1 expression is classified by WHO grade, IDH mutation status, and 1p/19q co-deletion in the TCGA (n = 584) (D-F) and CGGA (n = 686) (G-I) databases. (J,K) Representative images of IHC staining for GBE1 in glioma specimens and adjacent normal specimens. Scale bar: 50 mm (below). (L) ROC curves for distinguishing glioma grade using GBE1 and Ki67 according to the TCGA (n = 584) database, GBE1: AUC = 0.8915; cut-off value = 3.035 (FPKM); sensitivity = 79.72%; specificity = 83.71%, KI67: AUC = 0.7421; cut-off value = 1.297 (FPKM); sensitivity = 79.72%; specificity = 63.12%. Data are presented as mean +- SD (ns p > 0.05; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001). Figure 2 GBE1 knockdown inhibited glioma cell proliferation and induced cell cycle arrest and apoptosis. (A) The knockdown efficiency of two different lentiviral sequences analyzed by qRT-PCR in U87, LN229, and U251 cell lines (n = 3). (B,C) The knockdown efficiency of two different lentiviral sequences was analyzed by Western blot in three glioma cell lines (n = 3). Original blot see Supplementary Materials. (D) Cell viability of three glioma cell lines with GBE1 knockdown compared to the negative control. The OD 450 value was measured by the CCK-8 assay (n = 6). (E,F) Cell cycle analysis of three glioma cell lines with GBE1 knockdown compared to the negative control. Blue in the histogram represents the G0/G1 phase, yellow represents the S phase, and green represents the G2/M phase. (G,H) Apoptosis detection of the three glioma cell lines with GBE1 knockdown compared to the negative control. The sum of the Q2 and Q3 regions was considered the proportion of apoptotic cells. Cell cycle and apoptosis were detected by flow cytometry (n = 3). Data are presented as mean +- SD (* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001). Figure 3 Knockdown of GBE1 affected various biological behaviors of glioma cells. (A,B) Wound healing assay of negative control and GBE1 knockdown ln229 and U251 cells. Photographs were taken every 12 h, and representative images at 0 h, 24 h, and 48 h were selected for presentation. The reduction area of the scratch was calculated as the wound healing area (n = 3). Scale bar: 500 mm. (C,D) Transwell assay of U87, ln229, and U251 cells of the negative control and GBE1 knockdown groups (n = 3). Five fields from top to bottom were selected for each chamber, and the average number of cells from three independent experiments was calculated. Scale bar: 100 mm. (E,F) Colony formation assay of three glioma cell lines transfected with sh-GBE1 compared with the negative control (n = 3). Colony formation ratio = amount of colonies/number of seeded cells. (G,H) Representative real-time images of tube formation assay. Human umbilical vein endothelial cells (HUVECs) were cultured with conditioned media collected from three glioma cell lines with GBE1 knockdown and a negative control (n = 3). Scale bar: 250 mm. Data are presented as mean +- SD (* p < 0.05; ** p < 0.01; *** p < 0.001). Figure 4 GBE1 knockdown affected the biological behavior of gliomas by regulating various proteins and affecting the expression of FBP1 through the NF-kB pathway. (A,B) Immunofluorescence staining of Ki67 in U87, ln229, and U251 cells (n = 3). Three fields from top to bottom were selected for each well, and the average of three independent wells was calculated. Scale bar: 100 mm. (C,D) Expression of tumor behavior-related proteins in GBE1 knockdown U251 cells compared with the negative control (n = 3). The protein levels of HIF1a, MMP-9, VEGFA, Bax, and Bcl-2 were normalized to GAPDH. Cyclin D1 and cleaved caspase-3 were normalized to b-Tubulin. (E,F) FBP1, total p65, and phosphorylated p65 protein levels in GBE1 knockdown U251 cells compared with single QNZ (1 mM) treatment (n = 3). Protein levels of total p65 and phosphorylated p65 were normalized to GAPDH, and FBP1 was normalized to b-Tubulin. Data are presented as mean +- SD (ns p > 0.05; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001) Original blot see Supplementary Materials. Figure 5 FBP1-suppressed malignant phenotypes of glioma cells. (A,B) The knockdown efficiency of the sh-FBP1 group and the overexpression efficiency of the oe-FBP1 group in U251 cells (n = 3) Original blot see Supplementary Materials. (C) Cellular viability of U251 cells in the FBP1 knockdown group and FBP1 overexpression group compared to the negative control. OD450 values were measured by the CCK-8 assay (n = 6). (D,E) Wound healing assay of FBP1 knockdown and FBP1 overexpression in U251 cells. Photographs were taken every 12 h, and representative images at 0 h, 24 h, and 48 h were selected for presentation. The reduced area of the scratch was calculated as the wound healing area (n = 3). Scale bar: 500 mM. (F,G) Transwell assay of FBP1 knockdown and FBP1 overexpression in U251 cells compared with the negative control (n = 3). Five fields from top to bottom were selected for each chamber, and the average number of cells from three independent experiments was calculated. Scale bar: 100 mm. Data are presented as mean +- SD (* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001). Figure 6 FBP1 knockdown reversed the glioma inhibition caused by GBE1 knockdown. (A,B) Knockdown efficiency of the sh-GBE1 group and sh-GBE1+shFBP1 group in U251 cells was detected by qRT-PCR (Left B) and Western blot (Right B) (n = 3) Original blot see Supplementary Materials. (C) The viability of U251 cells infected with sh-GBE1 or sh-GBE1 + sh-FBP1 was assessed by the CCK-8 assay (n = 6). (D-G) The effects of both GBE1 and FBP1 knockdowns on the cell cycle and apoptosis in U251 cells were assessed by flow cytometry (n = 3). (H-M) Effects of both GBE1 and FBP1 knockdown on cell colony forming ability, angiogenic ability, migration, and invasion ability of U251 cells; (H,I) colony forming ability was evaluated by colony formation assay (n = 3); colony formation ratio = amount of colonies/number of seeded cells. (J,K) Angiogenic capacity was assessed by tube formation assay, and representative images at 12 h were selected for presentation (n = 3); scale bar: 250 mm; (L,M) migration and invasion abilities were evaluated by transwell assay (n = 3); five fields from top to bottom were selected for each chamber, and the average number of cells from three independent experiments was calculated; scale bar: 100 mm. (N,O) Effects of knockdown of both GBE1 and FBP1 on the expression of proteins associated with tumor behavior in U251 cells (n = 3). Original blot see Supplementary Materials; data are presented as mean +- SD (ns p > 0.05; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001). Figure 7 Elevated FBP1 expression caused by GBE1 knockdown induces metabolic reprogramming of glioma cells. (A,B) Extracellular acidification rate (ECAR) of negative control, sh-GBE1, and sh-GBE1 + sh-FBP1 in U87 and U251 cells. The effects of GBE1 and FBP1 on basal glycolysis, glycolytic capacity, and glycolytic reserve in glioma cells were assessed by ECAR. (C,D) Oxygen consumption rate (OCR) of negative control, sh-GBE1, as well as sh-GBE1 + sh-FBP1, in U87 and U251 cells. OCR reflects basal respiration, maximal respiration, and the spare respiratory capacity of glioma cells. Both ECARs and OCRs were detected by the Agilent Seahorse metabolic assay (n = 11). (E,G) Effect of GBE1 knockdown on the viability of glioma cells under hypoxia. (F,H) Cell viability at 24 h of hypoxia was selected for statistical analysis; cell viability was detected by the CCK-8 assay (n = 6). (I) The mechanism of GBE1 regulating the Warburg effect in glioma cells. Data are presented as mean +- SD (ns p > 0.05; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001). Figure 8 Knockdown of GBE1 significantly inhibited the growth of a glioma xenograft in vivo. (A) Schematic representation of intracranial tumor implantation and in vivo bioluminescence imaging by the IVIS in vivo imaging system. (B,C) Bioluminescence images and quantification of U87-derived xenografts in the brains of nude mice after GBE1 knockdown compared to the negative control (n = 5). (D) Kaplan-Meier survival analysis of nude mice after transplantation of GBE1 knockdown U87-derived xenografts compared with the negative control (n = 5). Data are presented as mean +- SD (* p < 0.05; ** p < 0.01). 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PMC10000544 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050700 cells-12-00700 Article 11,12-EET Regulates PPAR-g Expression to Modulate TGF-b-Mediated Macrophage Polarization Li Xiaoming Investigation 1 Kempf Sebastian Methodology Investigation 1 Gunther Stefan Methodology Formal analysis Data curation 2 Hu Jiong Supervision 13 Fleming Ingrid Conceptualization Formal analysis Writing - review & editing Funding acquisition 14* Shi Weibin Academic Editor 1 Institute for Vascular Signalling, Centre for Molecular Medicine, Goethe University, 60596 Frankfurt am Main, Germany 2 Max Planck Institute for Heart and Lung Research, Bioinformatics and Deep Sequencing Platform, 61231 Bad Nauheim, Germany 3 Department of Histology and Embryology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China 4 German Center of Cardiovascular Research (DZHK), Partner Site RheinMain, 60596 Frankfurt am Main, Germany * Correspondence: [email protected] 23 2 2023 3 2023 12 5 70030 11 2022 30 1 2023 07 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Macrophages are highly plastic immune cells that can be reprogrammed to pro-inflammatory or pro-resolving phenotypes by different stimuli and cell microenvironments. This study set out to assess gene expression changes associated with the transforming growth factor (TGF)-b-induced polarization of classically activated macrophages into a pro-resolving phenotype. Genes upregulated by TGF-b included Pparg; which encodes the transcription factor peroxisome proliferator-activated receptor (PPAR)-g, and several PPAR-g target genes. TGF-b also increased PPAR-g protein expression via activation of the Alk5 receptor to increase PPAR-g activity. Preventing PPAR-g activation markedly impaired macrophage phagocytosis. TGF-b repolarized macrophages from animals lacking the soluble epoxide hydrolase (sEH); however, it responded differently and expressed lower levels of PPAR-g-regulated genes. The sEH substrate 11,12-epoxyeicosatrienoic acid (EET), which was previously reported to activate PPAR-g, was elevated in cells from sEH-/- mice. However, 11,12-EET prevented the TGF-b-induced increase in PPAR-g levels and activity, at least partly by promoting proteasomal degradation of the transcription factor. This mechanism is likely to underlie the impact of 11,12-EET on macrophage activation and the resolution of inflammation. soluble epoxide hydrolase PPAR-g macrophage resolution of inflammation 11,12-epoxyeicosatrienoic acid Deutsche ForschungsgemeinschaftGRK 2336 TP5-Project ID 321115009 SFB 1039/3 B6-Project ID 204083920 EXC 2026, Project ID: 390649896 China Scholarship CouncilThis research was funded by the Deutsche Forschungsgemeinschaft (GRK 2336 TP5-Project ID 321115009; SFB 1039/3 B6-Project ID 204083920, and the CardioPulmonary Institute, EXC 2026, Project ID: 390649896). X.L. was supported by a grant from the China Scholarship Council. pmc1. Introduction The recruitment of neutrophils and monocytes to inflamed tissue and their differentiation into macrophages is a crucial step in the inflammatory process. However, once the neutrophil respiratory burst subsides, these and other cells, i.e., macrophages, eosinophils and lymphocytes, need to be removed to restore homeostasis . To support the removal of apoptotic cells and tissue debris (efferocytosis), macrophage function is altered and the cells are reprogramed into a pro-resolving phenotype. Polarized macrophages are frequently broadly classified in two main groups, i.e., classically activated (M1) macrophages which are induced by T-helper 1 (Th-1) cytokines, i.e., the combination of bacterial lipopolysaccharide (LPS) and interferon g (IFN-g), and alternatively activated (M2) macrophages that have a pro-resolving and pro-angiogenic phenotype, and are induced by Th-2 cytokines . The latter group can be further subdivided into more refined phenotypes: M2a, M2b, M2c, and M2d depending on the use of different stimuli such as interleukin (IL)-4 (M2a) or transforming growth factor b (TGF-b) (M2c). However, the phenotypic characterization of macrophages is highly complicated and there are many more distinct genetic fingerprints and metabolic states than are reflected in a basic M0/M1/M2 classification . Indeed, additional subtypes have been identified such as macrophages stimulated by oxidized phospholipids, oxidized LDL, or hemoglobin . TGF-b is a master immune regulator and checkpoint that has a major impact on immune suppression within the tumor microenvironment . It has also been implicated in poor responsiveness to cancer immunotherapy . In inflamed tissues, macrophage TGF-b synthesis is stimulated by the uptake of apoptotic cells, a step that is essential for the repolarization of pro-inflammatory macrophages into a pro-resolving phenotype (for reviews see ). Although endothelial TGF-b signaling drives endothelial-to-mesenchymal transition and vascular inflammation , there is some controversy about the exact impact of TGF-b on atherogenesis. Rather than promoting vascular inflammation, there is evidence suggesting that TGF-b signaling plays an important role in the protection against excessive plaque inflammation, loss of collagen content, and induction of regulatory immunity (reviewed by ). The current study set out to determine changes in macrophage gene expression associated with the repolarization of classically activated (M1) macrophages into a pro-resolving phenotype by TGF-b. 2. Materials and Methods 2.1. Animals C57BL/6N mice (6-8 weeks old) were purchased from Charles River (Sulzfeld, Germany). Floxed sEH mice (Ephx2tm1.1Arte) were generated in the C57BL/6N background by TaconicArtemis GmbH (Cologne, Germany) and crossed with Gt(ROSA)26Sortm16(Cre)Arte mice (TaconicArtemis) expressing Cre under the control of the endogenous Gt(ROSA)26Sor promoter to generate mice globally lacking sEH (sEH-/-) as described . Age-, strain-matched mice were used throughout, where possible littermates were used. In cases where studying littermates was not possible, cells were isolated from age-matched C57Bl/6N mice. Preliminary experiments revealed that responses were comparable in cells from C57Bl/6N and Cre-sEHflox/flox mice and different from those of the sEH-/- (Cre+ sEHflox/flox) mice. For the isolation of bone marrow, mice were sacrificed using 4% isoflurane in air and cervical dislocation. 2.2. Monocyte Isolation and Macrophage Polarization Murine monocytes were isolated from the bone marrow of 8-10-week-old mice and differentiated to naive (M0) macrophages in RPMI 1640 medium (Invitrogen; Darmstadt, Germany), containing 8% heat inactivated FCS supplemented with M-CSF (15 ng/mL, Peprotech, Hamburg, Germany) and GM-CSF (15 ng/mL, Peprotech, Hamburg, Germany) for 7 days. Cells were kept in a humidified incubator at 37 degC containing 5% CO2. Thereafter M0 macrophages were polarized to classical activated M1 macrophages by treating with LPS (10 ng/mL; Sigma-Aldrich, Munich, Germany) and IFN-g (1 ng/mL; Peprotech, Hamburg, Germany) for 12 h. Pro-resolving M2c macrophages were repolarized from M1 macrophages by the addition of TGF-b1 (10 ng/mL; Peprotech, Hamburg) for 48 h, as described . 2.3. RNA Isolation and Quantitative Real Time PCR (RT-qPCR) Total RNA was extracted and purified from murine macrophages using Tri Reagent (ThermoFisher Scientific, Karlsruhe, Germany) based on the manufacturer's instructions. Thereafter, RNA was eluted in nuclease-free water, and its concentration was determined (l260 nm) using a NanoDrop ND-1000 (ThermoFischer Scientific, Karlsruhe, Germany). For the generation of complementary DNA (cDNA), total RNA (500 ng) was reverse transcribed using SuperScript IV (ThermoFischer Scientific, Karlsruhe, Germany) with random hexamer primers (Promega, Madison, WI, USA). Quantitative PCR was performed using SYBR green master mix (Biozym, Hessisch Oldendorf, Germany) and appropriate primers (Table 1) in a MIC-RUN quantitative PCR system (Bio Molecular Systems, Upper Coomera, Australia). Relative RNA levels were determined using a serial dilution of a positive control. The data are shown relative to the mean of the housekeeping gene 18S RNA. 2.4. RNA Sequencing Total RNA was isolated from macrophages by using RNeasy Micro kit (Qiagen, Hilden, Germany) based on manufacturer's instructions. The RNA concentrations were determined by using NanoDrop ND-1000 (ThermoFischer Scientific, Karlsruhe, Germany; l 260 nm). Total RNA (1 mg) was used as input for SMARTer Stranded Total RNA Sample Prep Kit-HI Mammalian (Takara Bio, Kyoto, Japan). Trimmomatic version 0.39 was employed to trim reads after a quality drop below a mean of Q20 in a window of 20 nucleotides and keeping only filtered reads longer than 15 nucleotides . Reads were aligned versus Ensembl mouse genome version mm10 (Ensembl release 101) with STAR 2.7.10a . Aligned reads were filtered to remove: duplicates with Picard 2.25.5 (Picard: A set of tools (in Java) for working with next generation sequencing data in the BAM format), multi-mapping, ribosomal, or mitochondrial reads. Gene counts were established with featureCounts 2.0.2 by aggregating reads overlapping exons on the correct strand excluding those overlapping multiple genes . The raw count matrix was normalized with DESeq2 version 1.30.1 . Contrasts were created with DESeq2 based on the raw count matrix. Genes were classified as significantly differentially expressed at average count >5, multiple testing adjusted p-value < 0.05, and log2FC > 0.585 or <-0.585. The Ensemble annotation was enriched with UniProt data . The PCA, volcano plots and pathway enrichment analysis were generated using an online platform for data analysis and visualization. 2.5. Phagocytosis Assays M1 polarized macrophages were treated with either solvent or the PPAR-g antagonist; GW9662 (10 mmol/L, Merck, Darmstadt, Germany), 2 h prior to repolarization to the M2c phenotype using TGF-b1. Thereafter, cells were incubated in RPMI medium supplement with 0.1% BSA (37 degC, 5% CO2) and containing pHrodo Red Zymosan bioparticles (10 mg/mL, Invitrogen). After 30 min the cells were washed to remove nonphagocytosed material and zymosan uptake was visualized and quantified using an automated live cell imaging system (IncuCyte, Sartorius, Gottingen, Germany). 2.6. PPAR-g Activity PPAR-g activity was measured using a luciferase construct (PPRE-X3-Luc, Addgene No. 1015) which contains 3 response elements (AGGACAAAGGTCA) upstream of a luciferase reporter . For transfection, M0 macrophages were incubated in RPMI medium containing 0.1% BSA for 2 h prior to the addition of plasmid (100 ng/mL) and Lipofectamin 3000 Transfection Reagent (ThermoFischer Scientific, Karlsruhe, Germany) according to the manufacturer's instructions. After 24 h, the cells were polarized to M1 and M2c macrophages and stimulated as described in the results section. Luciferase activity was measured 48 h after cell polarization or stimulation with 11,12-EET (1 mmol/L, Cayman Europe, Tallinn, Estonia) using a commercially available kit (ONE-Glo Luciferase Assay System, Promega, Walldorf, Germany). 2.7. Immunoblotting Cells were lysed in RIPA lysis buffer (50 mmol/L Tris/HCL pH 7.5, 150 mmol/L NaCl, 10 mmol/L NaPPi, 20 mmol/L NaF, 1% sodium deoxycholate, 1% Triton and 0.1% SDS) enriched with protease and phosphatase inhibitors and detergent-soluble proteins were resuspended in SDS-PAGE sample buffer. Samples were separated by SDS-PAGE and subjected to Western blotting as described . Membranes were blocked in 3% BSA, incubated with primary antibodies in the blocking solution and horseradish peroxidase-conjugated secondary antibodies. Protein bands were visualized using Lumi-Light plus Western blotting substrate (Roche, Mannheim, Germany) and captured by an image acquisition system (Fusion FX7; Vilber-Lourmat, Torcy, France). The antibody used to identify PPAR-g was from Santa Cruz (Texas, USA; Cat. # sc-7196, 1:1000), anti-non muscle myosin was from abcam (Berlin, Germany; Cat. # ab75590, 1:1000), and the anti b-actin antibody was from Linaris (Eching, Germany; Cat. # MAK6019, 1:3000). The secondary antibodies were used were: goat anti-rabbit IgG H and L chain specific peroxidase conjugate, and a goat anti-mouse IgG, H and L chain specific peroxidase conjugate (both 1:20,000; Cat. # 401393 and Cat. # 401253, Merck). 2.8. Statistical Analyses Data are expressed as mean +- SEM. Statistical analysis was performed using Student's t test, or two-way ANOVA with a Tukey's or Sidak's post-test. Normalized data were compared using the Kruskal-Wallis rank sum test or Kruskal-Wallis test followed and Dunn's multiple comparison test (using Prism 9.0.2, GraphPad Software Inc., San Diego, CA, USA) as indicated in the figure legends. Values of p < 0.05 were considered statistically significant. 2.9. Data and Material Availability All data associated used this study are present in the paper or the Supplementary Materials. 3. Results 3.1. Impact of TGF-b-Induced Macrophage Repolarization on Gene Expression Bone marrow-derived monocytes were isolated from wild-type mice and differentiated to naive (M0) macrophages in the presence of M-CSF and GM-CSF for 7 days. Thereafter, M0 macrophages were either polarized to classically activated (M1) macrophages by adding lipopolysaccharide (LPS) and interferon (IFN)-g for 12 h or into pro-resolving M2c by treating M1 macrophages with TGF-b1 for 48 h. RNA-sequencing (RNA-seq) was then performed to identify changes in gene expression associated with macrophage polarization. Principal component analysis (PCA) confirmed that the three groups of macrophages clustered together with clear differences between the polarization types . As expected, the expression of the classical M1 marker genes Nos2, Ptgs2, Il1b, and Nlrp3 were significantly higher in M1 versus M2c polarized macrophages. On the other hand, the typical M2/M2c markers, i.e., Arg1, Vegfa were higher in M2c than in M1 polarized macrophages . A closer analysis of the genes differentially expressed in M2c versus M1-polarized macrophages revealed additional marked differences, with TGF-b inducing the upregulation of 2952 genes and the downregulation of 2051 genes, including the pro-inflammatory genes Cxcr4, Ptgs2 and Angptl4. One of the genes whose expression was significantly increased in M2c macrophages was Pparg and gene set enrichment analysis identified changes in the expression of several targets of the peroxisome proliferator-activated receptor (PPAR) family of transcription factors . PPAR-g-regulated genes induced by TGF-b included Angptl4, Abcd2, Eepd1 and Tmem8. 3.2. TGF-b-induced M2c Macrophage Polarization Relies on PPAR-g and Alk5 Activation To determine the importance of PPAR-g on the regulation of selected macrophage genes, we determined the impact of the PPAR-g antagonist GW9662 on the expression of three selected genes in M2c macrophages, i.e., Cxcr4 (higher in M2c), as well as Ptgs2 and Ptx3 (both higher in M1). While there was no significant effect of PPAR-g antagonism on Cxcr4 expression, cells treated with GW9662 expressed significantly higher levels of Ptgs2 and Ptx3 than cells treated with solvent . One characteristic of the latter cells is their ability to phagocytose cell debris. While M2c polarized murine macrophages effectively phagocytosed zymosan, particle uptake was clearly reduced in cells treated with the PPAR-g antagonist . These observations imply that PPAR-g activation is required for the down regulation of some pro-inflammatory genes as well as to support the induction of a pro-resolving phenotype by TGF-b. Consistent with the latter observations, PPAR-g expression was significantly elevated in M2c versus M1 or M0 macrophages . Given that M2c polarization was induced by adding TGF-b to M1 polarized macrophages, we determined which TGF-b type I receptor, i.e., activin receptor-like kinase (Alk) 1 or Alk5, mediated the TGF-b-induced increase in PPAR-g levels. While neither solvent, nor the Alk1 inhibitor; LDN193189 prevented the TGF-b-induced increase in PPAR-g , the response was abolished in macrophages pretreated with the Alk5 inhibitor; SD208. 3.3. PPARg Activity in Differentially Polarized Macrophages from Wild-Type and sEH-/- Mice Next, we set out to determine whether or not mediators known to regulate PPAR-g were implicated in the TGF-b-induced changes in PPAR levels and gene expression. Given that arachidonic acid metabolism was one of the pathways altered by TGF-b , we focused on the role of the potential role of arachidonic acid epoxides. These fatty acid mediators; such as 11,12-epoxyeicosatrienoic acid (11,12-EET), are reported to activate PPAR-g , and their cellular levels are largely determined by the activity of the soluble epoxide hydrolase (sEH). Therefore, a luciferase construct containing three PPAR-g responsive elements was expressed in macrophages from wild-type mice that were then polarized to the M1 and M2c phenotypes. Consistent with the increase in PPAR-g protein levels, luciferase activity was clearly increased in the M2c macrophages from wild-type mice . Deletion of the sEH significantly blunted the latter response, which was reflected in the differential expression of PPAR-g-regulated genes in M2c macrophages from the two genotypes . Indeed, the well-characterized PPAR-g-regulated genes Gipr, Vldlr, and Rbp1 were all expressed at significantly lower levels in M2c macrophages from sEH-/- versus wild-type mice. A series of fatty acid epoxides are metabolized by the sEH and it was possible to demonstrate higher 11,12-EET and lower levels of its sEH-generated diol; 11,12-dihydroxyeicosatrienoic acid (11,12-DHET), in M2c polarized macrophages from sEH-/- versus wild-type mice . Moreover, treating M1 polarized macrophages from wild-type mice with 11,12-EET prior to the repolarization with TGF-b, also decreased PPAR-g activity . 3.4. Regulation of PPAR-g Levels by 11,12-EET Comparison of the effects of 11,12-EET versus those of its diol; 11,12-DHET on PPAR-g protein levels were assessed next. This revealed that the sEH substrate; 11,12-EET, effectively prevented the TGF-b-induced increase in PPAR-g protein levels in murine macrophages . 11,12-DHET had no effect. Somewhat unexpectedly, 11,12-EET altered PPAR-g protein levels without altering Pparg expression indicating that 11,12-EET may affect the stability of the PPAR-g protein. At least in adipocytes, ligand-dependent PPAR-g activation is associated with its subsequent proteasomal degradation . To determine whether or not 11,12-EET decreased PPAR-g levels by stimulating its proteasomal degradation, experiments were performed in the absence and presence of the proteasome inhibitor MG132. As before, 11,12-EET, but not 11,12-DHET, decreased PPAR-g protein levels in M2c polarized macrophages and proteasome inhibition prevented the effect . 4. Discussion The results of this investigation revealed that the TGF-b-dependent repolarization of classically activated (M1) macrophages into a pro-resolving, highly phagocytic phenotype (M2c), relies on the increased expression and activation of PPAR-g. Deletion of the sEH, to increase cellular levels of fatty acid epoxides, largely prevented TGF-b-induced changes in macrophage gene expression as well as PPAR-g activation. The effect seen in macrophages from sEH-/- was reproduced in cells from wild-type mice treated with the sEH substrate 11,12-EET and was attributed, at least in part, to the accelerated proteasomal degradation of PPAR-g. In our study, we set out to determine changes in macrophage gene expression associated with the repolarization of classically activated (M1) macrophages into a pro-resolving phenotype by TGF-b. It is not surprising that repolarization resulted in marked alterations in macrophage gene expression and a decrease in the expression of pro-inflammatory markers. However, the observation that many of the genes increased in TGF-b-treated macrophages were classical PPAR-g targets, e.g., Abcd2, Eepd1, and Tmem8 was unexpected as TGF-b is a multifunctional cytokine that drives inflammation, fibrosis and cell differentiation, while PPAR-g activation tends to promote the opposite effects . The impact of TGF-b on gene expression was however consistent with its ability to increase PPAR-g protein levels as well as transcription factor activity. The changes in gene expression were reflected in functional alterations as zymosan phagocytosis by TGF-b-repolarized macrophages was clearly attenuated in cells treated with a PPAR-g inhibitor. Our results are consistent with recent reports from other groups that linked the actions of TGF-b with the activation of PPAR-g signaling (reviewed by ). For example, TGF-b signaling and the upregulation of PPAR-g was reported to be essential for the development and homeostasis of alveolar macrophages . On the other hand, PPAR-g was reported to interact with Stat3 and Smad3 to interfere with TGF-b signaling and account for the functional antagonism between BMP2 and TGF-b1 pathways in vascular smooth muscle cells . Thus, it seems likely that a complex crosstalk exists between the two pathways. The results of our study also indicate that in macrophages, the TGF-b-induced increase in PPAR-g expression relies on the activation of Alk5 and as such fits well with a previous report that TGF-b induces M2-like macrophage polarization via Snail-mediated suppression of a pro-inflammatory phenotype, as the induction of Snail is also mediated by Alk5 . PPARs are ligand-inducible transcription factors and are considered important therapeutic targets as they exert anti-atherogenic and anti-inflammatory effects on the vascular wall and immune cells, as well as acting to reduce insulin resistance and dyslipidaemia . However, unlike many receptors that possess a limited number of ligands, there are numerous natural PPAR-g ligands, in particular mediators derived from polyunsaturated fatty acids . The EETs are among the latter compounds and are generated by the sequential action of cytochrome P450 enzymes and the sEH . These fatty acid mediators are particularly interesting given that their actions have been attributed to PPAR activation , and the inhibition or deletion of the sEH to increase EET levels has anti-atherosclerotic effects in mouse models . In our study, we observed that the activity of PPAR-g was lower in TGF-b-stimulated macrophages from sEH-/- (EET high) than from wild-type (EET low) mice. While these findings were consistent with the clearly decreased levels of PPAR-g protein in sEH-deficient macrophages, they seemed to be a direct contradiction of previous reports. The timing of the experiments performed can go a long way to accounting for the observations made as PPAR-g activity was generally assessed 48 h after TGF-b addition or stimulation with 11,12-EET. Thus, 11,12-EET probably initiates a transient increase in PPAR-g activity that is terminated by an EET-stimulated pathway that results in PPAR-g degradation. Given that PPAR-g levels were not decreased by 11,12-EET in cells treated with MG 132 we propose that 11,12-EET can stimulate the proteasomal degradation of PPAR-g. Certainly, PPAR-g levels can be regulated by protein ubiquitination and degradation . Which ubiquitin ligase was activated by 11,12-EET was not studied but there is circumstantial evidence to link 11,12-EET with increased ubiquitination as the cardiomyocyte-specific overexpression of CYP2J2, which generates 11,12-EET and has been reported to promote the ubiquitination of the pattern recognition receptor NLRX1 . Taken together, our results indicate that macrophage levels of the sEH substrate; 11,12-EET, can modulate macrophage polarization by TGF-b, at least partly by promoting the ubiquitination and degradation of PPAR-g. Given that sEH inhibition prevents the development of atherosclerosis in mice , and the conversion of inflammatory macrophages to the M2 phenotype drives atherosclerosis regression , it may be interesting to determine how much of the phenotype observed can be attributed to changes in PPAR-g expression. Acknowledgments Authors are indebted to Oliver Haun for expert technical assistance. Supplementary Materials The following supporting information can be downloaded at: Table S1: Differentially expressed genes in M0, M1 and M2c macrophages from wild-type mice; Table S2: Differentially expressed genes in M2c macrophages from wild-type and sEH-/- mice. Click here for additional data file. Author Contributions Conceptualization, X.L. and I.F.; methodology, X.L., S.K. and J.H.; data analysis, X.L. and S.G.; writing--review and editing, I.F.; visualization, X.L.; supervision, J.H. and I.F.; project administration and funding acquisition, I.F. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All animals were housed in conditions that conform to the Guide for the Care and Use of Laboratory Animals published by the U.S. National Institutes of Health (NIH publication No. 85-23). Informed Consent Statement Not applicable. Data Availability Statement All the data are provided in the paper and its Supplementary Materials. Conflicts of Interest Authors declare no conflict of interest. Figure 1 Impact of TGF-b-induced macrophage repolarization on gene expression. (A) Principle component analysis showing the clustering of RNA-seq samples from differentially polarized (M0, M1 and M2c) macrophages from wild-type (WT) mice; n = 4 mice/group. (B) Volcano plot showing differentially expressed genes in M1 and M2c polarized. Blue = genes significantly downregulated and red = genes significantly upregulated in M2c versus M1 macrophages. (C) Gene set enrichment analysis of gene expression in M1 and M2c macrophages. Figure 2 M2c macrophage polarization relies on PPARg activation. (A) Expression of Cxcr4, Ptgs2 and Ptx3 in M2c polarized macrophages from wild-type mice treated with solvent (0.1% DMSO) or the PPAR-g antagonist; GW9662 (10 mmol/L) 2 h prior to the addition of TGF-b (n = 3 independent experiments, Student's t test). (B) Zymosan phagocytosis by M2c macrophages treated as in A. Images were taken 30 min after zymosan addition and the white boxes indicate the area magnified in the lower panels; bar = 200 mm (n = 5/group, Kruskal-Wallis rank sum test). ** p < 0.01, *** p < 0.001, **** p < 0.0001. Figure 3 TGF-b-regulated PPAR-g expression depends on the activation of Alk5. (A) Expression of PPAR-g in M0, M1, and M2c polarized macrophages from wild-type mice; n = 5 independent experiments (Kruskal-Wallis test followed and Dunn's multiple comparisons test). Non muscle myosin (NMM) was included as an additional loading control. (B) Expression of PPARg in M1 polarized murine macrophages treated with solvent (0.1% DMSO), the Alk1 inhibitor; LDN193189 (100 nmol/L), or the Alk5 inhibitor; SD208 (500 nmol/L) for 2 h prior to the addition of TGF-b for M2c polarization; n = 4 independent experiments/group (two way ANOVA and Sidak's multiple comparisons test). * p < 0.05, ** p < 0.01, *** p < 0.001. Figure 4 PPAR-g activity in differentially polarized macrophages from wild-type and sEH-/- mice. (A) Activity of a PPAR-g-luciferase construct in M0, M1, and M2c macrophages from wild-type (WT) and sEH-/- (-/-) mice; n = 5 independent experiments (two way ANOVA and Tukey's multiple comparisons test). (B) Volcano plot showing the expression of known PPAR-g-regulated genes in M2c macrophages from wild-type (WT) and sEH-/- mice. Dataset as in Figure 1; n = 4 independent experiments. Blue = genes significantly downregulated and red = genes significantly upregulated in sEH-/- mice versus wild-type. Grey indicates no significant alteration. (C) 11,12-EET and 11,12-DHET levels in M2c macrophages from wild-type and sEH-/- (-/-) mice (n = 5 independent experiments; Student's t test). (D) PPAR-g activity in M2c polarized macrophages from wild-type mice treated with solvent (0.1% DMSO) or 11,12-EET (1 mmol/L, 30 min prior to TGF-b). Solvent-treated cells from sEH-/- mice were included as control; n = 5 independent experiments (Kruskal-Wallis test followed and Dunn's multiple comparisons test). * p < 0.05, ** p < 0.01, **** p < 0.0001. Figure 5 Regulation of PPAR-g levels by 11,12-EET and 11,12-DHET in M2c polarized macrophages from wild-type mice. (A) Impact of solvent (Sol, 0.1% DMSO), 11,12-EET or 11,12-DHET (both 1 mmol/L; 30 min prior to TGF-b) on the expression of PPAR-g in M2c polarized macrophages (n = 5 independent experiments, Kruskal-Wallis test followed and Dunn's multiple comparisons test). (B) PPAR-g mRNA levels in cells treated with solvent, 11,12-EET and 11,12-DHET as in panel a (n = 4 independent experiments, Kruskal-Wallis test followed and Dunn's multiple comparisons test). (C) Consequence of inhibiting protein degradation using MG132 (2 mmol/L, 1 h pretreatment) on PPAR-g protein stability in M2c polarized macrophages treated with solvent (Sol, 0.1% DMSO), 11,12-EET or 11,12-DHET (both 1 mmol/L) 1 h prior to the addition of TGF-b (n = 3 independent experiments, two way ANOVA and Sidak's multiple comparisons test). * p < 0.05, ** p < 0.01. cells-12-00700-t001_Table 1 Table 1 PCR primers used. 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PMC10000545 | (1) Background. The purpose of this study is to evaluate the diagnostic accuracy of a quantitative analysis of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI of mucinous ovarian cancer (MOC). It also aims to differentiate between low grade serous carcinoma (LGSC), high-grade serous carcinoma (HGSC) and MOC in primary tumors. (2) Materials and Methods. Sixty-six patients with histologically confirmed primary epithelial ovarian cancer (EOC) were included in the study. Patients were divided into three groups: MOC, LGSC and HGSC. In the preoperative DWI and DCE MRI, selected parameters were measured: apparent diffusion coefficients (ADC), time to peak (TTP), and perfusion maximum enhancement (Perf. Max. En.). ROI comprised a small circle placed in the solid part of the primary tumor. The Shapiro-Wilk test was used to test whether the variable had a normal distribution. The Kruskal-Wallis ANOVA test was used to determine the p-value needed to compare the median values of interval variables. (3) Results. The highest median ADC values were found in MOC, followed by LGSC, and the lowest in HGSC. All differences were statistically significant (p < 0.000001). This was also confirmed by the ROC curve analysis for MOC and HGSC, showing that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC (p < 0.001). In the type I EOCs, i.e., MOC and LGSC, ADC has less differential value (p = 0.032), and TTP can be considered the most valuable parameter for diagnostic accuracy (p < 0.001). (4) Conclusions. DWI and DCE appear to be very good diagnostic tools in differentiating between serous carcinomas (LGSC, HGSC) and MOC. Significant differences in median ADC values between MOC and LGSC compared with those between MOC and HGSC indicate the usefulness of DWI in differentiating between less and more aggressive types of EOC, not only among the most common serous carcinomas. ROC curve analysis showed that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC. In contrast, TTP showed the greatest value for differentiating between LGSC and MOC. magnetic resonance diffusion-weighted imaging (DWI) magnetic resonance dynamic contrast enhancement (DCE) mucinous ovarian cancer (MOC) low-grade serous ovarian cancer (LGSC) high-grade serous ovarian cancer (HGSC) This research received no external funding. pmc1. Introduction Epithelial ovarian cancer (EOC) is one of the most common malignancies in women worldwide. Due to the lack of early clinical symptoms and screening options, it ranks fourth among causes of cancer deaths worldwide . EOC has been divided into two types depending on molecular and clinicopathological factors. Type I is less common and includes subtypes such as low-grade serous carcinoma (LGSC), mucinous ovarian carcinoma (MOC), endometrioid carcinoma and clear cell carcinoma. Type II is high-grade serous carcinoma (HGSC) and is the leading malignant tumor of the ovary . The histologic type of EOC, optimal cytoreductive surgery and platinum-based, adjuvant chemotherapy are considered prognostic factors . MOC is a rare type of ovarian cancer, with an estimated incidence of 3-12% of all EOCs. Typically, MOC grows slowly and is confined to the ovary at the time of diagnosis . It is the most common type of EOC in women under 40 years of age . According to the National Cancer Institute, 51% of HGSC cases are diagnosed in stage III and in 29% in stage IV, according to FIGO . In MOC, 80% of cases are recognized in stage I, according to FIGO . In the early clinical stages, MOC has a better prognosis than HGSC, while in advanced cases, the prognosis is worse, due to poor response to platinum-based chemotherapy . According to the European Society of Uro-Genital Radiology (ESUR) guidelines, preoperative staging of EOC includes contrast enhanced computed tomography (CT) of the chest, abdomen and pelvis . Magnetic resonance imaging (MRI) can provide more comprehensive information than CT on diagnosis of EOC, especially about the local extent of the disease. Compared with CT, MR diffusion-weighted imaging (DWI) combined with apparent diffusion coefficients (ADC) has shown promise not only in tumor staging, but also in assessing tumor type and predicting the clinical course of the disease . Dynamic contrast enhanced (DCE) MRI improves the diagnostic accuracy of conventional MRI. In addition, there are studies that DCE can be useful in differentiating between highly and low aggressive EOC . Furthermore, some studies have proposed the use of perfusion MRI as a prognostic tool in EOC . However, these studies concerned serous carcinomas and the differentiation of its types, LGSC and HGSC. To date, there are few papers describing the morphological features of MOC in MRI, with little attention paid to DCE and DWI parameters . Better insight into tumor morphology prior to surgical treatment enables easier and more precise planning of the scope of the operation. In tumors considered chemoresistant or poorly responsive to chemotherapy, such as MOC and low-grade serous ovarian cancer, primary optimal cytoreduction, precisely R-0 cytoreduction, is essential for prognosis. In these cases, suboptimal cytoreductive surgery or the use of neoadjuvant chemotherapy yields significantly worse results. The information obtained in the preoperative MRI that we are dealing with EOC types resistant to systemic treatment can be beneficial for the patient. The purpose of our study is to evaluate the diagnostic accuracy of DWI and DCE MRI quantitative analysis of the primary tumor in MOC patients and in differentiating between serous EOC (LGSC and HGSC) and MOC. The analysis of the primary tumor is dictated by the fact that MOC is diagnosed in early stages more often than other types of EOC, especially HGSC. In addition, we analyze selected DWI and DCE parameters for differentiating between serous EOC (LGSC and HGSC) and MOC. 2. Material and Methods 2.1. Study Protocol This single-center prospective study was conducted in the Second Department of Obstetrics and Gynecology and in the Second Department of Clinical Radiology at the Medical University of Warsaw. Patients with clinical suspicion of ovarian cancer based on CT or transvaginal ultrasound were included in the study. The exclusion criteria were current treatment of coexisting cancers and contraindications to MRI with gadolinium contrast administration. Histological grade and type of cancer were assessed according to the 2014 WHO criteria. The following types of EOCs were analyzed in the study: LGSC, HGSC and MOC . The profile of immunohistochemical (IHC) staining was as follows: CK7, CK20, PAX8, CDX2 WT1, MUC2, ER, and PR. The FIGO criteria (International Federation of Obstetricians and Gynecologists) were applied to disease staging. The patient characteristics, and clinical and histopathological data are collected in Table 1. 2.2. MRI Protocol MRI data were acquired with a 1.5T MR scanner (MAGNETOM Avanto, Siemens AG, Erlangen, Germany). The MRI protocol applied in the study included sequences as follows: turbo spin-echo (TSE), T2 weighted images (T2WI), fat suppressed T2-weighted images (fsT2WI), turbo inversion recovery magnitude (TIRM), diffusion-weighted echoplanar imaging (DW-EPI), and postcontrast dynamic T1-weighted gradient echo sequences (3D T1-GRE). Details of the applied parameters of MR imaging are presented in Table 2. The axial DW images were acquired using unified multi-slice EPI sequence 30 mm x 6 mm slices (pelvic part); 360 mm x 360 mm FoV; TR = 4250 ms; TE = 73 ms; and diffusion weights of 0, 50, 500, 1000, 1500 mm2/s. The parameters are collected in Table 2. Motion correction was completed automatically. The MRI were analyzed by two board-certified radiologists experienced in pelvis MRI (one with more than 15 years of experience in oncologic imaging and a board-certified radiologist with a European Diploma in Radiology certificate). The regions of interest (ROI) were drawn on the apparent diffusion coefficient (ADC) maps and all b values DWI outlined in the Multimodality Workplace Station (GE AW Server 3.2 ext. 4.0, Volume Viewer 16.0 Ext. 2 Ready View). Each radiologist examined each patient twice. To compare the ADC values recorded by the two radiologists and for the purpose of analyzing these values, they are referred to as follows. ADC1 and ADC2 correspond to the examination performed by the first radiologist, and ADC3 and ADC4 correspond to the examination performed by the second radiologist. On all the DWI (with b values of 0, 50, 500, 1000, 1500 mm2/s), the ROI contained a small circle with a diameter of 5mm that was placed in the solid part of the primary tumor, avoiding partial volume effect, areas of necrosis and artifacts. The ROIs were duplicated from the DWI to the corresponding ADC maps and the measurement on the ADC was recorded. The T1WI (non-contrast and post-contrast) and dynamic contrast enhancement (DCE) sequence parameters for dynamic analysis are collected in Table 2. The ROIs were placed on the post contrast DCE images and replicated to DCE parametric maps. During DCE image acquisition, non-contrast images were acquired first, followed by contrast agent administration and continued acquisition. On the DCE images, parameters such as perfusion maximum enhancement (Perf. Max En.) and time to peak (TTP) were measured. The DCE parametric maps were generated automatically using Workplace Station. In all patients, gadobutrol (Gadovist, Bayer AG, Leverkusen, Germany) was administered as a bolus dose of 0.1 mmol/kg, followed by a bolus dose of 20 mL of physiological saline (NaCl 0.9%). 2.3. Statistical Analysis IBM SPSS Statistics (version: 28.0.1.0(142)) was used to analyze the distribution of variables, perform statistical tests, as well as calculate statistics. PQStat (version: 1.8.4.) was used for the same purpose to analyze the data and to prepare all the visualizations seen in this article. The Shapiro-Wilk test was used to examine if a variable is normally distributed. During the analysis, it was decided to divide patients into three groups by EOC diagnosis (LGSC, HGSC and MOC patients) in order to compare the parameters for these groups when examined by a radiologist. To determine the p-value needed to compare median values of interval variables, the Kruskal-Wallis ANOVA test was used. The test is used specifically for independent variables that do not meet the condition of normal distribution. The main aim was to define if the p-value is less than 0.05, which indicates a statistically significant difference. Based on the post hoc (Conover-Iman) analysis, the two homogeneous groups were created based on similar median values. For the interval variables, to determine the inter-observer agreement between the two reviewers, the interclass correlation coefficient (ICC) was used. The determination of the ROC curve and the calculation of the area under this curve (AUC), as well as the calculation of sensitivity and specificity were used to compare which of the three quantitative parameters could give the best result in assigning patients to the appropriate groups. Due to the fact that there were three groups defined in the study while two groups are needed to plot the ROC curve, it was decided to assign patients to two groups for this analysis: LGSC with MOC and HGSC with MOC. 3. Results The study included 66 women aged 33-78 years (median 57.5 (48.5-64), interquartile range (IQR) = Q3 - Q1 = 15.5), who were diagnosed with EOC on the final histopathological examination. 3.1. Primary Tumor DWI Patients were examined using ADC, where two radiologists examined each patient twice. ADC1 and ADC2 correspond to the examination performed by the first radiologist, and ADC3 and ADC4 correspond to the examination performed by the second radiologist. The Shapiro-Wilk test showed that the variables ADC1, ADC2, ADC3 and ADC4 were not normally distributed (p value < 0.05). The calculated median values for ADC1, ADC2, ADC3 and ADC4 for the three defined groups are presented in Scheme 1. Due to the small differences in ADC values, it was decided to verify the inter-observer agreement using the ICC. 3.2. Inter-Observer Agreement The ICC was used to examine the inter-observer agreement for the quantitative parameter, ADC. For the ADC parameter, 132 (2 radiologists x 66 patients) observations were included. Based on the ICC values, there was an excellent, statistically significant inter-observer agreement between the two observers in assessing quantitative ovarian involvement by ADC. The inter-observer concordance oscillated at the level of excellent concordance, with ICC > 0.9, 95% CI: 0.899-0.961; p < 0.000001 . Scheme 2 and the box plot in Figure 2 show the results for ADC, treating the ADC parameter as one study, without dividing it into ADC 1-4. 3.3. Primary Tumor DCE Similar to the statistical analysis of ADC 1-4 values, the normal distribution of the parameters TTP and Perf. Max. En. was tested with the Shapiro-Wilk test and a p-value < 0.05 was obtained. The test showed that there was no normal distribution, so the median was used in Scheme 3 instead of the arithmetic mean. The statistical analysis was also performed across the three groups: LGSC, HGSC and MOC. The p-value < 0.05 by the Kruskal-Wallis ANOVA test indicates that the differences in the TTP and Perf. Max. En. parameters between the groups of patients according to EOC diagnosis were statistically significant. Thanks to the post hoc test, it was noted that the LGSC and HGSC patients had similar values for the parameters TTP and Perf. Max. En., which were statistically different from those for patients with MOC. For the TTP parameter, the LGSC and HGSC patients had lower median values (292 and 330, respectively) than the MOC patients (410), p-value = 0.009. However, for the Perf. Max. En., the median value for the patients in the LGSC = 260 and HGSC = 230 groups is higher than that of the patients with MOC = 141, p-value = 0.004. The median values obtained for the TTP and Perf. Max. Enh. parameters are shown as box plots . Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10 show the MOC morphology in T1-weighted and T2-weighted presentations and differences between MOC, LGSC and HGSC in DWI and DCE. 3.4. ROC Curve for LGSC vs. MOC Scheme 4 shows all the values important for the comparison and analysis regarding the ROC curve for the three quantitative parameters, i.e., range of values, sensitivity, specificity, cut-off value, AUC value and p-value. Using the ROC curves , the optimal cut-off value was selected that distinguishes LGSC patients from MOC patients. Comparing the results obtained for the ROC curves, it can be seen that the cut-off value for ADC is >=1382, that for TTP is >=354, and for maximum perfusion enhancement it is <=142. Based on these results, it can be concluded that for ADC and TTP, patients who achieved scores of 1382 and 354 or higher, respectively, should be assigned to the MOC group, whereas for Perf. Max. En., patients with values 142 or less are assigned to the MOC group. The three ROC curves showed good, excellent and very good diagnostic validity for the three measured parameters. The AUC values were good for ADC (0.744), excellent for TTP (0.9), and very good for Perf. Max. En. (0.814). The sensitivity oscillated at the levels of 66.7%, 100%, and 66.7%, respectively, and the specificity was at the level of 100%, 80% and 100%, respectively. Based on the obtained AUC values, we can conclude that LGSC is best differentiated from MOC by TTP, followed by Perf. Max. En. and ADC. 3.5. ROC Curve for HGSC vs. MOC By comparison with the previously defined ROC curves, it was determined which parameter (ADC, TTP or Perf. Max. En.) can better assign patients to the HGSC or MOC groups. Thus, the two groups were determined (HGSC and MOC). Scheme 5 shows all the values important for the comparison and analysis regarding the ROC curve for the three quantitative parameters, i.e., range of values, sensitivity, specificity, cut-off value, AUC value and p-value. By using ROC curves , the optimal cut-off value was determined, that best divides the study population into two groups: the patients with HGSC and the patients with MOC. Comparing the results obtained for the ROC curves, it can be seen that the cut-off value for the ADC parameter was >=1028.15, and for the TTP it was >=354 (the same value as when the patients were divided into the LGSC and MOC groups), and for the Perf. Max. En. it was <=142 (also the same value as in the analysis of patients by LGSC and MOC groups). Based on these results, it can be concluded that for the ADC and TTP parameters, the patients who score 1028.15 and 354 or higher, respectively, should be assigned to the MOC group, whereas for Perf. Max. En., patients with scores 142 or less are assigned to the MOC group. The three ROC curves showed excellent, good and very good diagnostic validity for the three measured parameters. The AUC values were as follows: ADC, excellent (0.932); TTP, good (0.722); and Perf. Max. En., very good (0.795). The sensitivity was 83.3%, 100% and 53.8%, respectively, and the specificity was 94.9%, 53.8% and 100%, respectively. Based on the obtained AUC values, we can conclude that HGSC is best differentiated from MOC by ADC, followed by Perf. Max. En. and TTP. 4. Discussion The results presented enabled us to determine the characteristics of MOC in DWI and DCE MRI. Our study showed that the use of parameters such as ADC, TTP and Perf. Max. En. make it possible to differentiate MOC and serous EOC and to divide the latter into HGSCs and LGSCs. The postoperative diagnosis of MOC is based on microscopic examination and immunohistochemical staining (IHC staining). MOC shares common features with other mucinous tumors, including gastrointestinal metastases, such as positive CK20, CEA, Ca19-9 and CDX2 staining. However, the primary differentiating factor is CK7 positivity. The standard IHC profile for MOC is CK7+, CK20+/-, CDX2+/-, PAX8-, WT1-, ER-, SATB2 . In our study, the IHC profile was similar and was as follows: CK7, CK20, CDX2, PAX8, WT1, ER, PR, and MUC-2. MRI is the imaging modality with the highest tissue resolution. It is the method of choice in the differentiation of primary ovarian tumors as well as in the diagnosis of metastatic lesions . In our study, we placed special focus on evaluating quantitative parameters of DWI and DCE. Nevertheless, qualitative analysis of the tumor was also included in our study as the two methods seem to be complementary to each other. The morphological elements of the primary tumor are taken into consideration in the differential diagnosis. Epithelial ovarian tumors contain solid components such as thick septa and internal solid components, while the content of solid elements in mucinous tumors is low. When determining the degree of malignancy in mucinous tumors, the size of the tumor is taken into account, especially above 10 cm, as well as the number of solid elements, mainly those with the "honeycomb" appearance . Some morphologic features of fluid content, such as a high signal on T1WI with fat suppression or an intermediate signal on T2WI, suggesting the presence of mucus, may raise the suspicion of a mucinous tumor. However, these features are exclusive to mucinous tumors. In serous carcinomas, mucous contents may also be present among fluid components . Large size of a tumor, unilateral mass, lack of spread to the peritoneum and infiltration of adjacent tissues may suggest mucinous carcinoma but are still not sufficient to make a diagnosis . Morphological features are not sufficient to determine the type and the grade of malignancy of an ovarian tumor. Additional information may be provided by the DWI as well as the DCE curves in the dynamic post-contrast examination and, as emphasized by many authors, can be essential in differential diagnosis . In our material, we focused on the comparative quantitative evaluation of DCE and DWI MRI in differentiating mucinous carcinomas from LGSC and HGSC. It has been demonstrated that differentiation of LGSC from HGSC is possible based on DWI and ADC . Some authors claim that certain perfusion parameters, such as k-tTRANS and TTP, may be considered as differentiating and prognostic factors for serous carcinomas simultaneously . Currently, there are no reports on the differentiation of MOC and other types of EOC based on diffusion and perfusion values on MRI. Single studies have described differences between MOC and mucinous borderline ovarian tumors (MBOT). The authors report that within the solid parts of the tumor, ADC values in MOC are lower than in MBOT . These findings are similar to studies on the serous EOCs, i.e., LGSC and HGSC. HGSCs, being more aggressive and less differentiated, show greater diffusion restriction and lower ADC values compared with well-differentiated LGSCs. This is also confirmed by the negative correlation with IHC markers of proliferation, such as Ki67 . Our study suggests that MOC is associated with LGSC in terms of DWI and DCE values. This is consistent with the division of EOC into two molecular types. Type I includes LGSC, MOC, endometrioid and clear cell carcinoma, while HGSC is classified as the more aggressive type II. LGSC and MOC are associated with BRAF and KRAS mutations. Mutation of p53 is characteristic of HGSCs . The results shown in Scheme 3 indicate statistically significant differences in median ADC values between MOC, LGSC and HGSC. However, the median values for type I (MOC and LGSC) are more similar than for HGSC (type II). This is also confirmed by analysis of the ROC curves for MOC and HGSC, showing that ADC has excellent diagnostic accuracy in differentiating between MOC and HGSC. In type I EOCs, i.e., MOC and LGSC, ADC has less differential value while TTP can be considered the most valuable parameter due to its excellent diagnostic accuracy. In this study, TTP was found to be the most valuable parameter. Our study has some limitations. First, it is a single-center study. Secondly, MOC is a rare type of EOC (only 3-4%). Due to this fact, a small number of patients were enrolled in the study, but this problem concerns all authors describing this type of EOC. 5. Conclusions DWI and DCE appear to be very good diagnostic tools in differentiating between serous carcinomas (LGSC, HGSC) and MOC. Significant differences in median ADC values between MOC and LGSC and between MOC and HGSC indicate the usefulness of DWI in differentiating between less and more aggressive types of EOC, not only in the group of most common serous carcinomas. ROC curve analysis showed that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC. In contrast, TTP showed the greatest differentiating value when diagnosing between LGSC and MOC. Author Contributions Conceptualization, L.G.-D. and P.D.; methodology, L.G.-D. and P.D.; validation, L.G.-D., P.D. and M.H.-R.; software, P.D.; investigations, L.G.-D., P.D. and M.H.-R.; resources, P.D., L.G.-D. and M.H.-R.; writing--original draft preparation, L.G.-D., P.D. and M.H.-R.; writing--review and editing, L.G.-D., P.D. and M.H.-R.; supervision, L.G.-D. and P.D.; project administration, L.G.-D. and P.D. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement All data were collected in accordance with the World Medical Association Declaration of Helsinki. The local ethics committee of the Medical University of Warsaw approved the study with vote number AKBE/288/2022. Informed Consent Statement A non-opposition statement was obtained from all subjects involved in the study. Data Availability Statement The data presented in this study are available on request from the corresponding authors. Conflicts of Interest The authors declare no conflict of interest. Figures, Schemes and Tables cancers-15-01453-sch001_Scheme 1 Scheme 1 Comparison of ADC 1-4 parameters between LGSC, HGSC and MOC. Figure 1 Multiple dot graphs for inter-observer agreement for ADC parameter performed by the two observers. cancers-15-01453-sch002_Scheme 2 Scheme 2 Comparison of ADC parameters between LGSC, HGSC and MOC. Figure 2 Box plot of comparisons of median ADC for LGSC, HGSC and MOC patients. cancers-15-01453-sch003_Scheme 3 Scheme 3 Comparison of TTP and Perf. Max. En. parameters between LGSC, HGSC and MOC. Figure 3 (a) Box plot of comparisons of median TTP for LGSC, HGSC and MOC patients. (b) Box plot of comparisons of median Perf. Max. En. for LGSC, HGSC and MOC patients. Figure 4 Images from a 24-year-old woman with mucinous ovarian cancer (MOC). A large primary multilocular cystic tumor was imaged with differing signal intensities of the cyst-on axial T2-weighted (A); on T2 STIR (B); on T1-weighted (C) and sagittal T1-weighted postcontrast fat-saturated subtracted MR show enhancement with solid part of the tumor (D). Figure 5 The same 24-year-old patient with MOC Diffusion-ADC maps. Multiple small ROI are placed on a region which is the most solid part of the tumor. Figure 6 Images from the same 24-year-old woman with mucinous ovarian cancer. Dynamic contrast enhancement and small ROI on intratumoral vessels. (A-C) Contrast enhancement curves (D). Figure 7 Images from a 59-year-old woman with low-grade serous ovarian cancer (LGSC). A multilocular cystic mass. Diffusion-ADC map. Figure 8 Images from the same 58-year-old woman with LGSC. Dynamic contrast enhancement shows dilated intratumoral vessels end-on manifesting as bright dots (A-C). Contrast enhancement curves (D). Figure 9 Images from a 60-year-old woman with high grade ovarian cancer. A large primary cystic tumor inspection for solid components. Diffusion-ADC maps. Multiple small ROI are placed on the solid part of the tumor. Figure 10 Images from the same 60-year-old woman with HGSC. Dynamic contrast enhancement and small ROI on intratumoral vessels. (A-C) Contrast enhancement curves (D). cancers-15-01453-sch004_Scheme 4 Scheme 4 The results obtained during the analysis of three ROC curves for three quantitative methods to identify the level of EOC disease progression in the studied patients (LGSC, MOC). Figure 11 ROC curve for diagnostic performance of the ADC parameter in detection of EOC (LGSC vs. MOC). Figure 12 ROC curve for diagnostic performance of the TTP parameter in detection of EOC (LGSC vs. MOC). Figure 13 ROC curve for diagnostic performance of the Perf. Max. En. parameter in detection of EOC (LGSC vs. MOC). cancers-15-01453-sch005_Scheme 5 Scheme 5 Table with the results obtained during the analysis of three ROC curves for three quantitative methods used to identify the level of EOC disease progression in the studied patients (HGSC, MOC). Figure 14 ROC curve for diagnostic performance of ADC parameter in detection of EOC (HGSC vs. MOC). Figure 15 ROC curve for diagnostic performance of TTP parameter in detection of EOC (HGSC vs. MOC). Figure 16 ROC curve for diagnostic performance of Perf. Max. En. parameter in detection of EOC (HGSC vs. MOC). cancers-15-01453-t001_Table 1 Table 1 Clinicopathological characteristics of 66 patients. Variable n (%)/Mean (Range) Age 55.5 (31-78) FIGO stage I 14 II 3 III 44 IV 4 Histological type Serous high-grade 39 Serous low-grade 15 Mucinous 12 cancers-15-01453-t002_Table 2 Table 2 MR study protocol. Parameter T2 TSE T2 TSE Fat-Sat DW EPI T2 TIRM Vibe 3D T1 GRE T1 GRE ( Outphase) T1 TSE Fat-Sat T2 TSE (BLADE) Fat-Sat (SPAIR) Repetition time (ms) 4250 2110 3800 6100 3.05 125 510 2300 Echo time (ms) 117 123 73 39 1.13 1: 2.22 2: 4.92 9.6 116 Flip angle (deg.) 137 150 90 150 10 70 150 150 iPAT factor - 2 2 - 2 2 - 2 Plane axial, sagital coronal axial axial axial axial axial axial, sagital coronal axial, coronal Number of signal averages 1 1 4 1 1 1 1 1 Field of view--FOV (mm) 360 360 360 360 360 360 360 360 Rectangular FOV (%) 75, 100, 100 100 75 75 75 75 75 100 Breath-hold No No No No No No No Yes Resolution (mm) 0.7 x 0.7 x 5 1.4 x 1.4 x 5 B value: 0, 50, 500, 1000, 1500 0.9 x 0.9 x 5 1.7 x 1.3 x 3 1.3 x 1.3 x 5 0.9 x 0.9 x 5 1.4 x 1 x 4 x 6 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000546 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051056 foods-12-01056 Article Effect of Thermal Pretreatment on the Physiochemical Properties and Stability of Pumpkin Seed Milk Yu Min Writing - review & editing 1 Peng Mengyao Software 1 Chen Ronghua Investigation 1 Chen Jingjing Formal analysis 12* Sun Jianan Academic Editor Jiang Hong Academic Editor 1 State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China 2 International Joint Laboratory on Food Safety, Jiangnan University, Wuxi 214122, China * Correspondence: [email protected] 02 3 2023 3 2023 12 5 105613 1 2023 18 2 2023 28 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). During the production of plant-based milk, thermal treatment of raw materials is an important processing method to improve the physicochemical and nutritional quality of the final products. The objective of this study was to examine the impact of thermal processing on the physiochemical properties and stability of pumpkin seed (Cucurbita pepo L.) milk. Raw pumpkin seeds were roasted at different temperatures (120 degC, 160 degC, and 200 degC), and then processed into milk using a high-pressure homogenizer. The study analyzed the microstructure, viscosity, particle size, physical stability, centrifugal stability, salt concentration, heat treatment, freeze-thaw cycle, and environment stress stability of the resulting pumpkin seed milk (PSM120, PSM160, PSM200). Our results showed that the microstructure of pumpkin seeds was loose and porous, forming a network structure because of roasting. As the roasting temperature increased, the particle size of pumpkin seed milk decreased, with PSM200 showing the smallest at 210.99 nm, while the viscosity and physical stability improved. No stratification was observed for PSM200 within 30 days. The centrifugal precipitation rate decreased, with PSM200 showing the lowest rate at 2.29%. At the same time, roasting enhanced the stability of the pumpkin seed milk in the changes in ion concentration, freeze-thaw, and heating treatment. The results of this study suggested that thermal processing was an important factor in improving the quality of pumpkin seed milk. pumpkin seed milk viscosity particle size zeta potential structural properties Chongzuo Scientific Research ProjectFA2020015 Xinjiang Production and Construction Crop Scientific Research Project2019AB027 This work was supported by Chongzuo Scientific Research Project (FA2020015) and Xinjiang Production and Construction Crop Scientific Research Project (2019AB027). pmc1. Introduction In recent years, consumers have shown an increased interest in plant-based milks as a healthier alternative to traditional animal milk. The reason why consumers prefer to consume alternative milks is because they do not contain cholesterol and can reduce cardiovascular disease risk and allergic risk . Besides, since plant-based milk does not contain lactose, there are no concerns about lactose intolerance, which is otherwise a serious problem in milk . Lastly, plant-based milk is thought to be more environmentally friendly due to the lower greenhouse gas emissions associated with plant farming compared to animal farming . At present, there are many varieties of plant-based milk on the market, such as almond, soy, oat, and cashew milk. Almond milk is low in calories and relatively high in calcium, but low in protein (1.44%). Soy milk contains almost twice as much folic acid and vitamin B12 as cow's milk . Rincon had developed a new plant-based milk based on chickpeas and coconut that had a higher protein calcium fat content than oat milk . However, stability remains a focus of plant milk research. There are many factors affecting the stability of plant-based milk, including protein-oil ratio processing methods, pH conditions, ion strength, environmental temperature, etc. . Pan et al. hydrolyzed rice protein with different proteases (neutral enzyme trypsin and alkaline protease) and found that the trypsin hydrolysate showed high stability. The stability of plant-based milk mixed with quinoa and lentil protein was also improved by regulating protein-protein interactions and the interaction between protein and quinoa starch . These findings demonstrate that further research into improving the stability of plant-based milk is needed. Heat treatment is a critical step in the production and processing of milk alternatives . Roasting, in particular, is one of the heat treatment processing methods. It uses the heating principle to make the product evenly cooked and improves the digestibility and sensory quality of food nutrition by studying the transformation of the food matrix with an ideal structure . Although heat processing can degrade and aggregate proteins, resulting in a decreased protein content, proper heat processing can improve functional properties by increasing protease contact sites . Moreover, after heat treatment, the polypeptide chain will unfold, and the sulfhydryl group and hydrophobic side chain inside the molecule will be exposed, affecting the functional properties of the protein. High temperatures can induce protein interactions, leading to protein aggregation and precipitation . Dissociation and aggregation caused by heating have been extensively studied in seeds such as soybeans, oats, and kidney beans . The increase in temperature during heat processing will promote the degradation of polysaccharide structure, reduce the particle size of substances, and improve the stability and storage period of food . Jin et al. , in their experiments on the effects of roasting on the physical and chemical properties of sesame paste, pointed out that roasting increased the texture and rheology of the paste, reduced the particle size of sesame paste, and improved its storage stability. Pumpkin seeds are a rich source of high-quality plant protein and oil. In addition to common nutrients such as carbohydrates and proteins, pumpkin seeds also contain vitamins (B1, B2, E, etc.), carotenoids, squalene, phytosterols, cucurbitacin, and phenolic compounds . Pumpkin seed extract has been shown to have several health benefits, including the prevention of prostate cancer and urinary system diseases , and the improvement of symptoms associated with hypertension and diabetes . Mixing pumpkin seed milk and camel milk can change the chemical properties, antioxidant, viscosity, and sensory properties of fermented camel milk, while increasing the phenolic components and antioxidant dietary fiber, thus improving the nutritional value and health benefits . Kuru et al. studied the optimization of the plant milk mixing design. After sunflower seeds and pumpkin seeds were combined, both the dry matter and ash contents of samples had increased. The content of total milk phenol and DPPH free radical scavenging activity were dominated by the sunflower seed ratio. The hazelnut ratio had positive effects on the protein content, whiteness index, serum stability, and sensory properties. The purpose of this experiment was to study the effects of roasting materials on the physicochemical properties and stability of pumpkin seed milk. 2. Materials and Methods 2.1. Material Pumpkin seeds (Cucurbita pepo L.) were provided by Sanxin Company (Urumqi, Xinjiang, China). Reagents used in this study were of analytical grade unless otherwise specified. N-hexane was purchased from InnoChem Science and Technology Co., Ltd. (Beijing, China). Disodium hydrogen phosphate dodecahydrate, sodium phosphate dibasic dihydrate, disodium tetraborate decahydrate, O-phthalic aldehyde (OPA), dithiothreitol (DTT), serine, folin-phenol, sodium carbonate, trichloroacetic acid (TCA), absolute ethyl alcohol, sodium chloride, sodium hydroxide, calcium chloride, potassium chloride, sodium bicarbonate, and magnesium chloride, were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Coomassie Blue Fast Staining Solution G250, Bovine Serum Albumin (BSA), and Phosphate-Buffered Saline (PBS) were purchased from Beyotime Biotechnology Co., Ltd. (Shanghai, China). 2.2. Preparation of Pumpkin Seed Milk Three equal masses of pumpkin seeds were roasted at 120 degC, 160 degC, and 200 degC for 10 min, respectively, in an oven (NB-HM3810, Panasonic Manufacturing Xiamen Co., Ltd., Xiamen, China). Then, the roasted pumpkin seeds were soaked in distilled water with a ratio of 1:3 (w/w) at 4 degC for 20 h . After soaking, the seed coats were carefully removed. The soaking water was drained and the residual water on the naked seeds was removed with a kitchen paper towel. Then, the seeds were grounded with water at the weight ratio of 1:8 (w/v) in a blender (HR2101, Philips, Amsterdam, The Netherlands) for 3 min. The slurry was filtered with eight layers of cheesecloth. Then, the filtrate was homogenized twice with a high-pressure homogenizer (JHG-54-P100, GEA Mechanical Equipment Italia S.P.A., Parma, Italy) at 40 MPa. Pumpkin seed milk (PSM) prepared with seeds at different roasting temperatures was obtained with the same method and named: RAW, PSM120, PSM160, and PSM200. 2.3. Characterization of Pumpkin Seed Milk 2.3.1. Microstructure of PSMs Confocal Laser Scanning Microscopy (CLSM) of PSMs The microstructure of roasted pumpkin seed milk droplets was observed using a confocal laser microscope (LSM710, Carl Zeiss AG, Oberkochen, Germany) method reported by Zhong et al. . Briefly, 0.1 mL of premixed Nile red and Nile blue A (0.1% in isopropyl alcohol) was added into 2 mL of pumpkin seed milk and placed in the dark for 30 min. Then, the mixture was dropped on a microscope slide and observed with the confocal laser microscope. The fluorescence of the dyes was excited at the wavelength of 488 nm for Nile red and 633 nm for Nile blue A. Microstructure of PSMs Pumpkin seed milk was freeze-dried. The freeze-dried solid samples were evenly spread on the sample table with conductive adhesive and treated with gold spraying. Imaging was observed under an accelerated voltage of 20 kV with a scanning electron microscope (TM3030, Koki Holdings Co. Ltd., Tokyo, Japan). 2.3.2. Particle Size Distribution of PSMs Each PSM sample was diluted 300 times with deionized water. The particle size distribution of the sample was determined using a multi-angle particle size and high sensitivity z-potential analyzer (Nano Brook Omni, Malvern Instruments, Malvern, Worcestershire, UK) after 2 h and 7 days of storage (20 degC) . 2.3.3. Rheological Properties of PSMs A rheometer (DHR-3, Kinexus, Malvern, Worcestershire, UK) was used to determine the rheological properties of PSMs . The instrument was equipped with a cone plate. A plate gap of 0.1 mm and plate truncation of 1deg was maintained throughout the experiment. Milk samples (2 mL) were loaded on the plate at a temperature of 25 degC. After calibration, the viscosity of the sample was measured within the shear rate range of 0.1-500 s-1. 2.4. Stability of PSMs 2.4.1. Appearance of PSMs In order to investigate the storage stability of pumpkin seed milk, 10 mL of each freshly prepared PSM was accurately transferred into the glass bottle with a lid and placed at room temperature for 30 days. Photographs were taken at 1, 3, 7, 14, 21, and 30 days to observe the phase separation of the different PSMs. 2.4.2. Centrifugal Stability of PSMs Samples with a certain mass were accurately weighed into the centrifuge tubes and centrifuged at 9030x g for 20 min at 4 degC with a CR30NX high-speed centrifuge (5840R, Koki Holdings Co. Ltd., Tokyo, Japan). After centrifugation, the supernatants were removed, the precipitation mass was weighed, and the centrifugation precipitation rate was calculated. The smaller the precipitation rate, the better the stability of the milk . The centrifugation precipitation rate was calculated with the following formula:Centrifugation precipitation rate = (m2 - m)/(m1 - m) x100%(1) where m is the mass of the empty centrifuge tube, m1 is the total mass before centrifugation, and m2 is the total mass after centrifugation. 2.4.3. Effect of Salt Concentration on Stability of PSMs Freshly prepared pumpkin seed milks were diluted with the same volume of concentrated salt (NaCl) solution to form the final sample with the salt concentrations of 0.1, 0.2, 0.3, 0.4, and 0.5 mol/L . After the samples were diluted 100 times, the particle sizes and z-potentials were measured by the multi-angle particle size and high-sensitivity z-potential analyzer (DLS, Zetasizer Nano, Malvern Instruments Ltd., Worcestershire, UK) to evaluate the stability. 2.4.4. Effect of Freeze-Thaw on Stability of PSMs Here, 5 mL of each freshly prepared pumpkin seed milk sample was placed in the freezer (-20 degC) and frozen for 24 h. After 24 h, the samples were taken out and placed in a water bath (37 degC) until half the ice was melted, and then transferred to a refrigerator to allow complete thawing. This was regarded as one complete freeze-thaw cycle. Each sample was subjected to three freeze-thaw cycles. After that, samples were diluted 100 times, and the particle size and z-potential were measured. 2.4.5. Effect of Heat Treatment on Stability of PSMs Here, 5 mL of each freshly prepared pumpkin seed milk sample was put in a test tube and heated in a water bath at 30 degC, 60 degC, and 90 degC for 6 h, then cooled to room temperature and diluted 100 times. The particle size and z-potential were measured by a multi-angle particle size analyzer and a highly sensitive z-potential analyzer. 2.5. Statistical Analysis The results are presented as mean +- standard deviation (SD) of three technical replicates. The significant differences between the means were evaluated by ANOVA using IBM SPSS Statistics 26.0 and values of p < 0.05 were considered statistically significant. 3. Results and Discussion 3.1. Characterizations of Pumpkin Seed Milk 3.1.1. Confocal Laser Scanning Microscope (CLSM) Observation Figure 1 shows the confocal laser scanning microscope images of pumpkin milk droplets made from pumpkin seeds roasted at different temperatures. The red image represents protein in PSMs upon being dyed with Nile red. As shown in Figure 1, the pretreatment temperature had a significant influence on the flocculation and coalescence of pumpkin seed milk. The fluorescent images of RAW and PSM120 were similar and both were aggregated. PSM200 had relatively scattered droplets. This may be due to an increase in soluble protein in milk as the pretreatment temperature increased. At higher protein concentrations, more emulsifiers can be used to cover the oil-water interface, resulting in smaller droplet sizes. Yun et al. also found that the quantity and concentration of adsorbed proteins at the interface of milk treated with preheating were significantly increased, thus showing good anti-flocculation stability and oxidation stability. The results of CLSM showed that high-temperature roasting could make the pumpkin seed milk droplets disperse, so that the distribution of pumpkin seed milk was more uniform and the stability was improved. 3.1.2. Scanning Electron Microscope (SEM) Scanning electron microscope images of freeze-dried powders of RAW, PSM120, PSM160, and PSM200 are shown in Figure 2. The morphologies of freeze-dried PSMs were significantly different. The surface of freeze-dried PSM120 was smooth and dense, and mushroom-like. While PSM160 showed a regular spherical distribution, PSM200 was spongy and porous, and RAW had a denser structure. These results were in accordance with CLSM results. This may also be explained by the increase of soluble proteins that served as emulsifiers during the preparation of PSMs, which will lead to a smaller droplet size and increased electrostatic repulsion between the droplets . Yan et al. found that roasting changed the structure of cashew protein, increased the development degree of protein molecules, exposed hydrophobic groups, and increased hydrophobic interactions, forming a three-dimensional network structure, which will eventually affect its application as an emulsifier. The SEM results showed that baking made the structure of PSM loose and porous, the interaction force between protein particles and fat pellets increased, and the particle size of PSM decreased. 3.1.3. Particle Size Distribution Figure 3 shows the particle size distribution of PSMs at 2 h and after being stored for 7 days. As shown in Figure 3, the particle size distribution curve of pumpkin seed milk prepared by different roasting temperatures was different. Compared with 2 h, the particle size of PSMs increased after 7 days of storage. The results showed that the particle size of protein molecules increased with the aggregation of protein particles after storage. Particle size distribution and average particle size were important indexes to evaluate milk stability . With the increase in the pre-roasting temperature of the raw material, the particle size of PSMs decreased. Again, this may be caused by increased protein in PSM prepared with pumpkin seeds roasted at higher temperatures. Another possible reason is the inactivation of lipoxygenase. Studies showed that lipoxygenase can promote the formation of protein aggregates through disulfide and non-covalent bonds between protein molecules, thus increasing the average particle size of milk . Increased pretreatment can cause the inactivation of lipoxygenase and prevent protein aggregation. This indicates that with the extension of storage time, the particle size increases due to aggregation among PSM molecules, and the stability of PSM deteriorates after a long storage time. 3.1.4. Rheological Property As shown in Figure 4, thermal pretreatment of raw material significantly affected the rheological behavior of pumpkin seed milk. At the low shearing rate, PSMs showed shear-thinning behavior, i.e., the apparent viscosity decreased as the shearing rate increased. For example, the apparent viscosity of PSM200 decreased from 8.90 to 1.25 mPa*s when the shearing rate increased from 0 to 50 s-1. This was due to the unstable flow of the liquid when measuring viscosity at lower shearing rates. Then, the viscosity increased slowly with the increase of the shearing rate, showing a shear-thickening behavior. For example, the apparent viscosity of PSM200 increased from 1.25 to 1.73 mPa*s when the shearing rate increased from 50 to 500 s-1. Overall, PSM120, PSM160, and PSM200 showed higher viscosity than raw PSM . After heating, high-temperature denaturation of protein and clustering resulted in the increase of sample viscosity and the decrease of the gel effect. Increased viscosity impedes droplet movement due to gravity or Brownian motion and inhibits further fusion and coalescence between proteins . This was consistent with the conclusion of Bernat et al. , who found that the viscosity of heat-treated almond products was higher than that of hazelnut milk. The results showed that the viscosity of PSM increased with the increasing roasting temperature, but there was no positive correlation between the viscosity and the baking temperature. The increased viscosity further promotes the physical stability of PSM. 3.2. Stability of Pumpkin Seed Milk 3.2.1. Storage Stability To study the stability of PSMs, pumpkin seed milks were stored at room temperature in the dark for 30 days, and photos were taken on days 1, 3, 7, 14, 21, and 30. As shown in Figure 5, after 7 days of storage, samples of RAW and PSM120 began to sediment. PSM160 began to sediment after 14 days, while PSM200 did not separate within 30 days. Compared with RAW and PSM120, the storage stability of PSM160 and PSM200 was greatly improved. Dai et al. reported that the hydrophobic groups inside peanut proteins were exposed after heat treatment, and the surface electrostatic charge was increased. Hydrophobic bonds and disulfide bonds of protein particles formed a gel, and the water-holding capacity and oil-mixing capacity of the emulsion were enhanced. After the surface of the oil droplets was adsorbed by proteins, the upward movement speed became smaller, which slowed down the phase separation and improved the stability . 3.2.2. Centrifugal Stability In this study, the centrifugal precipitation rate was used to characterize the centrifugal stability of pumpkin seed milk. The physical instability of pumpkin seed milk was mainly manifested in fat floating and protein sinking. The stability of pumpkin seed milk was improved with the decrease in the centrifugal precipitation rate. As shown in Figure 6, the centrifugal precipitation rates of RAW and PSM200 were significantly different. The centrifugal precipitation rate of unroasted pumpkin seed milk was higher than that of roasted pumpkin seed milk. PSM200 had the lowest centrifugal precipitation rate, which showed the best stability. This indicated that the stability of pumpkin seed milk was improved by roasting pretreatment, and the improvement was more obvious with the increase in roasting temperature. The stability of pumpkin seeds was not only affected by particles, but also by the interaction of composition, viscosity, and microstructure . Roasting improves the hydration capacity and surface hydrophobicity of proteins, increases the interaction between molecules, forms a network gel structure between proteins, and increases the viscous resistance of particle deposition . Therefore, increasing the roasting temperature can improve the centrifugal stability of pumpkin seed milk. 3.2.3. Effect of Salt Concentration on Average Particle Size and z-Potential of Roasted Pumpkin Seed Milk Effect of Salt Concentration on Average Particle Size of PSMs Figure 7a shows the average particle size of roasted pumpkin seed milk at different NaCl concentrations. As the NaCl concentration increased, the particle size first increased and then decreased, with a maximum at a NaCl concentration of 0.3 mol/L. On the other hand, as the roasting temperature increased, the particle size decreased, with the lowest particle size being observed for PSM200 (roasted at 200 degC). Compared with the similar experimental results of Minmin et al. , the influence of salt concentration on the average particle size of PSMs was not significant, which indicated that the pumpkin seed milk prepared by roasting pumpkin seeds had better ion stability. The addition of salt will remove the charge on the protein surface, leading to the reduction of electrostatic repulsion between droplets and the highly flocculated state of the emulsion, resulting in the increase of the particle size. However, with the further electrostatic shielding effect, the emulsion will turn from flocculation to condensation, so the particle size will increase first and then decrease . Effect of Salt Concentration on z-Potential of PSMs As can be seen from Figure 7b, the z-potential value of PSMs ranged from -5 mV to 55 mV under different salt concentrations. When the pH of pumpkin seed milk was higher than the isoelectric point, the protein was negatively charged . With the increase of NaCl concentration, the z-potential of pumpkin seed milk decreased first and then increased. The z-potential of PSM120 and PSM200 decreased first, then increased, and then decreased again. There was no significant correlation between PSM160 and salt concentration. At the same NaCl concentration, the absolute values of RAW charge were all smaller than PSM120 and PSM160 and had no significant correlation with PSM200. The results indicated that the addition of Na+ can prevent the emulsification of pumpkin seed milk to a certain extent, so that pumpkin seed milk had a higher ionic stability . 3.2.4. Effect of Freeze-Thaw Cycles on the Stability of PSMs Effect of Freeze-Thaw Cycles on the Average Particle Size of PSMs In the freeze-thaw process, the crystallization of oil and water would cause the separation of oil and water in milk, affecting its stability, as shown in Figure 8a. At the same temperature, the average particle size of PSMs increased with the increase of the freeze-thaw times, but there was no significant effect on the average particle size of PSM200 during the freeze-thaw process. With the same number of freeze-thaw cycles, the average particle size was decreased by increasing the roasting temperature. With the increase in freeze-thaw times, the particle size significantly changed due to the rearrangement of the protein particle network and the aggregation of fat spheres in the microstructure . When the seeds were roasted at 200 degC, the protein denaturation was serious, the exposure of hydrophobic groups increased, and the protein particles were closely bound to the fat so that they maintained a good shape of milk particles in the freeze-thaw process and reduced the aggregation . Therefore, the particle size of PSM200 did not change significantly after freeze-thaw cycles. The results showed that the pumpkin seed milk prepared by roasting at high temperatures could better maintain the droplet structure and had good freeze-thaw stability. Effect of Freeze-Thaw Cycles on z-Potential of PSMs In Figure 8b, the z-potential of pumpkin seed milk varied from -15 mV to 55 mV under different salt concentrations. The repulsive force between particles increased with the increase of the absolute value of z-potential, and thus the stability of the emulsion system was improved with the decrease in the possibility of particle polymerization . It can be seen from the figure that the absolute value of z-potential of the 4 kinds of pumpkin seed milk was greater than 30 when there was no freeze-thaw cycle. With the increase of freeze-thaw times, the absolute value of z-potential of the four kinds of pumpkin seed milk decreased, indicating that the freeze-thaw cycle would destroy the stability of pumpkin seed milk. 3.2.5. Effect of Heat Treatment on the Stability of PSMs Effect of Heat Treatment on the Average Particle Size of PSMs As can be seen from Figure 9a, heat treatment at a high temperature of 200 degC did not have a significant effect on the particle size of pumpkin seed milk (PSM200). With the increase of heat treatment temperature, the particle size of RAW and PSM120 obviously increased, indicating that the particles had gathered. The interaction between proteins can be attributed to thermal denaturation and aggregation enhancement. Under the hydrophobic interaction, the surface hydrophobicity was enhanced, and the aggregate size was larger. Similar results have been observed in the case of peanut milk, where roasting significantly increased the particle size and improved the resistance of peanut milk to sterilization heat treatment. This is believed to be due to the Maillard reaction and its effect on the conformation and properties of proteins . Effect of Heat Treatment on z-Potential of PSMs The effect of heat treatment on the z-potential of PSMs is shown in Figure 9b. As the heat treatment temperature was increased, the particle size of PSMs was increased, and the absolute value of their z-potential was decreased. This indicated that the electrostatic repulsion was weakened by the reduction of the molecular surface charge, resulting in protein aggregation and poor stability . At 90 degC, the large negative z-potential of PSMs was less than 30. The influence of heat treatment on absolute z-potential was intensified with the increase in the pretreatment temperature. Zhang et al. believed that heating changed the interface properties, exposed the hydrophobic groups of proteins, increased the electrostatic attraction, or formed disulfide bonds, and thus increased the electrostatic attraction between droplets, leading to the aggregation of milk. 4. Conclusions In this study, we investigated the effects of roasting on the physical and chemical properties of pumpkin seed milk. The pumpkin seeds were roasted at temperatures of 120 degC, 160 degC, and 200 degC, and the resulting pumpkin seed milks were compared to the milk made from unroasted pumpkin seeds. Our results showed that higher roasting temperatures led to a decrease in particle size, and an increased stability of PSMs compared to the unroasted pumpkin seed milk. The effects of salt concentration, freezing and thawing cycles, and heat treatment on the stability of PSM200 were minimal but had a significant influence on RAW. In conclusion, our results suggested that thermal pretreatment of raw materials may enhance the physiochemical properties and stabilities of pumpkin seed milk. In future studies, we aim to determine the protein content, structure, properties, as well as lipoxygenase content in each PSM sample, to gain a deeper understanding of mechanisms underlying these phenomena. The result of this study may provide important implications for the development of pumpkin seed milk and other plant milk products. Author Contributions M.Y., conceptualization, investigation, methodology, software, data curation, writing--original draft, writing--review and editing; M.P., software; R.C., investigation; J.C., project administration, writing--review and editing. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data used to support the findings of this study can be made available by the corresponding author upon request. Conflicts of Interest The authors declare no conflict of interest. Figure 1 CLSM images of pumpkin seed milk droplets prepared with different pumpkin seeds: (a) raw pumpkin seeds, (b) pumpkin seeds roasted at 120 degC, (c) pumpkin seeds roasted at 160 degC, and (d) pumpkin seeds roasted at 200 degC. Figure 2 SEM images of freeze-dried pumpkin seed milk prepared with different pumpkin seeds. (a) RAW: raw pumpkin seeds, (b) PSM120: pumpkin seeds roasted at 120 degC, (c) PSM160: pumpkin seeds roasted at 160 degC, and (d) PSM200: pumpkin seeds roasted at 200 degC. Figure 3 Particle size of pumpkin seed milk prepared with different pumpkin seeds. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Solid line: fresh pumpkin milk; dotted line: pumpkin milk stored at 20 degC for 7 days. Figure 4 Rheology of pumpkin seed milk prepared with different pumpkin seeds. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Figure 5 Appearance of PSM after storage for different times. (a-f) Storage for 1, 3, 7, 14, 21, and 30 days, respectively. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Figure 6 Centrifugal precipitation rate of pumpkin seed milk prepared with different pumpkin seeds. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Different lowercase letters represent significant differences (p < 0.05). Figure 7 (a) Effect of salt concentration on average particle size of PSMs. (b) Effect of salt concentration on z-potential of PSMs. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Different lowercase letters represent the significant difference of the z-potential of different pumpkin seed milks at the same salt concentration, and different uppercase letters represent the significant difference of z-potential of the same milk at different salt concentrations. Figure 8 (a) Effect of freeze-thaw cycles on average particle size of PSMs. (b) Effect of freeze-thaw cycles on z-potential of PSMs. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Different lowercase letters represent the significant difference of z-potential of different pumpkin seed milks at the same salt concentration, and different uppercase letters represent the significant difference of z-potential of the same milk at different salt concentrations. Figure 9 (a) Effect of heat treatment on average particle size of PSMs. (b) Effect of heat treatment on z-potential of PSMs. RAW: raw pumpkin seeds, PSM120: pumpkin seeds roasted at 120 degC, PSM160: pumpkin seeds roasted at 160 degC, and PSM200: pumpkin seeds roasted at 200 degC. Different lowercase letters represent the significant difference of z-potential of different pumpkin seed milks at the same salt concentration, and different uppercase letters represent the significant difference of z-potential of the same milk at different salt concentrations. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Arshad M. Anwar S. Pasha I. Ahmed F. Aadil R.M. Development of imitated meat product by utilizing pea and lentil protein isolates Int. J. Food Sci. Technol. 2022 57 3031 3037 10.1111/ijfs.15631 2. Javed F. Jabeen S. Sharif M.K. Pasha I. Riaz A. Manzoor M.F. Sahar A. Karrar E. Aadil R.M. Development and storage stability of chickpea, mung bean, and peanut-based ready-to-use therapeutic food to tackle protein-energy malnutrition Food Sci. Nutr. 2021 9 5131 5138 10.1002/fsn3.2479 34532022 3. Antunes I.C. Bexiga R. Pinto C. Roseiro L.C. Quaresma M.A.G. 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PMC10000547 | Cells Cells cells Cells 2073-4409 MDPI 10.3390/cells12050693 cells-12-00693 Article Tandem Multimerization Can Enhance the Structural Homogeneity and Antifungal Activity of the Silkworm Protease Inhibitor BmSPI39 Li Youshan Conceptualization Methodology Software Formal analysis Investigation Resources Data curation Writing - original draft Supervision Project administration Funding acquisition 12* Wang Yuan Software Investigation Data curation 1 Zhu Rui Formal analysis Writing - review & editing Project administration 2 Yang Xi Investigation Data curation 3 Wei Meng Investigation 1 Zhang Zhaofeng Investigation 1 Chen Changqing Investigation 4 Zhao Ping Methodology Writing - review & editing Supervision Project administration 5 Kim Yonggyun Academic Editor Espeso Eduardo A. Academic Editor 1 College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong 723001, Shaanxi Province, China 2 Qinba Mountain Area Collaborative Innovation Center of Bioresources Comprehensive Development, Hanzhong 723001, Shaanxi Province, China 3 Qinba State Key Laboratory of Biological Resources and Ecological Environment (Incubation), Shaanxi University of Technology, Hanzhong 723001, Shaanxi Province, China 4 Shaanxi Province Key Laboratory of Bio-Resources, Hanzhong 723001, Shaanxi Province, China 5 State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing 400715, China * Correspondence: [email protected] 22 2 2023 3 2023 12 5 69323 12 2022 05 2 2023 20 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Previous studies have shown that BmSPI39, a serine protease inhibitor of silkworm, can inhibit virulence-related proteases and the conidial germination of insect pathogenic fungi, thereby enhancing the antifungal capacity of Bombyx mori. The recombinant BmSPI39 expressed in Escherichia coli has poor structural homogeneity and is prone to spontaneous multimerization, which greatly limits its development and application. To date, the effect of multimerization on the inhibitory activity and antifungal ability of BmSPI39 remains unknown. It is urgent to explore whether a BmSPI39 tandem multimer with better structural homogeneity, higher activity and a stronger antifungal ability can be obtained by protein engineering. In this study, the expression vectors of BmSPI39 homotype tandem multimers were constructed using the isocaudomer method, and the recombinant proteins of tandem multimers were obtained by prokaryotic expression. The effects of BmSPI39 multimerization on its inhibitory activity and antifungal ability were investigated by protease inhibition and fungal growth inhibition experiments. In-gel activity staining and protease inhibition assays showed that tandem multimerization could not only greatly improve the structural homogeneity of the BmSPI39 protein, but also significantly increase its inhibitory activity against subtilisin and proteinase K. The results of conidial germination assays showed that tandem multimerization could effectively enhance the inhibitory ability of BmSPI39 on the conidial germination of Beauveria bassiana. A fungal growth inhibition assay showed that BmSPI39 tandem multimers had certain inhibitory effects on both Saccharomyces cerevisiae and Candida albicans. The inhibitory ability of BmSPI39 against these the above two fungi could be enhanced by tandem multimerization. In conclusion, this study successfully achieved the soluble expression of tandem multimers of the silkworm protease inhibitor BmSPI39 in E. coli and confirmed that tandem multimerization can improve the structural homogeneity and antifungal ability of BmSPI39. This study will not only help to deepen our understanding of the action mechanism of BmSPI39, but also provide an important theoretical basis and new strategy for cultivating antifungal transgenic silkworms. It will also promote its exogenous production and development and application in the medical field. protease inhibitor tandem multimer antifungal activity pathogenic fungi conidial germination Bombyx mori National Natural Science Foundation of China31702187 Key Project of Shaanxi Natural Science Basic Research Plan2022JZ-12 Key Scientific Research Project of Education Department of Shaanxi Province22JY017 Scientific Research Foundation of Shaanxi University of TechnologySLGKYXM2202 This work was supported by grants from the National Natural Science Foundation of China (31702187), the Key Project of Shaanxi Natural Science Basic Research Plan (2022JZ-12), the Key Scientific Research Project of Education Department of Shaanxi Province (22JY017) and the Scientific Research Foundation of Shaanxi University of Technology (SLGKYXM2202). pmc1. Introduction Bombyx mori is a silk-spinning insect with great economic value that has accumulated a large amount of basic research and has become one of the best models of insect biochemistry, genetics and genomics . After thousands of years of artificial domestication, although the silkworm has acquired some characteristics conducive to production, such as being suitable for social rearing and developing neatly, it has also accumulated unfavorable characteristics that are vulnerable to infection by pathogenic microorganisms. Insect pathogenic fungi, as a new type of biological pesticide, have been widely used in agriculture and forestry pest control and mosquito control. The use of fungal biopesticides will inevitably cause cross-infection with silkworms, which will lead to highly pathogenic silkworm disease, seriously affect the yield and quality of cocoon silk and cause significant economic losses to the whole sericulture industry. Therefore, it is of great significance for the whole silkworm production to elucidate the defense mechanism of silkworms against fungal diseases, seek new defense measures and innovate silkworm genetic materials. Entomopathogenic fungi penetrate the insect integument through the combined action of mechanical pressure and enzyme degradation . Many entomopathogenic fungi can secrete subtilisin-like proteases, an important class of cuticle-degrading proteases. Cuticle-degrading proteases are important virulence factors, which are usually secreted in insect integument during spore germination and participate in the penetration process of host cuticles . The overexpression of these toxic protease can significantly enhance the virulence of pathogenic fungi . Unlike mammals, insects lack lymphocytes or immunoglobulins, and serine protease inhibitors are considered to play an important role in insect immunity . Our previous studies systematically identified immune-related silkworm protease inhibitors and found that many protease inhibitors with the trypsin inhibitor-like cysteine-rich domain (TIL) were upregulated after microbial infection, implying that TIL-type protease inhibitors may be involved in the immune process of silkworms . Two structurally unique TIL-type protease inhibitors, BmSPI38 and BmSPI39, can block the harmful melanization induced by cuticle-degrading protease 1 (CDEP-1) and inhibit the conidial germination of Beauveria bassiana, thereby enhancing the antifungal ability of silkworms . In addition, studies have found that many protease inhibitors, especially TIL protease inhibitors, can be secreted into the cocoon layer during silk secretion and provide effective protection for the cocoon shell and pupa by inhibiting the activities of exogenous proteases secreted by pathogenic microorganisms . These results indicate that such inhibitors can be used as fungal resistance factors in the field of medicine and agriculture. Our previous study found that the recombinant protease inhibitor BmSPI39 is prone to spontaneous polymerization, forming dimers, trimers and tetramers . Further research has shown that BmSPI39 mainly exists and functions in the form of a tetramer in silkworm tissues, rather than a monomer . To date, the activity and function of BmSPI39 are well understood, but the effect of multimerization on its inhibitory activity and antifungal ability remains unknown. In addition, the structural homogeneity of recombinant protein expressed by the single-copy BmSPI39 gene is poor, which greatly limits its development and application. It is urgent to explore whether BmSPI39 tandem multimeric protein with better structural homogeneity, higher activity and a stronger antifungal ability can be obtained by protein engineering. In this study, we intend to construct the expression vectors of BmSPI39 homomeric tandem multimers; obtain the recombinant multimeric protein using the prokaryotic expression system; screen the tandem multimeric proteins with better structural homogeneity, stronger activity and higher exogenous expression level; and explore the influence of multimerization on its inhibitory activity and antifungal ability. This study will not only help to deepen the understanding of the action mechanism of BmSPI39 and provide an important theoretical basis and new strategies for cultivating antifungal transgenic silkworms, but it will also promote its exogenous production and development and application in the medical field. 2. Materials and Methods 2.1. Fungi and Reagents TransStart(r) TopTaq DNA Polymerase was purchased from TransGen Biotech (Beijing, China). Nde I, Not I, BamH I and Bgl II endonuclease were purchased from Takara (Dalian, China). Proteinase K from Tritirachium album limber were purchased from Roche (Mannheim, Germany). Subtilisin A from Bacillus licheniformis, N-acetyl-D,L-phenylalanine-b-naphthylester and Fast Blue B Salt were purchased from Sigma-Aldrich (St. Louis, MO, USA). Fluorescein isothiocyanate (FITC)-labeled casein was purchased from Thermo Fisher Scientific (Waltham, MA, USA). Escherichia coli BL21(DE3) competent cells were purchased from Sangon Biotech (Shanghai, China). E. coli Origami 2(DE3), B. bassiana, Saccharomyces cerevisiae and Candida albicans were all preserved by the College of Biological Science and Engineering, Shaanxi University of Technology. 2.2. Vector Construction of the Basic Units A PCR amplification was performed using a previously constructed BmSPI39-p28 plasmid as a template, BmSPI39-Nde I-BamH I-F as the upstream primer and BmSPI39-Not I-R, BmSPI39-Bgl II-R or BmSPI39-L-Bgl II-R as the downstream primers (Table 1). The conditions of the PCR were as follows: predenaturation at 94 degC for 3 min; 30 cycles of denaturation at 94 degC for 30 s, annealing at 58 degC for 30 s, extension at 72 degC for 30 s; final extension at 72 degC for 10 min. The PCR products were detected by electrophoresis using 1.5% agarose gel. The target gene fragments Nde I/BamH I-SPI39-Not I (255 bp), Nde I/BamH I-SPI39-Bgl II (248 bp) and Nde I/BamH I-SPI39L-Bgl II (293 bp) were recovered and ligated into the pEASY-T1 simple cloning vector (TransGen Biotech) and then transformed into E. coli Trans-T1 component cells (TransGen Biotech). The positive clones obtained by colony PCR screening were verified by sequencing. 2.3. Expression Vector Construct of BmSPI39 Tandem Multimers The Nde I/BamH I-SPI39-Not I plasmid and p28 expression vector were double digested by Nde I and Not I, and then the Nde I/BamH I-SPI39-Not I-p28 plasmid was constructed under the action of the T4 ligase (Takara). The recombinant vector was named the His6-SPI39-monomer expression vector. BamH I (G/GATCC) and Bgl II (A/GATCT) are a pair of isocaudarners. The basic unit vectors Nde I/BamH I-SPI39-Bgl II and Nde I/BamH I-SPI39L-Bgl I were double digested with Nde I and Bgl I, while the constructed His6-SPI39-monomer expression vector was double digested with Nde I and BamH I. Two tandem dimer expression vectors, His6-SPI39-dimer and His6-SPI39L-dimer, were obtained by ligating the recovered Nde I/BamH I-SPI39-Bgl II and Nde I/BamH I-SPI39L-Bgl II fragments with His6-SPI39-monomer vector fragments, respectively. Similarly, the homo-trimer expression plasmids (His6-SPI39-trimer and His6-SPI39L-trimer) can be constructed by ligating Nde I/BamH I-SPI39-Bgl II and Nde I/BamH I-SPI39L-Bgl II fragments into the dimer expression plasmids (His6-SPI39-dimer and His6-SPI39L-dimer) using the isocaudomer method, respectively. The homo-tetramer expression plasmids (His6-SPI39-tetramer and His6-SPI39L-tetramer) were constructed on the basis of homo-trimer expression plasmids (His6-SPI39-trimer and His6-SPI39L-trimer). The constructed expression plasmid of BmSPI39 homo-tandem multimers were verified by double enzyme digestion using endonuclease Nde I and Not I and were sent to the company for sequencing verification. 2.4. Protein Expression and Purification The constructed expression plasmids of the BmSPI39 tandem multimers were transformed into E. coli BL21(DE3) and Origami 2(DE3) strains and expressed as fusion proteins with 12 residues of a polyhistidine tag (MGHHHHHHMGGS) at the N-terminus. When the OD600 of the culture reached 0.6-1.0, the protein expression was induced with 0.2 mmol/L IPTG at 37 degC for 5 h or at 16 degC for 20 h. After centrifugation at 6000 rpm for 30 min, the E. coli cells were collected and suspended with a binding buffer (20 mmol/L Tris-HCl, 500 mmol/L NaCl, pH 7.9). After ultrasonic crushing and centrifugation, the supernatant of the bacteria was collected and analyzed using 16.5% SDS-PAGE. The recombinant proteins from the BL21(DE3) cells were purified with Ni2+-NTA (nitrilotriacetic acid) affinity chromatography (Sangon Biotech, Shanghai, China). The supernatant containing recombinant protein was filtered with a 0.45 mm filter membrane and then loaded onto a 1 mL Ni2+-NTA affinity chromatography column. The flow rate was controlled at 0.5-1.0 mL/min. The column was washed and eluted sequentially by a binding buffer supplemented with 0, 20, 50, 100 and 400 mmol/L imidazole until no more protein was eluted. The eluted portion of the highly enriched target protein was collected based on 16.5% SDS-PAGE. The second round of immobilized-nickel affinity chromatography was performed after the removal of imidazole by dialysis. After electrophoretic detection, the pure proteins of tandem multimers were finally collected and dialyzed to a 20 mmol/L PBS buffer (pH 7.8) for storage. 2.5. In-Gel Activity Staining of Protease Inhibitor The induced expression protein samples were mixed with a 4x Native PAGE loading buffer (40 mmol/L Tris-HCl pH 8.0, 40% glycerol, 0.032% bromophenol blue) and separated by 10% Native PAGE, followed by the in-gel activity staining of the protease inhibitor. The in-gel activity staining of the protease inhibitors referred to the previous reported method . The electrophoresed gel was placed in a protease solution and was incubated for 30 min at 37 degC, 45 rpm, without light. After recovering the protease solution, the gel was washed with ddH2O and then left for 30 min at 37 degC in dark conditions. At a volume ratio of 1:10, the mixture of the substrates solution (200 mg N-acetyl-D,L-phenylalanine-b-naphthylester dissolved in 100 mL of N,N'-dimethylformamide) and staining solution (100 mg of Fast Blue B Salt dissolved in 100 mL of 0.1 mol/L pH 8.0 Tris-HCl buffer containing 20 mmol/L CaCl2) were added and incubated for 15 min at 37 degC, 45 rpm. Subsequently, the staining solution was discarded, and the gel was washed with ddH2O to terminate the reaction. The gels were stained fuchsia due to the diazotization coupling reaction of b-naphthol that was produced by protease hydrolyzed N-acetyl-D,L-phenylalanine-b-naphthylester on the gel . If the protease inhibitor in the gel can inhibit the corresponding protease activity, its location will not be stained and will appear as a white band. 2.6. Protease Inhibition Assays The moles of the BmSPI39 tandem multimeric proteins were converted to the moles of TIL domains based on the number of TIL domains in the protease inhibitor molecules. For example, 1 mol His6-SPI39-dimer and His6-SPI39L-dimer proteins have 2 mol TIL domains. A total of 0.003 nmol of subtilisin (MW 27 kDa) or proteinase K (MW 28.8 kDa) was mixed with the protease inhibitor and supplemented with a buffer (100 mmol/L Tris-HCl, 20 mmol/L CaCl2, pH 8.0) to a final volume of 100 mL. Then, it was incubated at 37 degC for 30 min. The molar ratio of the TIL domain of the inhibitor to protease was set as 0.5, 1, 2, 5, 10 and 15. Then, 100 mL of 10 mg/mL FITC-casein was added and incubated at 37 degC for 60 min in the dark. The fluorescence intensity was measured at a 485 nm excitation and 528 nm emission wavelength, and the residual enzyme activity was calculated. The inhibitory activity of the protease inhibitor against protease was assessed with the following formula: residual enzyme activity% = enzyme activity of experimental group/enzyme activity of control group x 100%. 2.7. Assays of Conidial Germination of B. bassiana B. bassiana was inoculated in a solid potato dextrose agar (PDA) medium and cultured for 10 days at 28 degC. Spores were collected and mycelium was removed by filtration with sterile absorbent cotton. A conidial suspension was prepared at a concentration of 9 x 107 conidia/mL using sterilized ddH2O. A total of 200 mL of a potato dextrose liquid (PDL) medium was mixed with 100 mL of a 0.03 nmol/mL TIL domain equivalent protease inhibitor, and then 100 mL of a conidial suspension was added and incubated at 28 degC and 80 rpm for 4 h, 8 h and 12 h. The control group was treated with an equal volume of 20 mmol/L PBS. The conidial germination rate was calculated via microscopic observations after different incubation times. A conidium was considered germinated when the length of its germination tube was greater than or equal to its width. All the experiments were repeated three times. The conidial germination rate% = number of germinated conidia/total number of conidia x 100%. 2.8. Fungal Growth Inhibition Assay C. albicans or S. cerevisiae cultured overnight were inoculated into the potato dextrose liquid medium at a ratio of 1:1000 and were cultured at 28 degC and 100 rpm for 24 h. Fungal cultures were filtered using sterile absorbent cotton and then centrifuged at 4 degC and 4000 g for 20 min to collect the spores. After cell counting, 1 x 105 spores/mL spore suspensions were prepared using sterile ddH2O. In total, a 160 mL spore suspension, 160 mL PDL medium and 160 mL of a 0.01 nmol/mL TIL domain equivalent protease inhibitor were mixed in a 2.0 mL centrifuge tube. A 20 mmol/L PBS was used as the negative control, and 100 mmol/L EDTA was used as a positive control. The mixture was incubated by shaking at 28 degC and 100 rpm. After incubation for 0 h, 12 h, 24 h, 36 h and 48 h, 100 mL of the culture was taken into the 96-well plate. The absorbance at 600 nm was measured, and the fungal growth kinetics curve was drawn. All the assays were repeated three times. The fungal growth inhibition rate was calculated according to the following formula: Inhibitory rate% = (1 - OD600exp/OD600pbs) x 100%. 2.9. Statistical Analysis All statistical analyses of the data were performed using the Data Processing System (DPS) software version 9.01. Statistically significant differences were assessed by using a one-way analysis of variance (ANOVA). The error bar represents the standard error of the mean (n = 3). Different lowercase letters "a to e" indicate significant differences between the treatment groups at p < 0.05, while those marked with one identical letter mean no significant differences between the treatment groups at p < 0.05. 3. Results 3.1. Design and Construction of Expression Vector of BmSPI39 Tandem Multimers In order to obtain the active proteins of the BmSPI39 homologous tandem multimers, two sets of expression vector construction schemes were designed . In the first strategy, a flexible linker sequence was added between the fusion proteins. The second strategy did not add a linker sequence between the fusion proteins. A linker is an amino acid chain that connects two fusion proteins. It has a certain flexibility that helps the protein fold correctly during protein expression, allowing the proteins on both sides to perform their independent functions . Glycine-rich flexible linkers such as (GGGGS)n are the most commonly used linkers for separating different parts of the fusion protein. The linker sequence used here was "GGGGSGGGGSGGGGS", and its corresponding coding sequence was "GGCGGTGGTGGCTCAGGCGGTGGTGGCTCAGGCGGTGGTGGCTCA". Firstly, the basic unit vector Nde I/BamH I-SPI39-Not I, Nde I/BamH I-SPI39-Bgl II and Nde I/BamH I-SPI39L-Bgl II were constructed. Then, the gene fragment "Nde I/BamH I-SPI39-Not I" was inserted into a p28 expression vector by double-enzyme digestion to construct the His6-SPI39-monomer expression vector. Next, the gene fragments Nde I/BamH I-SPI39-Bgl II and Nde I/BamH I-SPI39L-Bgl II were inserted into the Nde I/BamH I sites of the plasmid His6-SPI39-monomer by using the isocaudomer method, respectively. The recombinant plasmids His6-SPI39-dimer and His6-SPI39L-dimer were obtained. Finally, homo-trimer expression plasmids (His6-SPI39-trimer and His6-SPI39L-trimer) and homo-tetramer expression plasmids (His6-SPI39-tetramer and His6-SPI39L-tetramer) were constructed by using the isocaudomer method. To obtain gene fragments of Nde I/BamH I-SPI39-Not I (255 bp), Nde I/BamH I-SPI39-Bgl II (248 bp) and Nde I/BamH I-SPI39L-Bgl II (293 bp), a PCR amplification was performed using BmSPI39-Nde I-BamH I-F as the upstream primer and BmSPI39-Not I-R, BmSPI39-Bgl II-R or BmSPI39-L-Bgl II-R as the downstream primers. The PCR products were detected by using agarose gel electrophoresis. Three specific target bands were detected at their expected sizes on agarose gels . The above three gene fragments were cloned into a pEASY-T1 simple cloning plasmid, and the positive clones were screened by colony PCR. The expression vectors of BmSPI39 tandem multimers were constructed as shown in Figure 1A. The results of Nde I/Not I double digestion and sequencing showed that the expression vectors His6-SPI39-monomer, His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer were successfully constructed . 3.2. Protein Expression and Purification of BmSPI39 Tandem Multimers In order to obtain sufficient BmSPI39 tandem multimeric proteins for subsequent research, the constructed expression vectors were transformed into E. coli cells for induced expression. The protein samples extracted from BL21(DE3) and Origami 2 cells were separated using a 16.5% SDS-PAGE . The theoretical molecular weights of His6-SPI39-monomer, His6-SPI39-dimer, His6-SPI39-trimer and His6-SPI39-tetramer are 9506.58, 17894.94, 26283.30 and 34671.67 Da, respectively. The theoretical molecular weights of His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer are 18840.80, 28175.02 and 37509.24 Da, respectively. The SDS-PAGE results showed that the BmSPI39 tandem multimeric proteins were expressed in the soluble form in both the BL21(DE3) and Origami 2(DE3) strains, and the band position of the target protein showed a step-like change with increasing molecular weight. His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer were highly expressed in the supernatants of BL21(DE3) and Origami 2(DE3). The expression of His6-SPI39-monomer was low in the supernatant of BL21(DE3) and relatively high in the supernatant of Origami 2(DE3). Overall, BL21(DE3) was more suitable for expressing BmSPI39 tandem multimeric proteins than Origami 2(DE3). In order to obtain the pure protein of the BmSPI39 tandem multimeric proteins, BL21(DE3) harboring recombinant expression vectors were mass cultured and induced for expression. The target proteins were purified by two repeats of Ni2+-NTA affinity chromatography. The SDS-PAGE results showed that the obtained His6-SPI39-monomer, His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer proteins had high purity and could meet the requirements of subsequent experiments . 3.3. Activity and Structural Homogeneity Analysis of BmSPI39 Tandem Multimers To explore the effect of tandem multimerization on the activity and structural homogeneity of BmSPI39, the tandem BmSPI39 multimers expressed in BL21(DE3) and Origami 2(DE3) were analyzed by in-gel activity staining . The results of the activity staining showed that all BmSPI39 tandem multimeric proteins expressed in the two strains had inhibitory activity against subtilisin and proteinase K. As the number of tandem units increased, the inhibitory bands of the recombinant proteins showed a stepped distribution. A strong active band was mainly detected for each tandem protein, while an extremely weak active band was also detected above the main active bands of His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer. Under the same treatment and loading conditions, His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer expressed in E. coli cells showed far stronger inhibitory activities against subtilisin than His6-SPI39-monomer. The tandem multimeric proteins, except for His6-SPI39L-tetramer, also exhibited more potent inhibitory activities against proteinase K than His6-SPI39-monomer. His6-SPI39-monomer showed a stronger inhibitory activity on proteinase K than it did on subtilisin, while His6-SPI39L-tetramer showed a stronger inhibitory activity towards subtilisin than it did towards proteinase K . In general, the inhibitory activities of the tandem multimeric proteins expressed in Origami 2(DE3) were stronger than that expressed in BL21(DE3), but the active forms expressed in BL21(DE3) were more uniform. The above results indicate that tandem multimerization based on protein engineering can greatly improve the inhibitory activity and structural homogeneity of BmSPI39. 3.4. Comparison of Inhibitory Capacity of BmSPI39 Tandem Multimers against Microbial Protease To further explore the effect of tandem multimerization on BmSPI39 activity, subtilisin and proteinase K were selected for protease inhibition activity assays. The residual enzyme activities of the proteases treated by seven forms of protease inhibitors were determined under the same molar equivalent of the TIL domain. The results showed that the inhibitory activities of His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer towards subtilisin were significantly stronger than His6-SPI39-monomer . Among them, His6-SPI39-trimer had the strongest inhibitory activity against subtilisin . His6-SPI39-monomer showed stronger inhibition towards proteinase K than His6-SPI39-dimer, His6-SPI39-tetramer and His6-SPI39L-tetramer, but it was significantly weaker than His6-SPI39-trimer, His6-SPI39L-dimer and His6-SPI39L-trimer . There was no significant difference in the inhibitory activity towards proteinase K between His6-SPI39-trimer, His6-SPI39L-dimer and His6-SPI39L-trimer . Overall, His6-SPI39-trimer showed the strongest inhibitory activity against subtilisin and proteinase K. The above results indicate that tandem multimerization can greatly improve the inhibitory activity of BmSPI39 against proteases, and each tandem protein has a certain preference for inhibiting different proteases. 3.5. Evaluation of Inhibitory Ability of BmSPI39 Tandem Multimers on Conidial Germination of Silkworm Pathogenic Fungi B. bassiana To evaluate the inhibitory ability of BmSPI39 tandem multimeric proteins on the conidial germination of B. bassiana, an important pathogenic fungus of B. mori, conidia, was incubated with protease inhibitors containing the same molar equivalent of the TIL domain. The results showed that all forms of tandem proteins could significantly inhibit the conidial germination of B. bassiana . His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-trimer and His6-SPI39L-tetramer inhibited conidial germination more effectively than His6-SPI39-monomer after incubation for 8 h. After incubation for 12 h, the conidial germination rate of the PBS treatment group had reached 93.88%, while that of the His6-SPI39-monomer, His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer treatment groups were 69.78%, 75.16%, 71.55%, 70.04%, 68.13%, 60.52% and 62.96%, respectively. His6-SPI39L-trimer and His6-SPI39L-tetramer still showed stronger inhibition on conidial germination than His6-SPI39-monomer, while His6-SPI39-dimer showed less inhibition on conidial germination than His6-SPI39-monomer. There was no significant difference between the His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer and His6-SPI39-monomer treatment groups. The above results indicate that tandem multimerization can effectively enhance the ability of BmSPI39 to inhibit the conidial germination of B. bassiana. 3.6. Evaluation of the Inhibitory Effects of BmSPI39 Tandem Multimers on the Growth of Single-Celled Fungus Saccharomyces cerevisiae and Opportunistic Human Pathogen Candida albicans To further investigate the inhibitory effect of BmSPI39 tandem multimers on the growth of other fungi, the single-cell fungus S. cerevisiae and opportunistic human pathogen C. albicans were selected for fungal inhibition tests. The results showed that all forms of tandem proteins could significantly inhibit the growth of S. cerevisiae and C. albicans . When incubated for 48 h, the inhibitory rate of His6-SPI39-monomer on the growth of Saccharomyces cerevisiae was only 5.81%, while the inhibitory rates of His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer were 10.45%, 32.28%, 30.74%, 28.76%, 28.94% and 27.77%, respectively . After incubation for 36 h, the inhibitory rates of His6-SPI39-monomer, His6-SPI39-dimer, His6-SPI39-trimer, His6-SPI39-tetramer, His6-SPI39L-dimer, His6-SPI39L-trimer and His6-SPI39L-tetramer against C. albicans were 16.97%, 15.28%, 10.35%, 11.43%, 11.97%, 20.10% and 15.40%, respectively . His6-SPI39L-trimer had the strongest inhibitory effect on C. albicans among all the tandem multimeric proteins. These results indicate that BmSPI39 tandem multimers have certain inhibitory effects on S. cerevisiae and C. albicans, and the inhibitory ability of BmSPI39 against these two fungi can be enhanced by tandem multimerization. 4. Discussion In this study, we successfully obtained the active tandem multimeric proteins of BmSPI39 by means of protein engineering and confirmed that tandem multimerization can not only greatly improve the structural homogeneity of BmSPI39 recombinant protein but can also improve the inhibitory activity of BmSPI39 protein against subtilisin and proteinase K. The tandem multimerization of BmSPI39 can also enhance its inhibitory ability against B. bassiana, single-cell fungus S. cerevisiae and opportunistic human pathogen C. albicans. Protease inhibitors are the main regulators of protease catalytic activity in vivo, which can bind protease molecules and inhibit their physiological activities. Protease inhibitors play an important role in many physiological processes such as digestion, coagulation, phenoloxidase cascade, cell migration and inflammatory reaction . The multimerization of proteins is a common phenomenon in living organisms. Many receptors, fungal immunomodulatory proteins, proteases and so on tend to exist and function in the form of multimers. Such a multimerization phenomenon has also been found in protease inhibitors, which are important for regulating the advanced structure and biological activity of protease inhibitors . Ecotin is a serine protease inhibitor that can be produced by hundreds of microorganisms, including pathogens. Ecotin has a very broad inhibitory specificity for almost all serine proteases in the chymotrypsin, trypsin and elastase superfamily, which protects the microorganism from the host immune response . It was found that the dimerized Ecotin can combine with protease to form heterotetramers with three distinct interfaces . Cystatin C, a cysteine protease inhibitor, plays an important role in various physiological and pathological processes such as vascular remodeling and inflammation, and its activity can be regulated by changing the multimerization state . DM43 is a homodimerized metalloproteinase inhibitor isolated from the serum of Didelphis marsupialis, which binds noncovalently to the metalloproteinase Jararhagin from Bothrops jararaca snake venom and effectively neutralizes its toxicity . Studies have shown that dimerization is critical in determining the structure and stability of the DM43 protein, thus adapting its conformation to a diverse range of environments and binding proteins . Our previous studies found that the TIL-type protease inhibitors BmSPI38 and BmSPI39 in silkworm could inhibit the invasion of pathogenic fungi by inhibiting its virulence protease . The recombinant proteins encoded by either single-copy BmSPI38 or single-copy BmSPI39 genes have poor homogeneous in vitro and are prone to multimerization, forming dimers, trimers and tetramers . Western blot results showed that the physiological forms of BmSPI38 and BmSPI39 in various tissues were mainly tetramer and a small amount of trimer, suggesting that multimerization is extremely important for their physiological functions . In this study, the structural homogeneity and expression level of recombinant BmSPI39 protein was greatly improved using the strategy of tandem gene fusion expression . The construction of tandem expression vectors can effectively improve the expression level and structural stability of small molecular recombinant proteins (peptides) and shield the harmful effect of toxic proteins on the host, so it is widely used . Thymosin beta4 (Tb4) is one of the major actin regulatory factors in the human body, which has a wide range of biological activities, and it is closely related to cytoskeletal balance, inflammatory response, angiogenesis, vascular regeneration, cell regulation and corneal and myocardial repair. 4xTb4 protein was successfully expressed in E. coli and demonstrated similar or better activity than the existing commercial Tb4 protein . Six copies of angiotensin I-converting enzyme inhibitory peptide (ACE-IP) genes were concatenated and inserted into an expression vector to achieve the fusion expression of the tandem peptide in E. coli BL21 (DE3) pLysS . In addition, tandem expression also provided a convenient and economical method for the large-scale production of the antidiabetic drug Momordica charantia peptide MC6 . Previous studies have confirmed that BmSPI39 can strongly inhibit subtilisin, proteinase K, Aspergillus melleus protease and the B. bassiana-sourced virulent protease CDEP-1 . In this study, it was found that tandem multimerization could greatly improve the inhibitory activity of BmSPI39 against subtilisin. It should be noted that although His6-SPI39-monomer showed significantly weaker inhibitory activity against proteinase K than His6-SPI39-trimer, His6-SPI39L-dimer and His6-SPI39L-trimer, it was stronger than His6-SPI39-trimer, His6-SPI39-tetramer and His6-SPI39L-tetramer, suggesting that each tandem protein has a certain selectivity for the inhibition of different proteases. To date, there is no advanced structural data on BmSPI39 binding to proteases, and the formation mechanism of BmSPI39 multimers and the specific action mechanism on different proteases need to be further studied. Previous studies found that BmSPI38 and BmSPI39 can not only inhibit the harmful melanization induced by B. bassiana virulence protease but also the conidial germination of B. bassiana, thereby improving the survival rate of the silkworm . This study further confirmed the inhibition of BmSPI39 on the conidial germination of B. bassiana, and for the first time found that tandem multimerization could effectively enhance its inhibitory ability on the conidial germination of B. bassiana . We briefly summarized the reported multimerization studies of cysteine protease inhibitors, serine protease inhibitors and metalloprotease inhibitors and found that most of the protease inhibitors function as dimers and that the higher-order multimeric forms are further oligomerized based on the dimeric structure . Dimerization is also present for many serine protease inhibitors with antifungal effects. It was found that the serine protease inhibitor BmSPI51 in the silkworm cocoon shell can significantly inhibit the spore growth of B. bassiana, C. albicans and S. cerevisiae . The SDS-PAGE results showed that the apparent molecular weight of BmSPI51 recombinant protein obtained by the prokaryotic expression technique was about 12 kDa, which was consistent with its dimer size, suggesting that it may function as a dimer . In addition, corn trypsin inhibitor (TI) with a molecular weight of about 14 kDa can inhibit the conidial germination and mycelial growth of plant pathogenic fungi. The SDS-PAGE results showed that the recombinant TI protein expressed in E. coli mainly existed in the form of a monomer, and a few existed in the form of a dimer . Whether such dimerization will increase the activity and stability of a recombinant TI protein remains unclear, and the molecular mechanism of dimerization also requires further investigation. As is well known, fungal infection has become one of the major threats to global public health, and problems such as toxic effects and drug resistance brought by existing antifungal drugs are increasingly prominent. Therefore, it is urgent to find new, efficient and safe antifungal drugs. C. albicans is the most common opportunistic pathogen among invasive fungi. In this study, we found that the BmSPI39 protein had an obvious inhibitory effect on C. albicans, and tandem multimization could significantly enhance its antifungal ability. Although many studies have confirmed the antifungal effect of B. mori protease inhibitors, their antifungal spectrum and specific antifungal mechanism are not fully understood, and more experimental data are still needed to support them. The development and application of protease inhibitors with antifungal effects need to be strengthened. It should be noted that His6-SPI39-monomer is much more effective in inhibiting C. albicans than S. cerevisiae, which may be related to its strong ability to inhibit proteinase K . The types and abundance of proteases secreted by different fungi are very different during growth. Proteinase K used in this study is a powerful proteolytic enzyme derived from C. albicans, which can digest natural keratin and belongs to the serine protease of the Peptidase S8 family. 5. Conclusions In this study, we successfully achieved the soluble expression of the tandem multimers of the silkworm protease inhibitor BmSPI39 in E. coli and confirmed that the tandem multimerization could significantly improve the structural homogeneity and antifungal ability of BmSPI39. This study will not only help to deepen people's understanding of the action mechanism of BmSPI39 and provide an important theoretical basis and new strategies for cultivating antifungal transgenic silkworm materials, but it will also promote its exogenous production and development and application in the medical field. Acknowledgments We thank Congzhao Zhou (University of Science and Technology of China) for kindly providing the p28 plasmid and Zhaoming Dong (Southwest University) for the advice and assistance. Author Contributions Conceptualization, Y.L.; data curation, Y.L., Y.W. and X.Y.; formal analysis, Y.L. and R.Z.; funding acquisition, Y.L.; investigation, Y.L., Y.W., X.Y., M.W., Z.Z. and C.C.; methodology, Y.L. and P.Z.; project administration, Y.L., R.Z. and P.Z.; resources, Y.L.; software, Y.L. and Y.W.; supervision, Y.L. and P.Z.; writing--original draft, Y.L.; writing--review and editing, R.Z. and P.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Design and construction of expression vector of BmSPI39 tandem multimers. (A) Schematic diagram of expression vector construction of BmSPI39 tandem multimers. Glycine-rich flexible linker was used to connect protein modules. "SPI39" represents the coding sequence of BmSPI39 protein module, and "SPI39L" represents the coding sequence of BmSPI39 protein module connected by flexible linker. The amino acid sequence of linker is "GGGGSGGGGSGGGGS". The coding sequence of linker is "GGCGGTGGTGGCTCAGGCGGTGGTGGCTCAGGCGGTGGTGGCTCA". BamH I (G/GATCC) and Bgl II (A/GATCT) are a pair of isocaudarners. (B) Agarose gel electrophoresis detection of PCR products of basic unit fragments. Target products of the PCR are indicated by red arrows. (C) Double digestion of recombinant expression vector using Nde I/Not Ienzymes. p28 is a derivative expression plasmid of pET28b. The target fragments produced by double digestion are shown by red arrows. The bands of about 5000 bp are linearized vector fragments produced by double digestion. Figure 2 Protein expression and purification of BmSPI39 tandem multimers. (A) SDS-PAGE analysis of BmSPI39 tandem multimers expressed in BL21(DE3) cells; (B) SDS-PAGE analysis of BmSPI39 tandem multimers expressed in Origami 2(DE3) cells; (C) SDS-PAGE analysis of the purified BmSPI39 tandem multimers. The E. coli cells transformed with p28 plasmid were used as the control. "Supernatant" indicates the supernatant part of E. coli cells. Arrows represent the fusion proteins of BmSPI39 tandem multimers. In addition to the target protein bands indicated by the arrows, some weak bands were found, which may be the impurity proteins coeluted with the target protein. Figure 3 Activity and structural homogeneity analysis of BmSPI39 tandem multimers using in-gel activity staining. (A) Activity analysis of BmSPI39 tandem multimers expressed in BL21(DE3) cells; (B) activity analysis of BmSPI39 tandem multimers expressed in Origami 2(DE3) cells. "SI" and "KI" indicate subtilisin inhibitors and proteinase K inhibitors, respectively. The supernatant part of E. coli cells transformed with p28 plasmid was used as a negative control. The hemolymph of the fifth instar larvae of the silkworm contains a variety of protease inhibitors, so it can be used as a positive control to detect whether the in-gel activity staining of protease inhibitor is successful. Figure 4 Comparison of inhibitory capacity of BmSPI39 tandem multimers against microbial protease using protease inhibition assays. (A) Inhibitory effects of increasing concentrations of BmSPI39 tandem multimers against subtilisin A from B. licheniformis; (B) inhibitory activities of BmSPI39 tandem multimers against subtilisin when the ratio of TIL domain to protease is 5; (C) inhibitory effects of increasing concentrations of BmSPI39 tandem multimers against proteinase K from E. album; (D) inhibitory activities of BmSPI39 tandem multimers against proteinase K when the ratio of TIL domain to protease is 10. Error bars represent the standard error of the mean (n = 3). Different letters "a-e" indicate a significant difference between groups (p < 0.05), and one identical letter indicates no significant difference between groups (p < 0.05). Figure 5 Evaluation of inhibitory ability of protease inhibitors on B. bassiana. (A) Inhibitory effects of BmSPI39 tandem multimers on conidial germination; (B) microscopic observation of conidial germination in different treatment groups after incubation for 12 h. The control group was treated with equal volume of 20 mmol/L PBS. Error bars represent the standard error of the mean (n = 3). Different letters "a-d" indicate a significant difference between groups (p < 0.05), and one identical letter indicates no significant difference between groups (p < 0.05). Figure 6 Evaluation of the inhibitory effects of protease inhibitors on single-celled fungus S. cerevisiae and opportunistic human pathogen C. albicans. (A) Inhibitory effects of BmSPI39 tandem multimers on the growth of S. cerevisiae; (B) statistical analysis of growth inhibition rate of S. cerevisiae after incubation for 48 h; (C) inhibitory effects of BmSPI39 tandem multimers on the growth of C. albicans; (D) statistical analysis of growth inhibition rate of C. albicans after incubation for 36 h. An equal volume of sterile 20 mmol/L PBS was used as a negative control and 100 mmol/L EDTA was applied as positive control. Error bars represent the standard error of the mean (n = 3). Different letters "a-e" indicate a significant difference between groups (p < 0.05), and one identical letter indicates no significant difference between groups (p < 0.05). cells-12-00693-t001_Table 1 Table 1 Primers required for expression vector construction. Primers Sequence (5' - 3') BmSPI39-Nde I-BamH I-F CGCCATATGGGCGGATCCTTTGAAAAAGATTGTCCTGAGAATTCT BmSPI39-Not I-R ATTTGCGGCCGCTTATGACTGTTGTTTATGGAAACAGTTG BmSPI39-Bgl II-R GAAGATCTTGACTGTTGTTTATGGAAACAGTTGAC BmSPI39-L-Bgl II-R GAAGATCTTGAGCCACCACCGCCTGAGCCACCACCGCCTGAGCC ACCACCGCCTGACTGTTGTTTATGGAAACAGTTGAC Nde I (CATATG), BamH I (GGATCC), Not I (GCGGCCGC) and Bgl II (AGATCT) restriction sites are underlined. The coding sequence of linker (L) is highlighted in gray. Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References 1. Xia Q. Zhou Z. Lu C. Cheng D. Dai F. Li B. Zhao P. Zha X. Cheng T. Chai C. 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PMC10000548 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050962 diagnostics-13-00962 Article Sphenoidal Foramen Ovale in the Slovenian Population: An Anatomical Evaluation with Clinical Correlations Sink Ziga Formal analysis Investigation Writing - original draft 1* Umek Nejc Conceptualization Methodology Formal analysis Writing - review & editing 1* Alibegovic Armin Resources Writing - review & editing Supervision 2 Cvetko Erika Conceptualization Methodology Resources Writing - review & editing Supervision Funding acquisition 1 Jahng Geon-Ho Academic Editor 1 Institute of Anatomy, Faculty of Medicine, University of Ljubljana, Korytkova 2, 1000 Ljubljana, Slovenia 2 Institute of Forensic Medicine, Faculty of Medicine, University of Ljubljana, Korytkova 2, 1000 Ljubljana, Slovenia * Correspondence: [email protected] (Z.S.); [email protected] (N.U.) 03 3 2023 3 2023 13 5 96231 1 2023 18 2 2023 01 3 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). The foramen ovale (FO) is a crucial feature of the skull base, serving as a passage for clinically important neurovascular structures. The present study aimed to provide a comprehensive morphometric and morphologic analysis of the FO and highlight the clinical significance of the anatomical characterization. A total of 267 FO were analyzed in skulls obtained from deceased inhabitants of the Slovenian territory. The anteroposterior (length) and the transverse (width) diameters were measured using a digital sliding vernier caliper. Dimensions, shape, and anatomical variations of FO were analyzed. The mean length and width of the FO were 7.13 and 3.71 mm on the right side and 7.20 and 3.88 mm on the left side. The most frequently observed shape was oval (37.1%), followed by almond (28.1%), irregular (21.0%), D-shaped (4.5%), round (3.0%), pear-shaped (1.9%), kidney-shaped (1.5%), elongated (1.5%), triangular (0.7%), and slit-like (0.7%). In addition, marginal outgrowths (16.6%) and several anatomical variations were noted, including duplications, confluences, and obstruction due to a complete (5.6%) or incomplete (8.2%) pterygospinous bar. Our observations revealed substantial interindividual variation in the anatomical characteristics of the FO in the studied population, which could potentially impact the feasibility and safety of neurosurgical diagnostic and therapeutic procedures. foramen ovale sphenoid bone anatomical variations morphometry trigeminal nerve Slovenian Research AgencyP3-0043 This research was funded by the Slovenian Research Agency, Grant No. P3-0043. pmc1. Introduction The sphenoid bone constitutes the base of the skull between the frontal, temporal, and occipital bones. Its greater wing contains three consistent and a few small variable foramina. The consistent foramina are the foramen ovale (FO), the foramen rotundum (FR), and the foramen spinosum (FS). They act as conduits for several cranial neurovascular structures and are important in various clinical conditions and procedures. The FO is located in the posterior aspect of the greater wing of the sphenoid bone, posterolateral to the FR, anteromedial to the FS, and lateral to the foramen lacerum (FL). It connects the middle cranial fossa to the infratemporal fossa and transmits the mandibular nerve, the lesser petrosal nerve, the accessory meningeal artery, the emissary veins, and the anterior trunk of the middle meningeal sinus . Its location renders it useful in various diagnostic and therapeutic procedures, including administering anesthesia to the mandibular nerve, trigeminal rhizotomy for managing trigeminal neuralgia, percutaneous biopsy of parasellar lesions, and electroencephalographic temporal lobe analysis during selective amygdalohippocampectomy . Accordingly, the structural characteristics of the FO bear remarkable clinical significance. Anatomical variations of the FO are a commonly observed phenomenon that may interfere with transoval cannulation and hinder surgical access to this area. In addition, aberrant FO anatomy is also etiologically associated with certain pathologies. For example, compression of the mandibular nerve in this region from anomalous shapes or bony outgrowths may lead to the development of trigeminal neuralgia . This study aimed to determine and compare the morphometric and morphological features of the FO in adult human skulls from the Slovenian population with those previously reported in the literature and highlight potential clinical relevance. 2. Materials and Methods The analysis was performed on 126 whole dried adult human skulls and an additional 15 dried human skull halves (3 right and 12 left) of undetermined sex and age, obtained from bodies donated by inhabitants from the territory of the Republic of Slovenia between the years 1965 and 2020 to the anatomical collection of the Institute of Anatomy of the Faculty of Medicine of the University of Ljubljana. Additionally, 30 whole dried adult human skulls were analyzed from the bone collection of the Institute of Forensic Medicine, Faculty of Medicine, University of Ljubljana, Slovenia. A total of 267 FO were analyzed in all specimens. Skulls with evidence of physical damage to the structures of interest, confirmed by inspection with magnifying lenses, were excluded from the analyses. The greater wings of sphenoid bones were observed from the extracranial and intracranial views of the skull base for visualization and measurement of the FO. A thin wire was used to confirm the patency of foramina and rule out false passages. The FO was measured along the anteroposterior (length) and transverse (width) diameters using a digital sliding vernier caliper with a precision of 0.01 mm. The distance between the FO and FS was measured using the same method. The shape of the FO and its potential anatomical variations (marginal bony outgrowths, divisions, duplications, confluences) were carefully recorded and photographed. Additionally, the FO was classified as either foramen-like or canal-like. FO was defined as canal-like when the distance between its outer and inner margins exceeded 2 mm. To minimize the measurement error and bias, each morphometric and morphological parameter was independently measured or assessed twice by at least two independent researchers, and the mean value was used for the analysis. Discordant descriptions or measurements were further evaluated by the other two authors, and consensus was reached through a joint discussion among all authors. Previous studies were also referenced to standardize evaluation protocols and anatomical descriptions . Statistical analysis was performed using GraphPad Prism 9 (GraphPad Software, San Diego, CA, USA). Data are presented as means (standard deviation) or frequencies (proportion). Differences between the right and left sides were analyzed using a paired sample t-test. The differences were considered statistically significant at p < 0.05. The Kolmogorov-Smirnov test was performed for the evaluation of the normality of the distributions. A nonparametric kh2 test was used to detect differences between proportions. The obtained data were compared with previous reports. 3. Results The FO was present in all analyzed 267 sides of dried adult human skulls. The mean anteroposterior diameter or length (longest axis) of the FO was 7.13 mm on the right side and 7.20 mm on the left side. The mean transverse diameter or width (shortest axis) of the FO was 3.71 mm on the right side and 3.88 mm on the left side. The morphometric features of the FO are summarized in Table 1. No statistically significant differences were found in any measured parameter between the left and right sides. The most frequently observed shape of the FO was oval (37.1%), followed by almond (28.1%), irregular (21.0%), D-shaped (4.5%), round (3.0%), pear (1.9%), kidney (1.5%), elongated (1.5%), triangular (0.7%), and slit-like (0.7%) shape. The different FO shapes noted in the present study are shown in Figure 1, while the classification and distribution of FO shapes are summarized in Table 2. There were no statistically significant differences between the left and right sides. Irregular shapes of the FO were a result of marginal bony outgrowths, confluence with other foramina, and complete (5.6%) or an incomplete (8.2%) pterygospinous bar, present either unilaterally or bilaterally. Marginal bony outgrowths were observed in 45 of the 267 (16.6%) skull halves: spines in 24 (9.0%), bony plates in 13 (4.9%), and tubercles in 8 (3.0%). A total of 12 (4.5%) foramina exhibited an irregular marginal morphology as a result of the presence of small marginal outgrowths that did not conform to any of the previously reported classifications. A small foramen was present inside the canal-like FO in 3 cases out of 267 (1.1%). Aberrant anatomical configurations of FO are depicted in Figure 2. The confluence of the FO and the foramen lacerum (FL) was observed in 17 (6.4%) skull sides, 7 (2.6%) unilaterally, and 5 (3.8%) bilaterally. The confluence of the FO with an accessory foramen was observed in 3 (1.1%) skull sides, while the confluence of the FO and foramen of Vesalius was observed in 1 skull side (0.4%). One duplication (0.4%) of the FO due to a bony plate was noted . Additionally, the analyzed FO were classified as either foramen-like (62.2%) or canal-like (37.8%). The incidence of a foramen-like FO was higher on both sides, 65.7% on the right and 58.5% on the left side. 4. Discussion The results of the morphometric analysis of the 267 FO were consistent with those reported in other studies conducted on populations of European, American, African, and Asian descent . However, the majority of existing morphometric studies of FO were limited to measurements of FO length and width (as presented in Table 3). In the present study, the shortest width of an FO measured was 1.30 mm on the right side and 2.33 mm on the left side. It has been suggested that the presence of a narrow FO may result in a restriction of blood flow and possible ischemia of the trigeminal ganglion . Alterations in blood flow and variations in the shape of the venous plexus inside the foramen can affect the mandibular branch of the trigeminal nerve and might therefore be another potential mechanism of trigeminal neuralgia . Li et al. inferred that a narrow FO is associated with primary trigeminal neuralgia and its recurrence after microvascular decompression . Furthermore, a small transverse diameter of an FO may affect the feasibility and safety of transoval cannulation during diagnostic and therapeutic procedures and consequently contribute to adverse events, including blindness, brainstem hematoma, temporal hematoma, carotid artery hemorrhage, and death . A reduced size of an FO may be seen in patients with Paget's disease or osteopetrosis due to structural deformity of the skull base . In contrast, in case of an abnormally enlarged FO, neurinoma of the trigeminal nerve and parasellar tumors should be considered in the differential diagnosis . diagnostics-13-00962-t003_Table 3 Table 3 Comparison of FO dimensions between the present and previous studies. Authors. Year (Country) Number of Skull Sides Longest Axis of FO (mm) Shortest Axis of FO (mm) Right Side Mean +- SD Left Side Mean +- SD Right Side Mean +- SD Left Side Mean +- SD Berlis et al., 1992 (Germany) 120 7.41 +- 1.31 3.91 +- 0.77 Ray et al., 2005 (Nepal) 70 7.46 +- 1.41 7.01 +- 1.41 3.21 +- 1.02 3.29 +- 0.85 Osunwoke et al., 2010 (Nigeria) 174 7.01 +- 0.1 6.98 +- 0.09 3.37 +- 0.07 3.33 +- 0.07 Somesh et al., 2011 (India) 164 7.64 +- 1.19 7.56 +- 1.12 5.13 +- 0.83 5.24 +- 0.95 Desai et al., 2012 (India) 250 8.14 +- 1.42 7.98 +- 1.89 5.26 +- 0.93 5.88 +- 1.01 Patil et al., 2013 (India) 104 7.00 +- 2.17 6.80 +- 1.40 5.00 +- 0.42 4.70 +- 0.91 Gupta and Rai. 2013 (India) 70 7.23 +- 1.14 6.49 +- 1.31 3.57 +- 0.70 3.50 +- 0.75 Unver Dogan et al., 2014 (Turkey) 62 7.18 +- 1.78 7.29 +- 0.94 4.32 +- 1.41 4.06 +- 0.66 Murugan and Saheb. 2014 (India) 500 8.9 +- 1.7 8.5 +- 1.3 3.7 +- 1.0 3.9 +- 1.0 Srimani et al., 2014 (India) 80 7.75 +- 1.16 7.70 +- 1.14 3.41 +- 0.70 3.56 +- 0.89 Ashwini et al., 2017 (India) 110 6.59 +- 2.21 6.38 +- 2.52 4.83 +- 0.97 4.59 +- 0.97 Bokhari et al., 2017 (Pakistan) 110 7.04 +- 1.08 7.18 +- 1.14 5.15 +- 0.92 3.99 +- 0.86 Natsis et al., 2017 (Greece) 195 7.63 +- 1.17 7.48 +- 1.20 4.47 +- 1.00 4.59 +- 1.00 Poornima et al., 2017 (India) 200 6.5 +- 1.4 6.4 +- 1.5 3.54 +- 0.57 3.73 +- 0.83 Rao et al., 2017 (India) 100 7.24 +- 0.89 7.11 +- 1.00 3.75 +- 0.71 3.75 +- 0.67 Srikantaiah et al., 2017 (India) 80 7.45 +- 3.1 6.8 +- 1.5 6.0 +- 1.7 5.6 +- 1.4 Zdilla et al., 2017 (USA) 169 6.62 +- 1.12 5.99 +- 1.08 3.13 +- 0.66 3.02 +- 0.63 Sophia et al., 2018 (India) 222 7.57 +- 1.55 7.39 +- 1.53 4.3 +- 0.9 4.6 +- 1.1 Sankaran et al., 2018 (India) 128 7.45 +- 1.1 7.61 +- 1.15 3.99 +- 1.8 4.6 +- 1.4 Prakash et al., 2019 (India) 124 7.74 +- 1.94 7.60 +- 1.25 5.18 +- 0.98 5.4 +- 0.85 Das et al., 2019 (India) 100 7.11 +- 1.69 6.53 +- 1.33 3.15 +- 0.69 3.20 +- 0.68 Kirwale and Sukre, 2020 (India) 224 7.52 +- 1.15 7.29 +- 1.15 4.18 +- 0.78 4.28 +- 0.81 Akcay et al., 2021 (Turkey) 80 7.09 +- 1.07 7.06 +- 1.01 4.16 +- 0.79 4.15 +- 0.5 Jyothi Lakshmi and Asharani, 2021 (India) 110 8.4 +- 1.6 8.5 +- 1.3 4.5 +- 0.8 4.1 +- 0.6 Kastamoni et al., 2021 (Turkey) 316 6.05 +- 1.01 5.86 +- 0.92 3.35 +- 0.83 3.37 +- 0.75 Acikgoz et al., 2022 (Turkey) 70 6.29 +- 0.15 6.00 +- 0.16 2.94 +- 0.10 2.83 +- 0.09 Hereus et al., 2022 (Belgium) 118 7.41 +- 1.30 7.57 +- 1.07 4.63 +- 0.86 4.33 +- 0.99 Kaur et al., 2022 (India) 200 8.16 +- 1.56 7.68 +- 1.25 4.97 +- 1.16 4.74 +- 1.21 Present study. 2023 (Slovenia) 267 7.13 +- 1.34 7.20 +- 1.29 3.71 +- 0.81 3.88 +- 0.84 FO--foramen ovale. SD--standard deviation. This study noted significant variability in the shape of the FO; however, no statistically significant differences were observed between the left and right sides. The most commonly observed shape was oval, followed by almond, irregular, D-shaped, round, pear, kidney-shaped (also described as crescent or semilunar ), elongated, triangular, and slit-like . Previous studies also reported substantial variability in the distribution of different FO shapes, with no significant differences noted between sides (as presented in Table 4). Variations in the shapes of FO should be considered a potential contributing factor to the failure of transoval access. An altered FO shape may indicate nasopharyngeal carcinoma, which tends to invade the intracranial space through the foramen . The variability in size and shape of FO across different world regions has been explained by population variation, as well as embryologically since the sphenoid bone develops from both intramembranous and endochondral ossification . During fetal development, the mandibular nerve migrates to its final position within the FO and is surrounded by a membranous bone. The first center of ossification in this region appears during the eighth week of fetal development, and the earliest formation of a fully formed ring-shaped FO is observed during the seventh month of fetal life. Overossification during the developmental process of the sphenoid bone comprising the FO may, however, result in morphologic abnormalities, such as spines, tubercles, bony bars, plates, or foramina, which may compress the mandibular nerve, causing trigeminal neuralgia. In addition, they may seriously hinder diagnostic and therapeutic procedures through the FO . The present study observed marginal bony outgrowths of FO in 45 out of 267 (16.6%) analyzed skull sides. Similar findings were reported by Das et al. , Berlis et al. , and Gupta et al. . The incidence of marginal projections reported by other authors varied from roughly 7% to as much as 24% . Kastamoni et al. reported only 2 cases (1.1%) of bony protrusion into the FO . We observed 24 spines (9.0%), 13 bony plates (4.9%), and 8 tubercles (3.0%) in 267 skull sides. Additional 12 (4.5%) foramina exhibited irregular marginal morphology due to small outgrowths that did not conform to previously reported classifications. Marginal irregularities were determined to be non-post-mortem, as the edges were smooth. These findings are consistent with those reported in previous studies . In the present study, one duplication of the FO was observed . The unusual position or absence of a typical FO may manipulate the anatomical organization of neurovascular structures passing through the foramen. This may result in a lateral disposition of the mandibular nerve and entrapment of its branches between the bone and the neighboring muscles, causing trigeminal neuralgia . The presence of a pterygospinous bar may reduce the space between the lateral pterygoid plate and the spine of the sphenoid bone and consequently preclude the cannulation of the FO . When encountering difficulties accessing the FO with the needle despite attempting various angles, it is important for the surgeon to consider the potential presence of a pterygospinous bar. In such cases, intraoperative CT-guided neuronavigation can be utilized to successfully navigate the needle and increase the safety of the surgical procedure . In the present study, 15 complete (5.6%) and 22 incomplete (8.2%) pterygospinous bars were observed. Cannulation of the FO is utilized in the percutaneous treatment of trigeminal neuralgia and biopsy of lesions in the cavernous sinus or deep lesions that otherwise require open surgical biopsy or craniotomy, namely, squamous cell carcinoma, meningioma, Meckel cave lesions , and electroencephalographic analysis of temporal seizures in patients undergoing selective amygdalohippocampectomy . The shape and dimensions of the foramen may therefore be important in determining the appropriate caliber of a stylet that could be transmitted through the FO . The FO serves as a landmark for percutaneous trigeminal rhizotomy in patients with trigeminal neuralgia (TN). The FO puncture is followed by destruction of TN fibers using radiofrequency thermocoagulation, balloon compression, or glycerol rhizotomy . During cannulation, a misplaced needle in the foramen of Vesalius (FV) can cause severe complications, such as intracranial bleeding , as the distance between these two foramina is relatively short, between 0.93 and 5.45 mm . In the present study, the mean distance between the FO and the FV was 4.26 mm on the right side and 2.52 mm on the left side. The minimal distance was 1.16 mm on the right and 0.83 mm on the left side. The failure of percutaneous approaches may also be attributed to the misidentification of a large FV as the FO on imaging . In the present study, the maximum diameter of the FV was 3.25 mm on the right side and 3.05 mm on the left side. The middle meningeal vessels and the meningeal branch of the mandibular nerve may also sustain injuries during rhizotomy since the foramen spinosum is located very close to the FO . In the present study, the mean distance between the FO and the FS was 3.04 +- 1.31 mm on the right side and 3.01 +- 1.11 mm on the left side. The shortest distance between the foramina was 0.25 mm on the right side and 0.72 mm on the left side. The analyzed FO were additionally classified as either foramen-like or canal-like, as previously proposed by Elnashar et al. to highlight the correlation between the anatomical shapes of FO and the surgical view. A canal-like FO may hinder access to the middle cranial fossa . Our study has a few limitations. First, we could not identify the sex and age of individuals from whom the skulls were obtained and consequently could not characterize the anthropometric evaluations based on these parameters. Second, the exact cause of variations observed in the present study is difficult to determine, although, in general, we consider that these may be due to genetic, nutritional, or environmental factors. However, because we had no autopsy data, it was impossible to exclude any potential underlying disease that would cause pathologic changes in the size, shape, or spatial disposition of the skull foramina. Finally, despite the meticulous precautions taken in the study protocols to minimize individual errors and subjectivity, we cannot absolutely exclude potential bias in evaluations. 5. Conclusions A thorough understanding of the anatomy of the FO and its variations is essential in a number of diagnostic and therapeutic neurosurgical and anesthetic procedures. In this study, we report morphologic and morphometric characteristics of the FO in skulls from the Slovenian population and highlight the clinical relevance of the anatomical features. Our findings indicate a substantial degree of interindividual variability in the shape, size, and aberrant anatomical relationships of the FO, which has the potential to impact the feasibility and safety of relevant procedures. Acknowledgments We are grateful to Friderik Stendler, Ivan Blazinovic, Stanko Kristl, Sebastijan Krajnc, Marko Slak, and Nejc Vencelberger for the technical support and Chiedozie K. Ugwoke for the manuscript proofreading. Author Contributions Conceptualization, N.U. and E.C.; formal analysis, Z.S. and N.U.; funding acquisition, E.C.; investigation, Z.S.; methodology, N.U. and E.C.; resources, A.A. and E.C.; supervision, A.A. and E.C.; writing--original draft, Z.S.; writing--review and editing, N.U., A.A. and E.C. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was approved by the National Medical Ethics Committee of the Republic of Slovenia (Permit No. 0120-459/2018/3, approved on 24 October 2018). Informed Consent Statement Informed consent was obtained from all donors. Data Availability Statement Data from this study are available upon reasonable request. Conflicts of Interest The authors declare no potential conflicts of interest regarding the conduct and publication of this study. Abbreviations FO: foramen ovale. FS: foramen spinosum. FV: foramen of Vesalius. FL: foramen lacerum. R: right. L: left. SD: standard deviation. Figure 1 Shapes of the foramen ovale. Images were captured from the external aspect of the cranial base. The upper part of the image corresponds to the anterior, the right part to the medial, the left part to lateral, and the bottom part to the posterior aspect of the cranial base. Figure 2 Foramen ovale (FO) with aberrant anatomical configurations. * Images were captured from lateral to medial direction on the external aspect of the cranial base. Images (B,C,E,G,H,I) were captured from the internal aspect of the cranial base. Images (A,D,F,J,K,L) were captured from the external aspect of the cranial base. FV--foramen of Vesalius. FL--foramen lacerum. diagnostics-13-00962-t001_Table 1 Table 1 Morphometric data on the foramen ovale. Parameter Mean +- SD (mm) Range (mm) Right Side Left Side Right Side Left Side n = 138 n = 128 n = 138 n = 128 Length of FO 7.13 +- 1.34 7.20 +- 1.29 4.19-10.55 4.72-11.81 Width of FO 3.71 +- 0.81 3.88 +- 0.84 1.30-7.22 2.33-6.43 Distance between FO and FS 3.04 +- 1.31 3.01 +- 1.11 0.25-7.72 0.72-5.98 Distance between FO and FV 4.26 +- 2.85 2.52 +- 1.34 1.16-9.44 0.83-5.33 FO--foramen ovale. FS--foramen spinosum. FV--foramen of Vesalius. SD--standard deviation. diagnostics-13-00962-t002_Table 2 Table 2 Distribution of foramen ovale shapes. Shape of FO Oval (%) Almond (%) D-Shaped (%) Round (%) Pear (%) Kidney (%) Elongated (%) Triangular (%) Slit (%) Irregular (%) Right side (n = 137) 38.7 27.7 4.4 2.2 2.9 1.5 1.5 1.5 0.7 19.0 Left side (n = 130) 35.4 28.5 4.6 3.8 0.8 1.5 1.5 0 0.8 23.1 Overall proportion (n = 267) 37.1 28.1 4.5 3.0 1.9 1.5 1.5 0.7 0.7 21.0 FO--foramen ovale. diagnostics-13-00962-t004_Table 4 Table 4 Comparison of FO shapes between the present and previous studies. Authors. Year (Country) Number of Skull Sides Oval (%) Almond (%) Irregular (%) D-Shaped (%) Round (%) Pear (%) Kidney (%) Elongated (%) Triangular (%) Slit-Like (%) R L R L R L R L R L R L R L R L R L R L Ray et al., 2005 (Nepal) 70 62.8 60.0 31.4 37.1 / / 2.8 2.8 / / / / 1.14 Somesh et al., 2011 (India) 164 58.53 54.87 29.26 28.04 2.43 4.87 / 9.75 12.19 / / / / / Daimi et al., 2011 (India) 180 29.87 / / 46.16 12.52 / / 10.41 / 1.04 Desai et al., 2012 (India) 250 62.8 23.2 / / 11.81 / / / / / Wadhwa et al., 2012 (India) 60 63.33 76.67 20.00 10.00 / / 10.00 10.00 / / / / 6.67 3.33 Gupta and Rai, 2013 (India) 70 57.14 51.43 40.00 31.43 / / 2.86 14.29 / / / / 0.00 2.86 Murugan and Saheb, 2014 (India) 500 69 29 0 / 2 / / / / / Patel and Mehta, 2014 (India) 200 64 55 12 12 / / 23 32 / / / / 1 1 Srimani et al., 2014 (India) 80 67.5 60 22.5 20 5 7.5 / 2.5 5 / 2.5 2.5 / / / Ashwini et al., 2017 (India) 110 69.09 63.63 9.09 16.36 14.50 18.18 / 7.27 1.81 / / / / / Bokhari et al., 2017 (Pakistan) 110 72.7 74.5 5.4 3.6 0 2.8 / 16.3 12.7 / / / 3.6 5.4 1.8 0 Sophia et al., 2018 (India) 222 68.46 3.15 15.31 8.55 / / / / 0.9 Natsis et al., 2018 (Greece) 195 49.6 62.6 23.5 14.8 19.1 13.9 / 7.8 8.7 / / / / / Das et al., 2019 (India) 100 32 38 10 8 / / 4 4 / / / 2 2 / Prakash et al., 2019 (India) 124 64.5 56.4 25.8 30.6 1.62 4.8 / 8.0 8.0 / / / / / Akcay et al., 2021 (Turkey) 80 70 70 17.5 20 / / 5 5 / / / / 7.5 5 Jyothi Lakshmi et al., 2021 (India) 110 67.3 70.9 10.9 14.5 / / 21.8 14.5 / / / / / Kastamoni et al., 2021 (Turkey) 316 81.0 14.9 / / 7.0 / 1.9 / / / Raguz et al., 2021 (Croatia) 78 41.0 71.8 7.7 7.7 / / 48.7 17.9 / / 2.6 2.6 / / Acikgoz et al., 2022 (Turkey) 70 34.29 34.29 / 10 12.85 / / / / 8.57 Kaur et al., 2022 (India) 200 68 72 20 18 / 6 6 4 2 0 1 / / 1 0 1 1 Santhosh et al., 2022 (India) 102 43.1 52.9 19.6 19.6 0 3.9 11.8 9.8 7.8 2 / / 9.8 7.8 / 7.8 3.9 Present study. 2023 (Slovenia) 267 38.7 35.4 27.7 28.5 19.0 23.1 4.4 4.6 2.2 3.8 2.9 0.8 1.5 1.5 1.5 1.5 1.5 0 0.7 0.8 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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PMC10000549 | Foods Foods foods Foods 2304-8158 MDPI 10.3390/foods12051052 foods-12-01052 Review Polyphenol-Dietary Fiber Conjugates from Fruits and Vegetables: Nature and Biological Fate in a Food and Nutrition Perspective Fernandes Ana * Mateus Nuno de Freitas Victor Benito Jose M. Academic Editor Laboratorio Associado para a Quimica Verde (LAQV-REQUIMTE), Departamento de Quimica e Bioquimica, Faculdade de Ciencias, Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal * Correspondence: [email protected] 01 3 2023 3 2023 12 5 105201 2 2023 16 2 2023 23 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). In the past few years, numerous studies have investigated the correlation between polyphenol intake and the prevention of several chronic diseases. Research regarding the global biological fate and bioactivity has been directed to extractable polyphenols that can be found in aqueous-organic extracts, obtained from plant-derived foods. Nevertheless, significant amounts of non-extractable polyphenols, closely associated with the plant cell wall matrix (namely with dietary fibers), are also delivered during digestion, although they are ignored in biological, nutritional, and epidemiological studies. These conjugates have gained the spotlight because they may exert their bioactivities for much longer than extractable polyphenols. Additionally, from a technological food perspective, polyphenols combined with dietary fibers have become increasingly interesting as they could be useful for the food industry to enhance technological functionalities. Non-extractable polyphenols include low molecular weight compounds such as phenolic acids and high molecular weight polymeric compounds such as proanthocyanidins and hydrolysable tannins. Studies concerning these conjugates are scarce, and usually refer to the compositional analysis of individual components rather than to the whole fraction. In this context, the knowledge and exploitation of non-extractable polyphenol-dietary fiber conjugates will be the focus of this review, aiming to access their potential nutritional and biological effect, together with their functional properties. bioactivity dietary fibers extractable polyphenols functional foods non-extractable polyphenols polysaccharides AgriFood XXI I&DT projectNORTE-01-0145-FEDER-000041 European Regional Development Fund (ERDF)NORTE 20202014/2020 FCT/MCTESCEECIND/00029/2018/CP1545/CT0010 research unit LAQV-REQUIMTEUIDB/50006/2020 UIDP/50006/2020 national fundsPartnership Agreement PT2020 FEDERPartnership Agreement PT2020 This research was financially supported by the AgriFood XXI I&DT project (NORTE-01-0145-FEDER-000041), project NORTE-01-0145-FEDER-000052, co-financed by the European Regional Development Fund (ERDF), through the NORTE 2020 (Programa Operacional Regional do Norte 2014/2020), and by FCT/MCTES through research contract (CEECIND/00029/2018/CP1545/CT0010) and research unit LAQV-REQUIMTE (UIDB/50006/2020 and UIDP/50006/2020), by national funds and co-financed by FEDER, under the Partnership Agreement PT2020. pmc1. Introduction In recent years, epidemiological studies and related meta-analysis established an association between the long-term consumption of fruit and vegetable-rich diets and the health benefits towards a vast array of human diseases (e.g., cardiovascular diseases, cancer, chronic inflammation, degenerative diseases, or metabolic disorders such as type II diabetes) . The health benefits arise mainly from the non-nutritive bioactives present in fruit and vegetable foodstuffs, commonly named phytochemicals. Among these, polyphenols have stood out as nutraceuticals and functional ingredients . In this sense, the comprehensive knowledge of the total content of polyphenols in foods and diets is a critical step for biological, epidemiological, and clinical studies, addressing their potential health effects . Polyphenol absorption on the food matrix has been increasingly understood over the years. The concept of "food matrix" points towards the fact that bioactives are part of a larger complex set of cellular origin (in fruits and vegetables) or even structures produced during food processing, where they may interact at different length scales . Due to these interactions, an appreciable amount of non-extractable polyphenols can still remain in the solid residues, absorbed to dietary fibers . Although non-extractable polyphenols are an important fraction in plant-based foods, they are usually neglected in bioavailability and metabolism studies, as well as in clinical trials and nutritional studies. Additionally, the therapeutic use of non-extractable polyphenol-dietary fiber conjugates through diet is missing, particularly related to the topics of bioaccessibility, pharmacokinetics, and bioavailability of polyphenols, which could influence the real use of these bioactives by the human organism. While extractable polyphenols are dissolved in the stomach and small intestine where they can be partially absorbed, non-extractable polyphenols cannot be absorbed at the small intestine . They reach the lower gastrointestinal tract almost intact in association with the vegetable cell wall. There, they exert systematic bioactive effects before or after being catabolized by colonic microbiota, yielding different metabolites that may counteract the effects of dietary pro-oxidants, and promoting colonic homeostasis . These compounds can also modulate the gut microbiota, resulting in a healthier profile that could be a potential tool to counteract several chronic diseases related to intestinal dysbiosis such as diabetes, obesity, and inflammatory bowel diseases . In this context, research priority should be directed towards the non-extractable fraction in plant-derived foods as well as in agri-food wastes and by-products, promoting their integral valorization and reincorporation to the food supply chain, as an innovative material that combines the properties of both polyphenols and dietary fibers. This review summarizes the relevance of polyphenol-dietary fiber conjugates in a food technology and health perspective, as many of the pathways sustaining the potential of these conjugates remain largely unexplored, including, for instance, their bioavailability, metabolism in the human digestive track, or microbiota modulatory potential. This review will lay the foundations for future studies aiming to unravel the applicability of non-extractable polyphenols in functional foods development and in nutraceutical fields as dietary supplements. 2. Polyphenols Polyphenols are secondary plant metabolites with fundamental roles in plant physiology and morphology . They can be found in fruits, vegetables, and cereals, thus representing an essential part of the human daily diet. In plant-based foodstuff, polyphenols can be associated with major sensorial properties, such as color, flavor, and taste (e.g., sweet and bitter taste), and to astringency perception . More notably, polyphenols have been in the spotlight of recent research exploiting their potential as functional ingredients in diverse food systems due to their therapeutic and health promoting properties. The general structure of polyphenols includes two aromatic nuclei with one or more hydroxyl substituent. They are commonly divided into two main classes, the flavonoids, characterized by a C6-C3-C6 flavanic core, and the nonflavonoids with a C1-C6, C3-C6 or a C6-C2-C6 core. Flavonoids account for nearly two-thirds of dietary polyphenols and, depending on the type of heterocycle present and its substitution pattern, they may be subdivided into anthocyanins, flavonols, flavan-3-ols, flavones, flavanones, isoflavones, and chalcones . Phenolic acids (hydroxycinnamic and hydroxybenzoic acids) and stilbenes are amongst the most common dietary non-flavonoids . Moreover, polyphenols are also present in the polymeric form in plants. Lignins are polymers of monolignols, such as p-coumaric and sinapic acid, while tannins may exist as hydrolysable and condensed tannins (or proanthocyanidins). Hydrolysable and condensed tannins are made of saccharide esters derived from gallic/ellagic acids or flavan-3-ols units, respectively , and they are particularly important as they can attain high molecular weights and complex polymeric structures . Although polyphenols can be found practically in all plant-derived foodstuffs, their distribution and quantities are extremely variable , ranging from more than 15 g per 100 g in cloves to 7.8 mg per 100 mL in rose wine . Other external factors can also regulate the polyphenolic content in plants and derived foodstuff, such as genetic, environmental (e.g., type of soil, sun exposure, stage of ripeness), and technological factors (e.g., industrial processing, storage, or culinary preparation) . Furthermore, their total content in fruits and vegetables are, most of the time, underestimated as they only include extractable polyphenols that can be easily recovered with aqueous-organic solvents. Compounds entrapped within the plant cell walls (non-extractable polyphenols or macromolecular antioxidants) are usually overlooked and not even considered in nutritional, clinical, and epidemiological studies, resulting in great dissimilarities between the estimated and ingested content . 3. Extractable and Non-Extractable Polyphenols Polyphenols can be found either in extractable (soluble-free) and non-extractable form (insoluble or bound), distributed in various tissues/organs of the plant body . The concept of extractable vs. non-extractable polyphenols is related to their extractability in aqueous and organic solvents, although non-extractable polyphenols can also be released and extracted after proper chemical or enzymatic hydrolysis . Most of the extractable polyphenols are located in the vacuoles of plant cells and do not interact physically or chemically with other plant macromolecules, being easily extracted after plant tissue disruption with polar aqueous/organic solvents . Flavonoids, phenolic acids, stilbenes, and lignans are some of the phenolics that can be found in extractable form. Non-extractable polyphenols, including high-molecular weight proanthocyanins, hydrolysable tannins, flavonoids, and low-molecular weight phenolics, can be virtually found in all types of plant-derived foods . Non-extractable polyphenols can be found cross-linked to cell wall structural components such as cellulose, pectin, hemicellulose (e.g., arabinoxylans), lignin, and structural proteins through covalent bonds (ester bonds with hydroxyl groups of cell wall substances via carboxylic groups, ether linkages with the aromatic hydroxyl groups, or by C-C bonds) . These phytochemicals play a major role in the connection of cell wall substances, enhancing cell wall mechanical strength and structural rigidity, being also involved in the protection against UV radiation and harmful organisms (pathogens, insects, and herbivores) , with antibacterial, antifungal, and antioxidant functions. Phenolic acids are the most common bound phenolic compounds in natural sources. Hydroxycinnamic acids (e.g., ferulic acid) are covalently linked to arabinogalactans in sugar beet or spinach , as well as to arabinoxylans in wheat , bamboo , and maize . Additionally, polysaccharides can form covalent bonds with polyphenols during food processing . For instance, heat treatment and acid conditions may cause polyphenol depolymerization and the formation of carbocations, being able to randomly react with cell wall nucleophilic compounds through covalent bonds . In addition, oxidation of polyphenols in damaged tissues may occur . However, it should be emphasized that the concept of non-extractable polyphenols is a broader concept than the term "bound phenolics", which is usually associated with phenolic acids covalently linked to cell walls . The type of chemical interactions between non-extractable polyphenols and dietary fibers also includes the formation of ordered junctions stabilized by arrays of non-covalent interactions (e.g., hydrogen bonding, ionic bond, electrostatic interaction, and hydrophobic effect), during or after physical damage and the senescence of plants . Furthermore, polyphenols may be physically entrapped in various cellular structures or entrapped by a surface adsorption phenomenon or by encapsulation in hydrophobic pockets within the biopolymer network and porous structures (particularly for dietary fibers) embedded into intact cellular structures . This mechanism is particularly notorious with pectic polysaccharides due to their higher structural flexibility . As these bonds are individually weak, these interactions are stable only above a minimum critical length, and their formation and disruption often occur as sharp and cooperative processes . 3.1. Types and Content of Non-Extractable Polyphenols in Foods Non-extractable polyphenols include several classes of polyphenols, either polymeric or single, linked to plant macromolecules, and can be found in fruits, vegetables, legumes, cereal grains, and seeds. In fruits and vegetables, non-extractable polyphenols encompass an average of 24% of the total amount . For instance, banana (Musa acuminate), orange (citrus sinensis), and apple (Malus domestica) have nearly 33, 24, and 7% of non-extractable polyphenols, respectively . Carrots (Daucus carota) and onions (Allium cepa) have about 38 and 10% of non-extractable polyphenols, respectively . On the other hand, cereals, such as brown rice, present 80-90% of total polyphenols in the bound form . Plant-based food by-products, such as peals, pomace, and seeds, also possess high amounts of non-extractable polyphenols. Cranberry pomace (Vaccinium macrocarpon) has approximately 76% of non-extractable polyphenols . Phenolic acids (mostly ferulic acid derivatives) are the most abundant non-extractable polyphenols, being covalently bound (by ester, ether, or C-C bonds) to the cell wall matrix . Other phenolic acids may be found to be associated with cell wall polysaccharides such as p-hydroxyphenyl, syringyl, or p-coumaroyl moieties. They are mostly found in cereals but are also present in other plant-based foodstuffs such as spinach and sugar beet (ferulic and p-coumaric acids), orange flavedo (ferulic, sinapic, and p-coumaric acids), and lentils (p-coumaric acid) . Proanthocyanidins with a higher degree of polymerization can be found in the non-extractable fractions, including both proanthocyanidins bound to cell wall polysaccharides and proteins. Interactions between proanthocyanidins and cell walls occur mostly through non-covalent binding, including hydrogen bonds, hydrophobic effect, or van der Waals forces. It is becoming clear that the adsorption mechanism between proanthocyanidins and cell wall constituents is affected by a multitude of factors, including environmental parameters (e.g., pH, temperature, ionic strength) and the physicochemical properties of the interacting partners: morphology (surface area, porosity, pore shape), chemical composition (sugar ratio, solubility, branching complexity), molecular weight, and polyphenol molecular architecture (polymerization degree, contributing to the increase of hydroxyl and aryl groups available to form hydrogen bonds and to establish hydrophobic interactions, respectively, degree of methylation and acetylation, degree of galloylation/hydroxylation, conformation) . Furthermore, higher proportions of pectic polysaccharides impart higher flexibility to the structure, thus allowing for a higher contact surface area, while higher proportions of lignin and cellulose, with higher structural rigidity, allow for fewer adsorption interactions . Most hydrolysable tannins have been detected in water-organic extracts, although significant amounts can also be found in the resulting solid residues . The way by which hydrolysable tannins are associated with the food matrix has not yet been established. In addition, no information about individual tannins was obtained, as the current method for their determination causes tannin depolymerization . Flavonols, including rutin, isoquercitrin, quercitrin, and quercetin were also found in the non-extractable fraction of tropical or subtropical fruits or leaves, tomato peel (also flavanones in this source), wine, beer, Hibiscus sabdariffa flowers, and tropical and subtropical fruits or leaves . However, the exact nature of the interactions between flavonoids and the solid cell wall matrix has not been properly addressed. Regarding anthocyanins, studies are somehow controversial as the data reported for the non-extractable anthocyanins determined after acid hydrolysis may correspond to the hydrolysis of proanthocyanidins . Thus, the presence of a fraction of non-extractable anthocyanidins remains to be properly established. Additionally, there are several limitations in the methodology for the extraction of these pigments from the food matrix. For instance, the use of glycosidases or acid hydrolysis to release anthocyanins may cause the formation of less stable aglycones . In a previous work, an anthocyanidin molecule (malvidin aglycone) associated with macromolecular material has been reported , suggesting, as reported for melanoidins, the covalent linkage of anthocyanins to the polymeric material , specially to pectic polysaccharides. In this sense, non-extractable polyphenols represent a very important fraction to be considered in a nutritional and health perspective. They may be slowly and continuously released in the human gastrointestinal tract and during colonic fermentation, which can improve bioaccessibility and potential bioavailability and exert high bioactivity on tissues and cells for a longer time. 3.2. Release of Non-Extractable Polyphenols from Dietary Fibers Although non-extractable polyphenols can be regarded as an important fraction of phenolic compounds in plant-based foods , the challenge is that their chemical composition analysis requires several isolation steps, as they cannot be detected with the usual analytical procedures for either fibers or extractable polyphenols (e.g., HPLC analysis). However, the extraction methods are often not systematically optimized and greatly dependent on the chemical and physical nature of the food plants , giving rise to different recovery yields. Furthermore, the accuracy of the results may be questionable, as some of the methodologies employed to release and assess non-extractable polyphenols are often destructive and inefficient. Depending on the chosen methodology, on the extraction methodology order applied, or on the plant matrix, degradation or incomplete release may occur, resulting in underestimated values . Extraction methods to recover non-extractable polyphenols from the cell matrix for further analyzes in the corresponding hydrolysates include chemical (acid or alkali) , physical (e.g., microwave-, ultrasound-assisted hydrolysis, pressurized solvent/liquid extractions, far-infrared (FIR) radiation-assisted, or pulsed electric field-assisted) , or enzymatic hydrolysis, with carbohydrate-hydrolyzing enzymes such as cellulases, hemicellulases, pectinases, proteases, glucanases, or bacterial enzymes . While alkaline hydrolysis is more effective in promoting the disruption of both ester and ether bonds, linking polyphenols to cell wall constituents , acid hydrolysis mainly promotes the disruption of glycosidic bonds, generally leaving ester bonds intact. Compared to acid or alkaline hydrolysis, enzymatic hydrolysis allows a lower loss of phenolic compounds as a moderate pH is used during the extraction procedure. Additionally, carbohydrate-hydrolyzing enzymes may also induce the production of aglycone moieties due to the presence of b-glucosidase, b-galactosidase, or a-L-arabinoside activities, which can be detrimental to the stability of several flavonoids, such as anthocyanins . In addition to the carbohydrases, esterases have also been shown to be efficient in the release of non-extractable polyphenols . Given the specificity of each hydrolytic system, a single methodology is probably inadequate to perform the full assessment of non-extractable polyphenols. Thus, a combination of different hydrolytic systems may provide more complete information regarding the non-extractable fraction. Food processes such as fermentation an germination, as well as thermomechanical processes such as extrusion, have also been shown to be effective non-thermal food processing methods for the release of non-extractable phenolics from the cell wall matrix . Abdel-Aty, 2019 reported the improved phenolic content, antioxidant and antimicrobial activities of garden cress seeds, using solid-state fermentation. However, other works have also reported the decrease in the levels of phenolic compounds, which can be attributed to the degradation and hydrolysis of phenolic compounds . Several works have shown the increased content of non-extractable phenolics due to germination . This bioprocess induces the activation of cell metabolism, which results in the release of hydrolytic enzymes, thus affecting phenolic compound content . Other food processes such as roasting, extrusion, or boiling have shown potential to release phenolic compounds associated with cell walls . These thermal processes involve the use of high temperatures and/or pressure, leading to the disruption of the cell wall matrix of foods through the depolymerization of pectins and hemicelluloses, thus enhancing the release of bound phenolics. On the other hand, the high energy extrusion conditions degrade bioactive phenolic compounds, with a consequent reduction of the antioxidant capacity . Hydrothermal treatments such as boiling have also been shown to cause chemical reactions between phenolic compounds and other compounds, such as proteins, forming irreversible covalent bonds that are not hydrolyzed during the extraction process . 4. Biological Activity of Non-Extractable Polyphenol-Dietary Fibers Over the past few years, several biological activities have been attributed to non-extractable polyphenols (either isolated or rich matrices), combining in vitro models, cell cultures, animal models, or human trials . However, it is important to note that non-extractable polyphenols have been previously subjected to a hydrolytic process to release polyphenolic compounds from the carbohydrate or protein moiety, following extraction and analysis of specific phenolic compounds in the corresponding hydrolysates and the assessment of their bioactivities similarly to extractable polyphenols . For instance, antioxidant capacity, antiproliferative and apoptotic effect on cancer cells, inhibition of carbohydrate and lipid metabolism enzymes, or anti-inflammatory activity are some of the bioactivities that have been described . Additionally, the released single phenolic acids and flavonoids have been extensively examined for their biological activities against diabetes, cardiovascular and neurodegenerative disease, and cancers in cell lines and in vivo models . After ingestion, a significant part of the non-extractable polyphenols reaches the colon, playing a major role in the reduction of local oxidative stress and boosting anti-inflammatory mechanisms and immunity through a chemical action in the gut environment . On the other hand, besides acting as carriers for polyphenols, thus affecting their bioaccessibility and potential bioavailability , cell wall polysaccharides can also influence host wellbeing and health through a variety of mechanisms, depending on their dietary source, physicochemical structure, fermentability, and physiological properties in the gut , modulating intestinal microflora, improving gastrointestinal health, and regulating brain signals, affecting the gut-brain axis. There is also evidence suggesting that polyphenol-dietary fiber interaction can modulate the fermentation of polyphenols in the gut . Dietary fibers are also associated with favorable body weight and overall metabolic health, being also associated with a reduced risk for the development of cardiovascular disease , some forms of cancer , and depression . However, the specific biological activity of non-extractable polyphenol-dietary fiber conjugates is not well established due to the insoluble nature of these compounds. For instance, the measurement of the antioxidant activity has been limited most of the time to soluble materials, with the extraction procedure being considered a critical step . However, many of the insoluble components cannot be solubilized without altering their molecular nature by chemical or enzymatic treatment. Thus, direct methodologies to assess the antioxidant activity of insoluble material have been developed . The QUENCHER methodology has been shown to accurately measure the antioxidant capacity of antioxidants (e.g., ABTS, DPPH, FRAP, ORAC, CUPRAC) bound to insoluble matrices , without extraction and hydrolysis processes, by a surface reaction phenomenon. The QUENCHER concept was also adapted to the methodologies that evaluate the scavenging capacity of superoxide, hydroxyl, and lipid peroxyl radicals . On the other hand, all antioxidant compounds are present in a dynamic system where radicals and antioxidant compounds react continuously with each other, with the coexistence of multiple antioxidants possibly resulting in additive, synergistic, or antagonistic interactions . Previous studies have shown that the antioxidant activity of non-extractable antioxidants bound to dietary fibers can be regenerated by extractable antioxidants in the liquid phase, as the extractable ones can provide electrons or hydrogen atoms to the formers, regenerating them . Consequently, non-extractable ingredients with an increased antioxidant capacity can be obtained, as during the digestion process, they can react with the free radicals and at the same time being regenerated by extractable compounds , a promising framework in the development of functional foods. Furthermore, non-extractable polyphenols and dietary fibers have shown to positively affect SCFA production, with rats fed with dietary fibers enriched with polyphenols extracts showing a higher SCFA production compared with only fibers . Mice supplemented with apple pomace flour showed a lower body weight gain and improved glucose tolerance . The daily intake of grape pomace consumed in bread, biscuits, or directly mixed with water improved blood pressure, glycaemia, postprandial insulin, and antioxidant defense . Finally, its consumption in burgers supplemented with wine pomace improved fasting glucose, insulin resistance, plasma antioxidant levels, and oxidative damage markers . The same pomace contributed to a decrease on inflammation markers . 5. Non-Extractable Polyphenol-Dietary Fiber Fate through the Human Gut Bioavailability of a compound can be defined as the fraction that can reach systematic circulation after administration, so that they can exert bioactivity . Thus, bioavailability represents one of the most relevant aspects for the potential therapeutic effects of the ingested compounds. With respect to in vivo potential, non-extractable polyphenols are essentially considered non-bioavailable as they can reach the colon still covalently linked or chemically adsorbed or entangled within the fiber matrix, with their absorption mechanisms in the upper part of the gastrointestinal tract greatly depending on their release from the food matrix. From a nutritional point of view, non-extractable polyphenols are a relevant group of compounds for two main reasons: (a) most of the non-extractable polyphenols are not affected by the acidic conditions at the gastric phase or by the enzymes of small intestine . Only a small percentage (about 5-10%), can be partially released from the food matrix, namely the water soluble non-extractable polyphenols, due to their poor structure. In this case, polyphenols may be absorbed through the small intestine mucosa by direct solubilization in the intestinal fluids in physiological conditions (37 degC, pH 1-7, mobility, transit time) and after ester bond cleavage, by the action of mucosa cell esterases . Glucuronidation, sulfation, or methylation may also occur at the level of intestinal mucosa ; (b) the remaining non-absorbed polyphenols, connected to cell wall macromolecules, can reach the lower gut intact, where they play a major role in the reduction of local oxidative stress and in modifying the microbiota composition, thus improving gut permeability and boosting the anti-inflammatory mechanisms and immunity . There, they undergo fermentation by the colonic microbiota, releasing absorbable metabolites or by the action of some intestinal enzymes able to break covalent bonds, such as esterases . Colonic microorganisms, including, for instance, Bifidobacterium spp., Clostridium spp., and Lactobacillus spp., secrete a variety of extracellular enzymes such as carbohydrolases, protease, and other types of enzymes, leading to the disruption of the cell wall matrix and hydrolysis of covalent bonds or release of entangled polyphenols, and producing metabolites. Additionally, colonic microbiota cleaves the glycosidic linkage and breaks down the flavonoid structure of the unabsorbed phenolics, releasing aglycones as well as converting them into small molecules . On the other hand, the action of the microbiome on macromolecules, mainly carbohydrate and protein, produces mainly short-chain fatty acids (SCFA) (acetic, propionic, butyric) and gases from carbohydrates, along with nitrogen compounds from proteins and low molecular weight phenolic compounds and some phenolic metabolites (hydroxyphenylacetic, hydroxyphenylvaleric, and hydroxyphenylpropionic acids or urolithin) from non-extractable and also from extractable phenolic compounds that were not absorbed in the small intestine and which have been implicated in the suppression of intestinal inflammation and improvement of the intestinal microenvironment . The released polyphenols (aglycones and small molecules) in the gut lumen render a myriad of health benefits that influence the fermentation environment of the colon by decreasing pH, enhancing the intestinal antioxidant status, which may protect against dietary prooxidants and free radical and prevent the growth of cancer-inducing microorganisms . Once free in the gut lumen, polyphenols and their metabolites can pass the colon mucosa and be absorbed into the bloodstream, through passive diffusion and/or active transport by transporters, such as glucose transporters, ATP-binding cassette transporters, and monocarboxylic acid transporters in the intestinal epithelium . Through the portal vein, polyphenols arrive in the liver where they are mainly metabolized as glucuronides metabolites and, to a minor extent, as sulfated and methylated compounds. These metabolites may return to the digestive tube through the bile, or pass into the bloodstream, reaching tissues and organs, allowing protection against chronic diseases . Colonic phenolic acids may also influence the regulation of the immune system response at the epithelial level or modulate colonic microbiome, through the activation of SCFA excretion, promoting gut health, thus presenting a prebiotic effect . On the other hand, SCFA have also been shown to affect and to enhance the uptake of phenolic metabolites . The metabolites produced by colonic fermentation from the free and non-extractable polyphenols during digestion were shown to be similar. However, the specific characteristics of non-extractable polyphenols, such as high molecular weight and/or association with other macromolecules present in the food matrix, cause two specific features in the colonic transformation. From the delay of polyphenol levels observed in the plasma after intake, comparing non-extractable-rich matrices and free phenolics-rich matrices, it could be concluded that the metabolites derived from non-extractable polyphenols circulate for longer periods in the human body than those produced from free phenolics, exerting their effects much longer than extractable polyphenols in a living organism . In fact, non-extractable polyphenols and other phenolic metabolites may persist in the human plasma for up to 3-4 days after ingestion, playing key bioactive roles, such as modulators of low-grade inflammation and cell-signaling pathway mediators . According to Vitaglione et al., 2008, the slow and continuous release of non-extractable polyphenols may favorably act in vivo, quenching the soluble radicals that are continuously formed in the intestinal tract, as opposed to the extractable polyphenols that are immediately absorbed and metabolized in the gastrointestinal tract , thus allowing a continuous protection. In this sense, dietary fibers may act as natural delivery carriers, improving not only polyphenol chemical stability and solubility but also modulating its bioavailability throughout the gastrointestinal tract . In sum, the presence of macromolecular components in non-extractable polyphenols might affect polyphenol bioaccessibility in the small intestine, by decreasing it. At the same time, they may potentially increase the polyphenol amount that reaches the lower parts of the digestive tract , being released and bio-transformed into catabolites. 6. Non-Extractable Polyphenol-Dietary Fibers: A Potential Functional Ingredient Single polyphenols and dietary fibers have been widely used as functional ingredients in foodstuffs due to their well-recognized physiological roles. For instance, dietary fibers have been associated with an increase of the volume of fecal bulk, decrease of the intestinal transit time, reduction of cholesterol and postprandial blood sugar levels, stimulation of intestinal microflora proliferation, such as Bifidobacterium (bacteria associated with colon, stomach, breast, and prostate cancer prevention ), and promote the formation of SCFA, reducing luminal pH, which helps to prevent colonization and infections from pathogenic bacteria . Moreover, some bioactive polysaccharides possess other health-promoting properties (e.g., antimicrobial, antitumoral, and immunostimulating effects) . These bioactivities are mainly associated with polysaccharide physicochemical and conformational properties . On the other hand, polyphenols are attracting more attention due to their antioxidant capacity and antimicrobial, anti-carcinogenic, and anti-inflammatory activity in the human body . They also exhibit an inhibition effect on digestive enzymes, such as lipase, amylase, and glucosidase . Polyphenols can also act as prebiotics due to their inhibitory effect against pathogens and stimulation effects on beneficial bacteria . From a technological perspective, dietary fibers may affect the technological properties of food related to texture, due to water and fat-holding ability, gelling and swelling capacity, emulsion stability, increased viscosity, and foam capacity and stability, as well as solvent retention capacities (e.g., lactic acid, sodium carbonate, sucrose) . The viscosity of dietary fibers is due to physical interaction between fiber particles, strongly associated with fiber microstructure . Additionally, they may be used as non-caloric bulking agents for partial replacement of flour, fat, or sugar. Polyphenols, on the other hand, have been used as natural dyes, preservatives in food formulations (antimicrobial, antioxidants, and antibacterial activity), favoring, thickening agents, and prebiotic ingredients . In this sense, non-extractable polyphenols associated with dietary fibers have assumed an increasingly significance, as they hold the promise to provide physiological and technological properties (e.g., texture, color, health benefits, or stability during shelf-life) of both substances in a single material . Hence, the search for innovative non-extractable polyphenol-dietary fiber materials to the food industry has been emerging, also representing an opportunity to apply sustainable circular economy models. However, it should also be taken into consideration that the supramolecular structure and physical properties of dietary fibers (e.g., rheology, encapsulation efficiency, water solubility, and structural stability) can be altered through polyphenol interaction . For instance, previous studies have shown that polyphenols may induce a viscosity decrease and the pseudoplastic (Newtonian) behavior of polysaccharide solutions through the formation of polysaccharide-polyphenol aggregates (e.g., b-glucan, galactomannan, guar, and xanthan gum) . Another study showed that phenolic acids and flavonoids can alter the gelatinization, retrogradation, and digestibility of starch. Procyanidins, on the other hand, can increase the crystallinity, bonding temperature, and maximum viscosity of starch . In a food concept, non-extractable polyphenol-dietary fibers can be defined as a dietary fiber concentrate with significant amounts of associated natural polyphenols . Furthermore, there are certain requirements that must be observed so that the material can be considered as a potential food ingredient, namely the dietary fiber content should be higher than 50% in a dry weight basis and the antioxidant capacity must be an intrinsic property of the material, deriving from the natural constituents and should not be related to added antioxidants or any other constituents released through chemical or enzymatic treatment of the original components. Regarding the antioxidant capacity, 1000 mg of antioxidant dietary fibers should inhibit lipid oxidation equivalent to at least 200 mg of vitamin E and present a free radical scavenging capacity equivalent to at least 50 mg of vitamin E . The fruit and vegetable industry generates high amounts of wastes and by-products that can be reused in different applications. Multifunctional polyphenol-dietary fiber ingredients, with higher health-promoting effects (source of bioactive compounds, such as vitamins, minerals, and polyphenolic compounds) and technological functionalities represents a suitable alternative to valorize these residues. For instance, olive pomace has been reported as an antioxidant, antimicrobial, and prebiotic ingredient, with potential beneficial effects on the gut microbiota and with functional properties (solubility and water and oil-holding capacity) . The most commonly prepared fruit and vegetable dietary fibers with associated polyphenols that could be employed as sources to develop functional ingredients are obtained from guava, acai and mango fruits, chokeberries, apples, cranberries, carrot peels, pineapple shells, cocoa, and cabbage leaves, or they are by-products of Vitis vinifera L. grapes (pomaces) or apple pomace (Table 1). Cereals, particularly bran and husk, are also a rich source, with a high proportion of non-extractable polyphenols associated with dietary fibers . Polyphenol-dietary fiber materials are available in various forms, such as granules, seeds, hulls, shells, or grains, as well as in the form of powdered ingredient . Typically, these preparations are subjected to a washing and stabilization step (normally by heat treatment) to inactivate microorganisms and enzymes . Decontamination with sodium hypochlorite solution, followed by rinsing with water, can be applied to guarantee food safety . Depending on the vegetable source, separation of liquid and solid fractions may be required, which allows a reduction of the drying time and the caramelization extent of the free sugars during drying . Additionally, this process allows one to obtain a solid residue with lower water content and to collect a liquid part rich in water soluble compounds, allowing a wider valorization of the raw material. Typically, these preparations have been prepared with low water activity, obtained after drying and grinding. These two parameters can affect the techno-functional properties of the powdered ingredient. While drying temperature can be managed to increase phenolic compounds and consequent health benefits of the by-products, grinding and the particle size affect the technological properties of the flours, particularly the hydration properties. At lower particle size, dietary fiber water holding capacity, water retention capacity, and swelling capacity increase. However, further decreases lead to a decrease on the hydration properties, possibly due to soluble and insoluble fiber content . In recent years, the presence of a specific type of naturally occurring water-soluble polyphenol-polysaccharide conjugates has been described in the flowering parts and leaves of many traditional medicinal plants and some food crops (e.g., grape pomace, lingonberry, or rice), with these conjugates being the focus of several studies. Despite their relatively lower purity and higher heterogeneity, some common and characteristic structural features (consisting of two parts, a polyphenolic and a polysaccharide moiety) and biological activities have been identified. Purification methods are similar to those applied for polysaccharides due to their macromolecular nature, including anion exchange chromatography and gel filtration chromatography. In general, polyphenol glycoconjugates exhibit several biological activities, including anticoagulant, antioxidant, radioprotective, anti-platelet, antitussive, and bronchodilatory activity . More notably, naturally occurring polyphenol-polysaccharide conjugates were also shown to have a bright prospect in the field of food and nutraceuticals, presenting an antiglycation and antihiperglycemic effect, digestive enzymes inhibitory effect, anti-obesity, and regulation of gut microbiota . Glucose transport in Caco-2 cells was also found to be significantly inhibited by water soluble polyphenol-polysaccharide treatments . Recovery of these conjugates through conventional solvent extraction techniques (hot water or alkaline extraction) require long extraction time, high energy consumption, and organic solvents, which may cause negative effects on human health upon ingestion due to their residue in the final product. Among modern extraction methods, subcritical water extraction (SWE), pressurized liquid extraction (PLE), ultrasound-assisted extraction (UAE), and microwave-assisted extraction (MAE) have shown the potential to replace conventional extraction techniques . Besides naturally occurring polyphenol-dietary fibers, synthesized conjugates may also play a fundamental role in the development of new functional ingredients, with improved physicochemical and bioactive properties, compared to the unmodified polyphenols and polysaccharides. Phenolic acids, including caffeic, gallic, ferulic, vanillic, and coumaric acids, have been covalently grafted onto chitosan , starch , curdlan , pectin , and gum arabic . Other flavonoids, such as catechin, rutin, quercetin, hesperidin, curcumin, naringenin, and proanthocyanindins, have also been successfully grafted onto polysaccharides . The grafting reactions can be achieved by carbodiimide-mediated coupling reaction, free-radical induced reaction, or enzyme-mediated polyphenols-polysaccharide conjugation reactions (e.g., laccase, tyrosinase, horseradish peroxidase, and choroperoxidase) . Wheat bran, a source of dietary fibers, was shown to reacted with polyphenols from different sources (green and black tea and white and red wine) under alkaline conditions with free amino groups available on the surface of wheat bran, followed by polymerization of the soluble antioxidants . Synthetic conjugates have also shown several bioactive properties, such as antioxidant, anticarcinogenic, anti-inflammatory, and antidiabetic activity, which could allow their application in the food industry, such as in food preservation and packaging or in active nanocarriers for delivery of active ingredients . Thus, understanding the synthetic strategy, purification methodology, and the knowledge of the functional and physiological properties of polyphenol-polysaccharide conjugates is fundamental for the development of innovative food ingredients. 7. Non-Extractable Polyphenol-Dietary Fibers: An Approach in Food Industry and Innovation Potential Non-extractable polyphenol-dietary fibers are promising ingredients to bring innovation and functionality to the food industry, affecting polyphenol bioavailability and promoting high bioactivity on tissues and cells, while potentiating the technological functionalities of both dietary fibers and polyphenols. In fact, non-extractable-dietary fiber conjugates can be seen as innovative delivery systems, acting as polyphenol carriers, and at the same time modulating gut microbiota . On the other hand, using food by-products and wastes to obtain new ingredients that can be re-introduced into the industrial chains can be considered as a solution to mitigate the economic, environmental, and social impact caused by food wastes, bringing innovation to the food sector . After the validation of the potential of non-extractable polyphenol-dietary fiber conjugates as functional ingredients, there are some aspects that must be globally considered in the next steps of the development of food products, particularly production processes (as it may impact the texturizing properties), raw-material availability, stability, and storage conditions, including shelf-life, microbiological safety regarding the presence of pesticides and other contaminants from agriculture, and physical hazards. Finally, it should be taken into consideration that the valorization of these bioactive compounds should occur at competitive prices, so that they can be used . Non-extractable polyphenol-dietary fibers from fruits and vegetables have been incorporated into food products, preferably into cereals, as this material presents a better nutritional profile due to the significant content of associated bioactive compounds, lower phytic acid content, and caloric value. Additionally, this material presents a balanced dietary fiber composition (higher fiber content, IDF:SDF ratio) and technological functionalities, namely as thickeners, gelling agents, fillers, and as water and oil holding retainers, as well as in the production of edible films . Literature has shown the application of this ingredient in different food products, enhancing the bioactive compound level (antioxidants and dietary fiber) in finished food products, and increasing their technological behavior . In bakery products, dried fruit and vegetable pomaces can be added to replace flour, sugar, or fat, thus reducing energy load, while enhancing fiber and antioxidant contents. On the other hand, techno-functional interactions may occur, affecting the physicochemical and sensory properties of the finished product . For instance, pasta fortified with mango peel powder showed a dietary fiber and polyphenol increase of about two and four times, respectively, resulting in an improved storage stability without changing the textural, cooking, and sensory attributes . In addition, the replacement of 20% of wheat flour with mango peel in soft dough biscuits led to a phenolic content increase of up to eight times, compared to the control . Cakes prepared with watermelon and melon peel powders, as a dietary fiber rich in phenolic compounds, showed improved nutritional and antioxidant properties , while muffins have been successfully fortified with dried apple peel . Probiotic yogurt fortified with 1% fiber-rich pineapple peel powder was produced, remarkably reducing the fermentation time of milk. However, a loss in firmness and storage modulus could be observed . Other examples of non-extractable polyphenol-dietary fiber application can be found in a large variety of food products, including meat products, bread, cereals, pasta, dressings, cookies, biscuits, and extruded or dairy products . 8. Conclusions and Future Perspectives The increasing awareness of lifestyle in human well-being has resulted in a great interest in the health-promoting aspects of food. In this sense, the food industry needs to translate nutritional information into consumer demand through the development of natural food products that provide not only appealing sensorial features and gastronomic innovation but also nutritional and health benefits. In recent years, the attention on polyphenols research regarding human health benefits has expanded from extractable compounds to non-extractable ones. Non-extractable polyphenol-dietary fiber conjugates are a promising natural bio-ingredient, which have been increasingly recognized as important players in food development, nutrition, and human health. There is a new trend and opportunity to investigate more deeply how non-extractable polyphenols bound to dietary fibers are implicated in the prevention or evolution of different chronic diseases and how they can be used in the development of innovative functional foods. Their application as a global entity, having dual properties, shows a great potential for how functional food development can be used to produce innovative food products with improved techno-functional properties. Moreover, these ingredients can be used to improve the nutritional content of food products or be targeted to consumers with a high risk of human health problems (e.g., type II diabetes, obesity, or cardiovascular disease) or to enable personalized nutrition. Although non-extractable polyphenol-dietary fibers present high potential applications for the development of innovative functional ingredients and foods, contributing at the same time to the valorization and exploitation of agri-food by-products and wastes for non-extractable polyphenol-dietary fibers recovery, they have not been implemented on a big scale. Future research should be directed towards the global exploitation of plant-based by-products, which could lead to the generation of new business, revenues streams, and jobs. Thus, the focus should be addressed towards updating the methodological approach for the obtainment of non-extractable polyphenol-dietary fibers in a multidisciplinary and innovative design. An improved understanding regarding this fraction may allow the establishment of a new bridge between their chemical composition, bioavailability, and their ultimate biological function, contributing for the design of sensorial and texture appealing, healthier, and sustainable foods, with this opening up new possibilities for the food industry to address consumer demands. Author Contributions Conceptualization, A.F.; validation, N.M. and V.d.F.; investigation, A.F. resources, A.F.; data curation, A.F.; writing--original draft preparation, A.F.; writing--review and editing, N.M. and V.d.F.; visualization, N.M. and V.d.F.; supervision, V.d.F.; project administration, V.d.F.; funding acquisition, V.d.F. All authors have read and agreed to the published version of the manuscript. Data Availability Statement Not applicable. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Chemical structure of the major nonflavonoids and flavonoids subclasses (aglycones). Figure 2 Chemical structure of some representative polymeric phenolic compounds. Figure 3 Overview of the metabolic fate of polyphenol-dietary fiber conjugates through the gut. 1--polyphenols can be ingested both in free form and conjugated to the dietary fibers components of plant cell walls; 2--only a small percentage of polyphenol-dietary fiber conjugates can be absorbed through the small intestine mucosa. Others reach the lower gut intact, reducing the local oxidative stress and modifying the microbiota composition; 3--non-absorbed polyphenol-dietary fiber conjugates reach the lower gut where they are fermented by the colonic microbiota, releasing absorbable polyphenols and producing absorbable metabolites. The action of the microbiome on dietary fibers produces mainly SCFA and gases; 4--polyphenols and their metabolites can be absorbed into the bloodstream, through passive diffusion and/or active transport, reaching tissues and organs and exerting biological activities. foods-12-01052-t001_Table 1 Table 1 Examples of polyphenol-dietary fibers from fruit and vegetable by-products. Adapted from . By-Product Total Dietary Fiber Total Phenolic Content Reference (%) (mg GAE/100 g) Mango (Mangifera indica L.) 54.2 2170 (TPC) peel flour Cabbage powder 36.7 322 (TAE) Guava (Psidium guajava) peel 48.55 5871 (TEP) Guava (Psidium acutangulum) peel 51.5 5870 (TEP) Acai (Euterpe oleraceae) pulp 71.2 1500 (TEP) Red grape pomace. 74.0 5.63 (TPC) Apple pomace 51.1 1016 (TPC) Blueberry pomace powder 26.2 28.514 (TPC) Carrot (Daucus carota) peels 45.4 1371 (TPC) Banana (peels) 41.6 7168.5 (TPC) Coffee (pulp, husk, silver, skin, 28.0-80.0 1020-1480 (TPC) and spent coffee) Grape (Vitis vinifera L.) pomace 74.5 2630 (TEP) Orange (Citrus aurantium) peel 33.1-36.5 0.51 (TPC) Orange by-product 71.6 40.7 * (albedo,flavedo, and pulp) Plantain peel flour 37.6 771 (TEP) Viburnum opulus (fruits) 38.4 3730 (TPC) Cacao pod husk products 59.0 6893 (SD) Mexican Blackberry 44.3 4016 (TPC) (Rubus fruticosus) residues Passion fruit seeds (DCF) 81.5 41.2 * Pineapple (DFC) 75.8 129 * Papaya pulp (DFC) 59.8 0.47 * Tomato peel 86.1 158.1 (TPC) GAE, gallic acid equivalent; TPC, total phenolic compounds; TAE, tannic acid equivalents; TEP, total extractable phenolics; SD, soluble phenolics; DFC, dietary fibers concentrate; * mg GAE/g. 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PMC10000550 | Diagnostics (Basel) Diagnostics (Basel) diagnostics Diagnostics 2075-4418 MDPI 10.3390/diagnostics13050891 diagnostics-13-00891 Article The Anthropometric Measurement of Nasal Landmark Locations by Digital 2D Photogrammetry Using the Convolutional Neural Network Minh Trieu Nguyen Conceptualization Software Formal analysis Investigation Resources Writing - original draft Visualization Truong Thinh Nguyen Conceptualization Methodology Validation Formal analysis Data curation Writing - review & editing Supervision Project administration * Fu Chia-Hsiang Academic Editor Lee Ta-Jen Academic Editor College of Technology and Design, University of Economics Ho Chi Minh City--UEH, Ho Chi Minh City 72516, Vietnam * Correspondence: [email protected] 26 2 2023 3 2023 13 5 89111 1 2023 15 2 2023 19 2 2023 (c) 2023 by the authors. 2023 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ). Measuring and labeling human face landmarks are time-consuming jobs that are conducted by experts. Currently, the applications of the Convolutional Neural Network (CNN) for image segmentation and classification have made great progress. The nose is arguably one of the most attractive parts of the human face. Rhinoplasty surgery is increasingly performed in females and also in males since surgery can help to enhance patient satisfaction with the resulting perceived beautiful ratio following the neoclassical proportions. In this study, the CNN model is introduced to extract facial landmarks based on medical theories: it learns the landmarks and recognizes them based on feature extraction during training. The comparison between experiments has proved that the CNN model can detect landmarks depending on desired requirements. Anthropometric measurements are carried out by automatic measurement divided into three images with frontal, lateral, and mental views. Measurements are performed including 12 linear distances and 10 angles. The results of the study were evaluated as satisfactory with a normalized mean error (NME) of 1.05, an average error for linear measurements of 0.508 mm, and 0.498deg for angle measurements. Through its results, this study proposed a low-cost automatic anthropometric measurement system with high accuracy and stability. nasal landmarks nasal geography facial morphology anthropometric measurement This research received no external funding. pmc1. Introduction According to many reports, the development of global cosmetic surgery is at a high positive level in Europe and Asia . Facial cosmetic surgery is performed more and more not only in females but also in males . Many studies have reported that most people are dissatisfied with the features of their bodies . Depending on age, profession, gender, and residence area there are different aesthetic and beauty ideals . Indeed, idealized facial beauty is ever-changing and achieved by structural harmony of the face. The nose, occupying the central position of the face, is the most important and impressive feature . Achieving good results in rhinoplasty surgery requires many factors, including an understanding of the morphological characteristics of the nose and its correlation with organs in the face . The measurement and evaluation of its anthropometric parameters and anatomical structure is important in order to have a more comprehensive view of the nasal morphology. In nasal anthropometry, there are not many studies on the root of the nose. Rather, the focus has been on the tip of the nose . In plastic surgery, if the doctor changes the structural indicators of the nose without understanding the relationship between the parameters, it will result in undesirable results and post-surgery complications. With the main goal of ensuring the beauty and safety of plastic surgery, research analyzing and modeling human faces using deep learning is developing rapidly and robustly. The surgical process should focus on safety and patient satisfaction, so the analysis of anthropometric indicators is studied to establish the relationship between facial parts . Moreover, there are quite a few studies focusing on predicting age, gender, emotions, and human recognition . In addition, there are many studies using deep learning in assessing the morphology of the face in some diseases . There are many anthropometric methods used to determine the parameters and position of landmarks. The most popular method is the direct measurement method, which is used by many researchers in papers . The basic measuring device used in anthropometric measurements is usually sliding calipers, and for measuring angles a goniometer is used. In these measurement methods, since the dimensions can be read directly it seems as though the measurer can feel more clear and more confident. However, this method takes a lot of time and the measurer needs a lot of experience to determine the landmarks on soft tissue accurately. In addition, it is difficult to use the direct measurement method to accurately measure sensitive soft tissue locations, such as the eyes, as the measurement is easily disrupted by blinking. During the measurement, the elasticity, thickness, and density of the soft tissue organization also cause errors. Another disadvantage of the direct measurement method is that the result depends on the adjustment process and the measuring force may change the result. Many studies have proposed anthropometric approaches that use 3D images by 3D scanners . The price of 3D image collected systems is very high, so there are few medical facilities that can be used especially in developing countries. Therefore, a low-cost method for collecting anthropometric data is needed, and using 2D images from digital cameras is an approach that deserves attention. In the report by Seo, Y. S et al. , they compared reliability between 3D imaging and 2D photography, and the conclusion showed no difference between the measurements. Another method for anthropometric measurement of the human face is indirect measurement through normalized photographs. Photogrammetry is a technique that has supported anthropometric studies dating back to the 19th century. There are many studies on dimensions from images . Researchers proposed general rules about head posture, camera placement, lighting conditions, and landmark recognition on the face as well as the described methods. The use of normalized photographs makes this method scientific and accurate. Photographs have become important and reliable research materials in anthropometric research and lecturing. With this measuring methodology, there are advantages: the easy determination of points and dimensions; simple operation and easy evaluation; and easy storing and exchanging of data information. In addition, the focus of the camera, lighting, and the psychology of the photographed person can affect the quality of the photograph, which in turn can lead to measurement and analysis errors. Most of the studies for recognizing landmarks on the face have focused on applications in life and entertainment. The recognition of landmarks with the support of deep learning models can be determined automatically, but the accuracy is not high because it is mainly applied in face reconstruction in VR models or to the recognition of key points on the face to detect emotions. In X-ray medical images, studies of cephalometry landmarks are based on random forest models in machine learning . In these studies, the cluster and determination of landmarks were about 70-75% accurate. In addition, the use of artificial neural networks for binary classification yielded an accuracy of about 75.3% . Some studies have used deep learning to determine the x and y coordinates of the waypoints presented in reference . To increase the accuracy, the scientists also used the improved faster R-CNN model called CaphaNet . Rao et al. introduced an approach in orthodontics using the YOLO model to detect the face and then the active shape model (ASM) algorithm was also used to extract the landmarks. The results of their study show well-recognized landmarks with errors from 0-6 mm. However, most landmarks have errors that lead to errors in anthropometric measurements. The YOLO model was used only to detect the face, which reduces the speed of the main model. In another study, 18 landmarks were automatically retrieved using the anthropometric face model . They identified the rotation angle of the face and calibrated it to the frontal angle in order to distinguish other portions of the face using the distance between the eyes as the primary parameter and then facial landmarks were extracted using an anthropometric face model. However, the study only corrects the face in the horizontal direction and is ineffective for significant vertical rotations. In addition, the model's correctness is dependent on how well the two added eyes' centers are identified. This study proposes a method to determine landmarks and nose properties based on the convolutional neural network (CNN). The regression for landmarks is a highly nonlinear mapping function; each point has a corresponding nonlinear mapping function. This study proposes a method for the automatic recognition of facial landmarks. Medical experts label the facial landmarks for data that are used to train and test the extraction model. Anthropometric measurements, performed by medical experts, are applied to collect anthropometric data which are used in many different fields. This process takes a long time and depends on the experience of the performer, so the training costs and time are high. A low-cost automatic system is proposed to help collect anthropometric data quickly and objectively. The experiments confirmed in the final section show that this model achieves the required results compared to other methods. In brief, a low-cost facial landmark location automatic system is introduced, and it is used to collect anthropometry indexes for plastic surgery using the CNN model. This paper includes four parts. Sustainability theories of anthropometric measurements, neoclassical facial proportions, and a deep model for landmark extraction and automatic measurements based on landmarks are presented in Section 2. Next, the experiments are detailed in Section 3 and the conclusions are outlined in Section 4. 2. Materials and Methods 2.1. Nasal Landmarks and Anthropometric Measurements There are many studies on the anthropometry of the external nose and nasal base by direct or indirect measurement through normalized imaging. The facial landmarks are defined below based on the study of LG Farkas . The nasion (denoted n), is the midpoint of the two segments of the nasal bone and the nasofrontal joint. In fact, for researching soft tissue, some studies also determined this point as the most concave point of the soft tissue in the nasofrontal joint along the midline . The glabella (g) is the most convex point of the forehead on the midface. The maxilofrontale (mf) is the point located at the base of the nasal root, and is more medial than the medial corner of the eye and closer to the medial border of the orbital part of the frontal bone. The kyphion (k) (aka hump point) is the highest point on the bridge of the nose. This is where the nose structure is not straight and usually this point is removed to create a straight nose after surgery. The rhinion (r) is the point between the bone and cartilage on the nose. The alare (al) is the outermost point on the curve of each side of the nose. The alar curvature (ac) is the most lateral point on each ala's curved baseline (alar groove). The labiale superius (ls) is the sagittal midline point of the upper lip. The pogonion (pg) is the most protrusive anterior sagittal midline of the chin . In addition, the landmarks on the nasal base are defined in Figure 1. In this study, the anthropometric noses are focused; however, some facial landmarks are also detected to compare the index by neoclassical standards. The landmarks used in this stud are summarized in Table 1 with their name and symbol. The n of straight nose bridges in men is higher than in women, but the proportion of rough nasal bridges in men and women is the opposite. Vietnamese people have two main types of nose bridge: a straight nose bridge and a rough nose bridge. Based on the base of the nose and the line between the base of the nose and the tip of the nose, the bridge of the nose is divided into four types as follows. Firstly, a straight nose is defined by the line connecting the base of the nose and the tip of the nose coinciding with or deviating 1.0 mm from the bridge of the nose at the junction between the bone and the cartilage of the nose. Next, a concave nose is defined by a concave bridge below the line connecting the base of the nose and the top of the nose that coincides with or differs from 1.0 to 5.0 mm at the junction between the bone and cartilage of the nose. Thirdly, a broken nose is defined as having a concave bridge below the junction of the nose root and the tip of the nose more than 5.0 mm at the junction between the bone and cartilage of the nose. Finally, the nose is defined as having a convex bridge over 1.0 mm above the line connecting the base of the nose and the tip of the nose at the junction between the bone and cartilage of the nose. Anthropometric measurements are non-invasive measurements for the collection of human anthropometric data, which are used in identification, and include ethnic identity, sex, and age. Measurements are taken to collect indicators that can be used as a basis for assessing the patient's changes before and after surgery. In this study, 12 linear measurements are taken including the nasal root (mf-mf), nasal height (n-sn), nasal length (n-prn), nasal tip protrusion (sn-prn), nasal width (al-al), anatomical width (ac-ac), inter canthal width (en-en), ala length (ac-prn), nostrils floor width (sbal-sn), columella width (c'-c'), superior width of the columella (cw-cw), and ala thickness (al'-c'). Measurements are defined in Table 2 with the symbol from d1 to d12. Angular measurements are applied including 7 angles on the later view and 3 angles on the mental view. In rhinoplasty surgery, the kyphion angle is of interest to doctors and patients. The presence or absence of this angle depends on the configuration of the nasal bones and often the surgeries to remove it are highly complex. Moreover, anthropometric geometries are also used to predict syndromes and perform genetic screening . The angles used in determining the nasal angles are summarized in Table 3 based on the recommendations of Lazovic et al. and He et al. . As mentioned, rhinoplasty is becoming more and more popular not only in women but also in men. Therefore, the standards of a perceived beautiful nose are proposed as the basis for rhinoplasty surgery. In Vietnam, eight neoclassical standards are used as references in planning rhinoplasty surgery and patient education, which are presented in Table 4. They were defined as beautiful facial proportions as suggested by Le et al. and Porter et al. . It includes the orbitonasal canon, orbital canon, naso-oral canon, nasofacial canon, three sections of the facial profile canon, a nose height equivalent to the ear length, a nose height of approx. 0.43 (n-gn), and a distance of the corner of the mouth to the nasal alare of equal distance to the corner mouth to the center of the pupil. These standards are used as a reference for patients and doctors. In addition to these criteria, the surgery must also pay attention to the patient's respiratory problems and the revised horizontal deviation of the nose . Anthropometric data are used in many different cases such as in post-operative evaluation to design humanoid robots . 2.2. Concept of the CNN Model for Determining the Location of Nasal Landmarks 2.2.1. Data and Pre-Processing Anthropometric measurements based on landmarks play an important role in evaluating the indices of the nose before and after surgery. Currently, landmark extraction and measurement are performed by experts, so these take a great deal of time and high cost for training staff. Moreover, the accuracy of figures depends a lot on measuring equipment and experience. This study proposed an automatic system to extract facial landmarks to collect data, which is used for patients undergoing rhinoplasty surgery. The dataset is collected from a digital camera with three views: frontal, lateral, and mental. Each participating volunteer was studied with three different images for training and testing model. A digital camera is used on an automated collecting system such as Figure 2, thus ensuring that the distance between the camera and people is constant in all of the images. This helps to ensure the accuracy of the extraction and conversion of the factors of the measurements. The automatic system includes a digital camera and a rotating mechanism to take three images for each patient. These images are pre-processed and labeled manually for the training model. Participants in this study were set up to collect the data at the university. This is a non-invasive data collection process that does not affect the volunteers' health, only using images. For ease of handling, the images were collected with a green background. It speeds up the process of extracting facial landmarks. Moreover, to avoid the overtraining case, some data augmentation methods are applied such as rotation, scale, flip, etc. Algorithms of deep learning are proposed to solve each specific problem in different fields, including natural language processing and computer vision. In the computer vision field, the convolutional neural network (CNN), which is a form of feed-forward neural network based on the share weight of kernels , is widely applied in many fields such as agriculture, industry, service, medical, etc. . Extracting facial landmarks is not a new topic but it has not been widely applied in the medical field, especially to tracking anthropometric indexes of rhinoplasty surgery patients. Little research on landmark extraction has been published . Notably, the names and locations of landmarks are determined differently according to the application. In this study, we designed a suitable CNN network to identify landmarks according to medical theory. Accuracy is considered an important factor in medical systems therefore in this study, which is an important impact to decide the success of the study. The basic structure of the CNN includes an input layer, convolutional layers, pooling layers, fully connected layers, and the final output layer. The process of landmark extraction is performed through the following steps. Stage 1. Dataset Pre-processing Images are taken by a digital camera (Canon EOS 60D) which is set up on a system with a green background and the size of the parent image as 5184 x 3456 pixels. The background does not need to be removed when using the CNN model for medical image analysis to collect the anthropometric index. Indeed, accuracy plays an important role. Therefore, to improve the metrics of the applied model, all the of the background should be removed by the threshold method because the background is a green color so this can be conducted quickly and easily. All images are converted to grayscale with optimal resized 416 x 416 images. The feature extraction for removing the noise is subject to increased bias due to the camera's noise . The data are manually labeled by experienced personnel in the medical field. Training data consists of 37 key points with coordinates of each defined landmark Li(xi,yi), where xi and yi are the coordinates of the ith landmarks in the x and y directions, respectively. Similarly, the Oxz are considered for the landmarks in the nasal base. Stage 2. Determining the location of facial landmarks using the CNN model The structure of the proposed model includes six convolutional layers (Conv2d), three max-pooling layers, and three fully connected layers shown in Figure 3. The facial images with three views are fed into a CNN model that has been kernel-convoluted to extract characteristics specific to each class. The convolutional kernel computed parameters are included in the feature map. The pooling layer, which is non-learnable, is used to decrease the model's parameters, speed up the calculation, and prevent overfitting. The input of the CNN model is the gray image with the size of 416 x 416, which is convoluted with kernels to extract the features. The size of the input is large enough to improve the accuracy of the model, which means that the speed of the model is traded off. The facial landmarks are provided with a location for each key point represented by (x,y) or (y,z) coordinates, respectively, which are used to determine the anthropometric dimensions of the face. Then, the coordinates of the landmark are aggregated to appear as Li(xi,yi,zi) which is used to calculate the measurements. After each Conv2d block, the normalization layer is applied to provide data consistency, which helps reduce the overfitting of the model . The parameters of Adam optimizer and a learning rate of 0.001 are applied to the model for training. The output of the model is the landmark's locations on the face. Anthropometric dimensions are applied to track the patient indexes before and after rhinoplasty surgery. The standards for a beautiful nose follow the neoclassical standards proposed by the authors . This paper has great significance in medicine, especially plastic surgery. Moreover, anthropometry is also used as a reference for human robots or designing protective equipment. 2.2.2. Automatic Anthropometric Measurements Based on Facial Landmarks The nose is defined as the most attractive part of the face, and nose-related surgeries are also major challenges for doctors . Plastic surgery standards are determined by anthropometric measurements and are used for monitoring the results of surgery or are used for patient education. Currently, anthropometric measurements are performed manually on the patient's face or through 2D/3D images by medical staff or a semi-automatic system . The accuracy of this process very much depends on the experience and knowledge of the medical staff, and the cost of training human resources is enormous. Therefore, in this study, a system for the automatic anthropometric measurement of patients is proposed. The coordinates of the landmarks are defined as Li(xi,yi,zi) including L(x,y), and L(x,z) coordinates depending on the viewing angle. Measurements are defined in terms of the Euclidean distance for key points, which is calculated by Equation (1) and only in the 2D axes for each stage. (1) d(Li,Lj)Oxy=(xj-xi)2+(yj-yi)2, where d is the distance of the landmark Li(xi,yi) and Lj(xj,yj) in the Oxy coordinate, similarly to the Oxz coordinate. In the external morphology, the angles on the nose are used to evaluate changes, which are used to monitor patients before and after surgery, and also in in patient education. The human head has a 3D shape, so the coordinates of its landmarks must include three values (x,y,z). The Oxyz coordinate system is mounted at the glabella point that is presented in Figure 1. Considering the side view, the nose angles (1-8) are defined in Table 2, and are calculated by the angle between the two vectors from the point of the angle under consideration. Namely, the angle between three landmarks Li, Lj, and Lk at Lj is calculated by the angle created by the two vectors LjLk-. This angle (thi) is defined by Equation (2):(2) thi=arccos(LjLi*-LjLk-||LjL-i||||LjLk-||), where thi is the ith angle which is defined in Table 2 and ||LjLk-|| is a vector with a length of LjLk-. The measurements are calculated, and the next task of the system is to determine the scale to convert the measurement unit of measurements from pixels to actual size for easy use in future applications. This ratio (D) depends on the camera correction factor introduced in ref. , which is expressed by Equation (3). (3) D=ai=0Mkic2i where a is the ratio constant between the pixel size and the actual size; ki is the distortion coefficient of the ith pixel; M is the number of pixels; and c is the Euclidean distance between the coordinate of the ith pixel and the optical center of the image. While collecting the images in the mental view, the head pose is requested at a certain angle for all participants. However, this is qualitative because each person's head size is different, and the staff also do not check this perfectly, so the measurements are affected by the angle of the head. This manifests in an increase in error for figures. Letting T be the coefficient, it is the parameter of the angle of the head that is vertical in the mental view and is defined by Equation (4). (4) T=cos(||dg-prnm||||dg-prnf||), where ||dg-prnm|| is the distance from landmark g to prn in mental view, ||dg-prnf|| is the distance from landmark g to prn in lateral view. Considering the coordinate Oxyz, in the two images taken from the side view and the frontal view the ratio between the two images is also considered a coefficient. Since the distance from the camera to the person is a very small change during the measurement process, this coefficient is usually very small. In this study, the coefficient was defined as the ratio of deviation about the unit length of three views and it was also used to determine the unit conversion ratio D. Linear measurements were performed on 2D images and to ensure the accuracy of the measurements on all three of the different images the coefficients are added. Actual measurements from two landmarks Li and Lj (dac) are converted according to Equation (5) if measurement is made on a frontal view image, Equation (6) if the measurement is taken on a lateral view image and Equation (7) if the measurement is performed on a mental view image. (5) dac=d(Li,Lj)Oxy*D, (6) dac=d(Li,Lj)Oxy*dsdf*D, (7) dac=d(Li,Lj)Oxy*dmdf*D*T, where df is the unit measure value in the frontal view, ds is the unit measure value in the side view, and dm is the unit value in the mental view. 3. Results and Discussion This section describes the experiments performed to evaluate our scheme and discussion in this field. Nowadays, anthropometric data are collected manually based on the knowledge and experiences of the medical staff. This takes a deal of money and is time-consuming for the training process. The error of linear and angle measurements comes from measuring equipment and subjective factors from the operator. Studies on facial landmarks have been carried out in many studies with high accuracy; however, medical applications, especially in anthropometric measurement are limited . Therefore, an automatic anthropometric measurement system is very necessary and suitable. This dataset is collected from 1000 participants of various ages wherein each person has a set of three images taken including the frontal, lateral, and mental view. The images are labeled data on the location data sheet of medical students. The matching process is also checked with the measurement of the physical dimensions of the nose with a caliper. The system is evaluated based on the comparison between 12 linear distances and 10 angles from 37 facial landmarks between the proposed system and the manual method by medical staff. Anthropometric measurements focus on the nose to collect the patient's anthropometric indicators before and after rhinoplasty surgery. Landmarks are carefully marked by medical staff on 203 patients to evaluate the accuracy of the system. The dataset is described in Table 5 including the number of participants, sex, and age. Participants were required to be free of nasal deformities, and to perform facial anthropometric data collection by non-invasive measurement. The actual system proposed in this work is shown in Figure 4. An anthropometric data acquisition system is proposed to ensure that the focal length of the camera and the distance from the camera to the participant are unchanged to ensure the conversion coefficients. Landmarks are defined using a CNN model with input from the digital camera and then pre-processing is applied to reduce the noise and then data are fed into the CNN model. The location of nasal landmarks is extracted with each landmark L(x,y) in the frontal view, L(x,z) in the lateral view, or L(y,z) in the mental view. Then, the coordinates of the landmarks are aggregated according to Oxyz coordinates, namely L(x,y,z) to be used for reconstruction studies from anthropometric measurements. From landmarks, the anthropometric measurements are made using the formulas presented in Section 4. Figure 5 depicts the proposed implementation for the automatic measurement of anthropometric values. Stage 0 is images collected from the camera system. In stage 1, the images are preprocessed with steps such as resizing, reducing noise, and converting gray color. Next, the image is fed into the CNN model to extract the location of the facial landmarks. Finally, calculations are applied to determine the patient's anthropometric dimensions. These metrics are then used to monitor patients or are compared with neoclassical standards. 3.1. Dataset for Evaluation The data used for the evaluation of the model's accuracy are not used for the training process. The data include 203 participants with each person collecting images at three views: frontal, mental, lateral, and marked anthropometrically by specialized staff. The data used for this process consist of 609 images, with a male ratio of 0.49. Images are collected from a digital camera with a green background and are collected from the proposed capture system so the distance from the person to the camera is unchanged during data collection. All collected images are resized to 416 x 416 to match the model's input. These metrics are used for comparison with the system's automated measurements. 3.2. Evaluation of the Accuracy of Landmark Extraction In this experiment, the location of ground truth and predicted landmarks are compared using the dataset of 203 participants. Thirty-seven points are extracted with each point having coordinates x, y, and z for each view. The error of landmarks as evaluated by normalized mean error (NME) is calculated by Formula (8). From three views, each modified and updated landmark has the form Li(x,y,z) with the coordinate system shown in Figure 1. In this study, occlusion cases cannot occur because this is the data collection process, participants are required to stay in fixed positions when collecting images. (8) NME=1N(n=1N(xi-xi_)2W+(yi-y_i)2L+(zi-z_i)2H), where x, y, and z are the coordinates of the ith landmark. W, L, and H are the width, length, and height of the shapes, respectively, for each view. All images are labeled and fed into the CNN model to perform the learning of the parameters shown in Figure 6. In each block, the learnable parameters are shared and updated after the training epoch. Figure 7a shows the results of identifying 37 landmarks on a participant. The error evaluation of the above process is performed by comparing the actual coordinates and the predicted Li coordinates. Actual coordinates are collected by qualified personnel and are considered to be absolute. The average error value in the x, y, and z axes is 0.530, 0.555, and 0.474 mm, respectively, and the standard deviation is 0.269, 0.295, and 0.298 mm, respectively, which means NME = 1.05%. This result is satisfied by experts in the field of anthropometry. To objectively assess the accuracy of the model, we compared the NME defined in Equation (7) and the failure rate summarized in Table 6. Failure was defined as those points with an NME greater than 8% . The CNN model is set up including six Conv layers with a learning rate of 0.001 and an Adam optimize function. The image is fed into the model to train the recognition of 37 landmarks over a space of 416 x 416 with the gray-color space and is trained over 100 epochs to achieve the accuracy shown. The entire program performed in this study was introduced on a Tesla K80 GPU provided by Google Colab. Figure 8 shows the model loss and accuracy of the proposed model where the red line shows training accuracy and loss, and the blue line shows testing accuracy and loss, respectively, and layer parameters of the proposed CNN model are shown in Table 7. The error of landmarks is evaluated based on Formula (7) and Table 6 shows a comparison with the study of Hong et al. . In fact, this comparison only shows that the NME of this model is satisfied when compared to the results of the landmark recognition contest and there is no statistical significance in comparing NME between studies because they are not evaluated on the same dataset. 3.3. Evaluation of the Accuracy of Anthropometric Measurements In this experiment, 12 measurements and 9 measuring angles (for participants without hump K) or 10 measuring angles (for participants with hump K) are taken on 203 people. The data are used to compare the results of manual measurements with the automatic measurement process by the system. Anthropometric data are used to collect the patient's readings before and after the surgery to help the doctors keep track of changes. The criteria of facial beauty are defined in Table 3 and are used to evaluate beauty according to neoclassical standards. The deviation of 12 linear measurements is evaluated using Formula (9). (9) e=|di-di_|, where di is the actual measurement taken by an expert in this field; d_i is the measurement performed by the automated system. In fact, the accuracy of the measurements depends largely on the accuracy of the coordinates of the landmark location and the conversion coefficients. The coordinate system of the automatic measuring system is mounted on the patient's face so face angles will not affect the measurement results. In this study, the anthropometric indices of the nose were focused on for application in rhinoplasty surgery; however, for comparison according to neoclassical standards, some other facial measurements were also taken. Linear and angular measurements are shown in Figure 7b, encompassing measurements used in the clinical diagnosis and monitoring of patient indexes. Anthropometric data are used in identification, racial discrimination, and human gender prediction using the structure of human internal structures such as bones, soft tissues, etc. . Alternatively, data can be used as a basis for designing protective gear for workers in different areas, especially as this can also serve as a reference for making human-shaped robots. The measurement angles are used as the basis of assessment before and after rhinoplasty surgery. Aside from the facial beauty factor, the angles at the nasal base are determined so that the patient's airways can avoid respiratory problems. Seven angles are identified in the lateral view for patients with a hump K that are marked from g1 to g7 in Figure 7b and three angles in the mental view assess the patient's airway. Linear distances are evaluated for accuracy through a dataset consisting of 203 participants, both male and female, and this dataset is different from the training dataset. The distance error is shown in Figure 9a, with the average error of the distances being 0.508 mm. The error values are accepted in the field of anthropometric collection. Figure 9b shows the deviation of the measuring angles which are extracted at the lateral view, which is defined as the deviation between the actual measured angle value and the measured values predicted. The mean error of all 10 measurements is 0.498deg and the mean deviation is 0.287deg. As for g7, this angle exists only when there is a hump point k on the participant's nose, which is required to approximate 180deg after corrective surgery. Anthropometric data of the measured angles are recorded to evaluate the performance of the surgical process. The values representing the anthropometric dimensions of a beautiful nose are shown in Table 4 and are used as a reference for rhinoplasty surgeries. This study is meaningful in collecting anthropometric data for regions and countries in medicine. Moreover, these data are used as references in studies on the characteristics of patients, properties, and gender. 4. Conclusions In this study, a framework is proposed to automatically locate facial landmarks based on three 2D images from three views. Moreover, an automatic system is introduced to collect the image from patients. For medical image analysis, landmarks are defined according to the sustainability theories of medicine, and the accuracy of the recognition processes is highly valued in this field. The landmarks are detected in order to define the facial morphology and appearance, disease-specific geometric characteristics, and local texture features. Anthropometric data are used in many different fields: they are used as a reference for clinical diagnosis for surgery, especially rhinoplasty, and they provide a basic theory for surgery to create a beautiful nose according to perceived standards. In addition, it is used as an input parameter for humanoid robot studies. Finally, the automatic landmark extraction system is satisfied with an NME of 1.05 when tested on 203 Materials. And no file in redmine, please confirm if this part should be deletedlocal participants. Anthropometric measurements were carried out and achieved high accuracy, with an average error for linear measurements of 0.508 mm and 0.498deg for angle measurements. Automatic anthropometric measurement, with the help of computers, is a low-cost method which reduces a great deal of pressure on medical staff. Acknowledgments This research is funded by the University of Economics Ho Chi Minh City, Vietnam. Author Contributions Conceptualization, N.T.T. and N.M.T.; methodology, N.T.T.; software, N.M.T.; validation, N.T.T. and N.M.T.; formal analysis, N.T.T.; investigation, N.M.T.; resources, N.M.T.; data curation, N.T.T.; writing--original draft preparation, N.M.T.; writing--review and editing, N.T.T.; visualization, N.M.T.; supervision, N.T.T.; project administration, N.T.T. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Not applicable. Informed Consent Statement Not applicable. Data Availability Statement Not available. Conflicts of Interest The authors declare no conflict of interest. Figure 1 Location of the facial landmarks in three views. (a) Frontal view. (b) Lateral view. (c) Mental view. Figure 2 An automatic system is proposed to collect the data (including one digital camera and one rotating mechanism). Figure 3 The structure of the proposed model to extract the landmarks, including six conv2d layers, three pooling layers, and three fully connected layers. Figure 4 An actual system to collect the data. Figure 5 Illustration of a proposed anthropometric measurement process including three stages using the CNN model combined with anthropometric measurements. Figure 6 Visualizing the feature map of each block in the CNN model. Figure 7 (a) A total of 37 landmarks are extracted from 3 views by the proposed system. (b) Measurements are made by the proposed formulas. Figure 8 Training loss and testing loss and training accuracy and testing accuracy for the proposed model. Figure 9 Error chart of measurements. (a) The error of the 12 linear measurements. (b) The error of the angle measurements. diagnostics-13-00891-t001_Table 1 Table 1 Names and symbols of facial landmarks that are used in this study . Number Landmark Symbol Number Landmark Symbol 1 Trichion tr 13 Labiale superius ls 2 Glabella g 14 Pogonion pg 3 Nasion n 15 Zygion zy 4 Endocanthion en 16 Maxillofrontale mf 5 Exocanthion ex 17 Subalare sbal 6 Pronasale prn 18 Columellar peak c 7 Kyphion k 19 Columellar waist cw 8 Rhinion r 20 Lateral crus lc 9 Subnasale sn 21 Lateral alar la 10 Alare al 22 Soft triangle c' 11 Alare' al' 23 Cheilion ch 12 Alar curvature ac diagnostics-13-00891-t002_Table 2 Table 2 Defining linear anthropometric measurements. Symbol Measurements Distance d1 Nasal root mf-mf d2 Nasal height n-sn d3 Nasal length n-prn d4 Nasal tip protrusion sn-prn d5 Nasal width al-al d6 Anatomical width ac-ac d7 Inter canthal width en-en d8 Ala length ac-prn d9 Nostril floor width sbal-sn d10 Columella width c'-c' d11 Superior width of the columella cw-cw d12 Ala thickness al'-c' diagnostics-13-00891-t003_Table 3 Table 3 Anthropometric angles. Symbol Name Angle g1 Lateral view Nasofrontal g-n-prn g2 Nasomental n-prn-pg g3 Facial convexity g-sn-pg g4 Nasal tip n-prn-sn g5 Nasolabial c-sn-ls g6 Nasofacial n-prn and g-pg g7 Kyphion n-k-r g8 Mental view Alar slope al-prn-al g9 Interaxial nostril axis-nostril axis g10 Nostril axis nostril axis-horizontal plane diagnostics-13-00891-t004_Table 4 Table 4 Neoclassical facial proportions. Standard Symbol 1 Orbitonasal Canon en-en = al-al 2 Orbital Canon en-en = ex-en 3 Naso-oral Canon ch-ch = 1.5 (al-al) 4 Nasofacial Canon al-al = 0.25 (zy-zy) 5 Threesection Facial Profile Canon n-sn = 1/3 (tr-gn) 6 Nose Height Equal to Ear Length n-sn = sa-sba 7 Nose height approx. 0.43 (n-gn) n-sn = 0.43(n-gn) 8 Distance of the corner of the mouth to nasal alare of equal distance to the corner of the mouth to the center of the pupil ch-en = ch-center (pupil) (Horizontally) diagnostics-13-00891-t005_Table 5 Table 5 Characteristics and standard parameters of datasets. Characteristic Training Dataset Evaluation Dataset Number of participants n = 1000 n = 203 Number of Images 3000 609 Male 152 78 Female 848 125 Age 28.09 +- 12.32 23.09 +- 12.32 diagnostics-13-00891-t006_Table 6 Table 6 Comparison of NME and the failure rate between the proposed method and the method proposed in the study by Z. Hong et al. Failure Rate (%) NME (%) Z. 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PMC10000551 | To clarify the clinical impact and to identify prognostic predictors of surgical intervention for pulmonary metastasis from esophageal cancer, a registry database analysis was performed. From January 2000 to March 2020, patients who underwent resection of pulmonary metastases from primary esophageal cancer at 18 institutions were registered in a database developed by the Metastatic Lung Tumor Study Group of Japan. An amount of 109 cases were reviewed and examined for the prognostic factors for pulmonary metastasectomy of metastases from esophageal cancer. As a result, five-year overall survival after pulmonary metastasectomy was 34.4% and five-year disease-free survival was 22.1%. The multivariate analysis for overall survival revealed that initial recurrence site, maximum tumor size, and duration from primary tumor treatment to lung surgery were selected as the significant prognostic factors (p = 0.043, p = 0.048, and p = 0.037, respectively). In addition, from the results of the multivariate analysis for disease free survival, number of lung metastases, initial recurrence site, duration from primary tumor treatment to lung surgery, and preoperative chemotherapy for lung metastasis were selected as the significant prognostic factors (p = 0.037, p = 0.008, p = 0.010, and p = 0.020, respectively). In conclusion, eligible patients with pulmonary metastasis from esophageal cancer selected based on the identified prognostic predictors would be good candidates for pulmonary metastasectomy. lung metastasis esophageal cancer pulmonary metastasectomy prognostic factor This research received no external funding. pmc1. Introduction Esophageal cancer is one of the most aggressive of all gastrointestinal malignancies. It is the eleventh most common cause of cancer worldwide (473,000 cases) and the sixth most common cause of cancer-related mortality (436,000 deaths) . Five-year relative survival for all stages of esophageal cancer was only 20% in the United States , although advances in multimodal treatment have recently been achieved . In particular, no effective or beneficial systemic treatment has been established for esophageal carcinoma that has metastasized to distant sites. The anticipated incidence of clinically detected distant metastases from esophageal carcinoma ranges from 27.3% to 66.7% . Among the most common sites of metastasis is the lungs . However, the prognosis is differs depending on the site of metastasis, and it is reported that the five-year overall survival (OS) rates were better in patients who underwent lung surgical resection than in those who underwent surgical resection of other organs . In general, pulmonary metastasectomy is one of the standard methods of treatment for patients with pulmonary metastases . In fact, the resection of metastatic lung tumors derived from a variety of malignancies, including colorectal, uterine, head and neck, urinary tract, hepatocellular, and gastric cancers, has become the standard of care in highly selective cases . However, for patients with esophageal cancer, the clinical factors that best predict prognosis remain unknown, although several studies conducted in small numbers of patients have already examined the role of pulmonary resection . In this study, a retrospective analysis was performed using a registry database of the Metastatic Lung Tumor Study Group of Japan (METAL-J) to clarify the clinical impact and to identify prognostic predictors of surgical intervention for pulmonary metastasis from esophageal cancer. 2. Materials and Methods 2.1. Database The METAL-J developed a database to register cases of lung metastases since 1984, and a total of 7251 cases have already been registered. All these patients underwent surgical resection for metastatic lung tumors. This study included cases in which surgery was performed for the purpose of treatment of metastatic lung tumors. Therefore, lung resections for biopsy were excluded. The database contains the following parameters: sex, age, primary tumor status, treatment for primary tumor, metastatic tumor status, date and details of metastases resected, disease-free survival (DFS), OS, and follow-up. This METAL-J registry study was approved by the institutional ethics committee of Teikyo University (current version of approval number: 19-013, approved on 12 April 2019) and other institutions. In this registry, clinical and pathological data from patients with pulmonary metastases from esophageal cancer were collected at 18 institutions in Japan. From these data, patients who underwent curative lung metastasectomy from January 2000 to March 2020 were included in this study. The exclusion criteria were as follows: (1) Cases with unknown prognosis and cases with unknown details of lung surgery; (2) patients with residual tumor in the thoracic cavity on the operative side; and (3) patients with follow-up less than 90 days after lung surgery. Figure 1 shows the flowchart of data selection. This retrospective study was also approved by the institutional ethics committee of Teikyo University (approval number: 21-142, approved on 4 November 2021). Radiological diagnosis, indications for surgery, and pathological diagnosis of metastatic lung tumors were all dependent on the respective institutions. At each participating institution, all the decisions related to the diagnosis and treatment of the tumors were made by an institutional cancer board consisting of oncologists, radiologists, pathologists, surgeons, and related specialists. In general, the metastasectomy was intended to achieve macroscopically complete removal of all pulmonary lesions in patients without any radiographical evidence of extrathoracic metastasis or sign of uncontrolled primary tumors. Regarding the presence of lymph node metastasis, lymph node dissection or sampling was performed in patients who underwent lobectomy or segmentectomy, but not in patients who underwent wedge resection. Wedge resection is performed only when there is no evidence of lymph node metastasis on preoperative PET-CT or other methods. 2.2. Statistical Analysis SPSS version 28 (IBM Corporation, Armonk, NY, USA) and GraphPad Prism version 9.4 (GraphPad Prism Software Inc., San Diego, CA, USA) were used for statistical analyses and to construct figures. A p-value of <0.05 was considered statistically significant. The optimal cutoff values for continuous prognostic indexes were determined with the method established by Budczies et al. described at (accessed on 25 February 2023). This method fits Cox proportional hazard models to the dichotomized variable and the survival variable. The optimal cutoff was defined as the point with the most significant split. OS was defined as the time between pulmonary metastasectomy and death or last follow-up date. DFS was defined as the time between pulmonary metastasectomy and further recurrence, death, or last follow-up date. Patients alive at the date of the last follow-up were censored. Survival curves according to the clinicopathological factors were depicted by means of the Kaplan-Meier method, and comparisons between the curves were performed by the log-rank test. Cox proportional models were used for univariate and multivariable analyses to assess the relationships between the clinicopathological factors and survival after pulmonary metastasectomy. In the Cox proportional analysis, the continuous variables were analyzed instead of using the aforementioned optimal cutoff values. 3. Results A total of 109 patients with pulmonary metastasis from esophageal carcinoma were eligible for the analysis. Table 1 shows the clinicopathological characteristics of the patients. Ninety-seven (89%) were male and one hundred and three (94.5%) of primary tumors were squamous cell carcinoma. As an initial treatment for primary tumor, 36 patients (33%) received esophagostomy alone, 28 patients (26%) received surgery and chemotherapy, 21 patients (19%) received chemotherapy and radiotherapy, and 12 patients (11%) received surgery, chemotherapy, and radiotherapy. Fifteen cases (14%) had detected and treated metastases to other sites prior to the discovery of lung metastases. Multiple lung nodules were detected in 24 cases at the discovery of lung metastases. Fourteen cases (13%) received neoadjuvant chemotherapy for lung metastasis and sixteen cases (15%) received adjuvant chemotherapy, while two patients (2%) received both neoadjuvant and adjuvant chemotherapy. Eighty-six cases (79%) underwent wedge resection for lung metastasis. Three patients (2.8%) had lymph node metastases identified at surgery that were accessible from the ipsilateral thoracic cavity. The mean maximum tumor diameter of resected lung metastases was 16.9 +- 7.7 mm. The mean interval between the first primary treatment and lung surgery was 887 +- 684 days. Disease-free interval from the initial treatment was 664 +- 527 days. After lung metastasis surgery, the median follow-up period was 20 months, and further recurrence was observed in 62 patients, while 54 patients eventually died. Figure 2 shows the survival curve after surgery for lung metastasis. Three-year OS was 48.3% and five-year OS was 34.4%. Median OS was 33.8 months. However, three-year DFS was 40.3% and five-year DFS was 22.1%, while median DFS was 26.6 months. Figure 3 shows a comparison of OS curves regarding patients' characteristics using the log-rank test. When the maximum tumor size of lung metastasis was more than 18 mm, the OS of patients was significantly worse than that of patients with lung metastasis of not less than 18 mm . Furthermore, when multiple lung metastases were found at the time of lung metastasis detection, OS of patients was significantly worse than that of patients with solitary lung metastasis at the time of lung metastasis detection . When the surgery for lung metastasis was performed less than 800 days after the initial treatment of the primary tumor, the OS of patients was significantly worse than that of patients with surgery performed not less than 800 days after the initial treatment of their primary tumor . Finally, when the lymph node metastases identified at surgery were accessible from the ipsilateral thoracic cavity, OS was significantly worse than that without lymph node metastasis . Figure 4 shows a comparison of DFS curves regarding co-factors among patients' characteristics. When the maximum tumor size of lung metastasis was more than 18 mm, DFS of patients was significantly worse than that of patients with lung metastasis of not less than 18 mm . In addition, when multiple lung metastases were found at the time of lung metastasis detection, DFS was significantly worse than that with solitary lung metastasis at lung metastasis detection . When the surgery for lung metastasis was performed at less than 720 days after the initial treatment of the primary tumor, DFS was significantly worse than that with the surgery performed not less than 720 days after the initial treatment of the primary tumor . Finally, when the lymph node metastases found at surgery were accessible from the ipsilateral thoracic cavity, DFS was significantly worse than that without lymph node metastasis . Table 2 shows the result of Cox regression multivariate analysis for OS and DFS after lung metastasectomy. On the basis of the above log-rank analyses, as well as co-factors found to be significant in the previous literature, the following items were selected for the multivariate analysis: number of lung metastases at detection, lymph node metastasis found at lung metastasectomy, initial recurrence site, maximum tumor size of resected lung metastasis, duration from primary tumor treatment to lung surgery, and preoperative chemotherapy for lung metastasis. In the analysis of OS, initial recurrence site, maximum tumor size, and duration from primary tumor treatment to lung surgery were selected as the significant prognostic factors (p = 0.043, p = 0.048, and p = 0.037, respectively). However, in the analysis of DFS, number of lung metastases, initial recurrence site, duration from primary tumor treatment to lung surgery, and preoperative chemotherapy for lung metastasis were selected as the significant prognostic factors (p = 0.037, p = 0.008, p = 0.010, and p = 0.020, respectively). On the other hand, lymph node metastasis and distant metastasis of primary tumors and their treatment did not affect the prognosis after lung metastasis surgery (Supplement Table S1). 4. Discussion This study indicated that long-term survival can be expected in selected patients after pulmonary metastasectomy for esophageal cancer. Furthermore, univariate and multivariate analyses identified the following factors as being associated with good prognosis: single lung metastasis, initial metastasis in the lung, tumor diameter <=18 mm, duration between primary tumor treatment and lung surgery >2 years, and administration of preoperative chemotherapy for lung metastasis. Although pulmonary metastasectomy has been reported as an effective treatment strategy that can be expected to provide long-term survival in various solid tumors, few studies reported the results of pulmonary metastasectomy for esophageal cancer, perhaps because of the extremely poor prognosis of esophageal cancer. This study included 109 cases of pulmonary metastasectomy, which is the largest number of cases compared with any of the previous reports. Thus, the results obtained in this study may provide reliable prognostic factors regarding the impact of pulmonary metastasectomy. Prognosis after recurrence of esophageal cancer is very poor, and the five-year survival rate after recurrence is reported to be approximately 5% . However, it was demonstrated that the survival rate of patients with fewer recurrence sites was better than that of patients with multiple recurrence sites . In addition, curative treatment of oligo-recurrence will improve survival, and many papers reported that oligo-recurrence may be a favorable characteristic of tumor biology . In this respect, pulmonary metastasectomy should be an important treatment option for selected patients with lung metastasis. Moreover, Depypere et al. showed prolonged survival in patients with solitary local recurrence or single solid organ metastases, especially when surgery was performed . In particular, Nobel et al. reported that patients with lung oligometastasis had significantly longer median OS than patients with other sites of oligometastasis . They reported that the median OS of patients with lung oligometastasis was 2.41 years, which is quite similar to our study. Here, the question may arise as to who a good candidate for pulmonary metastasectomy is. The lung is one of the major recurrence sites from esophageal cancer , but metastasectomy will contribute to a better prognosis only in very selected cases. In this selection, the prognostic predictors identified in our study would be helpful for clinicians, and it is clear that the tumor number and size should be defined. The results of the prognostic predictors in the OS analysis suggest that, in cases of preceding recurrence in other organs or recurrence within 800 days from the initial treatment, curative surgery would likely be indicated, preferably after a minimum 800 days, or 2.2 years, after the first treatment, provided that chemotherapy is administered before surgery to prevent further metastatic lesions. On the other hand, neither disease-free interval after the initial treatment nor the time from the initial treatment to the discovery of lung metastases were the significant factors in the univariate and multivariate analysis. This suggests that the impact of pulmonary metastasectomy depends on the timing of the surgery, because the time from the initial treatment for the primary tumor until lung metastasectomy was important, but not so much the disease-free interval after the initial treatment or the time from the initial treatment for the primary tumor until the discovery of lung metastasis. The prognosis of lung tumor treatment was not significantly associated with the N or M factor of the primary tumor or the content of the initial treatment. This database only includes cases in which lung resection was performed for the treatment of metastatic lung tumors. Therefore, we believe that information that might affect the prognosis of the primary tumor was irrelevant to the prognosis after lung resection because of that very selective selection of cases from all cases of esophageal cancer. Conversely, some would argue that the prognosis after pulmonary metastasectomy should account for the possibility that primary lung squamous cell carcinoma might be mixed in the population of "lung metastasis from esophageal cancer", considering that prognosis improved with a longer duration from the initial treatment for the primary tumor. The risk factors for carcinogenesis associated with esophageal squamous cell carcinoma and lung squamous cell carcinoma are very similar . In fact, some cases may be difficult to classify pathologically, even if immunohistochemical staining is performed. In a study of squamous cell carcinomas arising in the lungs after treatment for squamous cell carcinoma derived from the head and neck region, Gurts et al. verified the concordance of clinical information, pathological evaluation, and genetic information by loss of heterozygosity analysis, and determined that half of the cases with a clinical diagnosis of metastatic lung tumor were likely to be primary lung cancers . In this registry study, patients were enrolled who were determined to have lung metastases by the tumor board at each participating institution, and there is no information on the presence or absence of genetic proof of metastasis. Therefore, the possibility of primary lung cancer being mixed in the study population cannot be ruled out. However, it has been reported that a similar trend was observed in a group of patients with complete resection of esophageal cancer, including other recurrence sites , suggesting that the inclusion of primary lung cancer is not enough to account for this trend. Furthermore, five-year OS after wedge resection for solid-type squamous cell carcinoma of the lung (<2 cm) is reported to be approximately 55% ; this prognosis is considerably better than that of the current study group, suggesting that there may be a small number of lung cancer cases in this study population, if any. It is true that it is difficult to distinguish between metastatic and primary lung cancer based solely on a partial tissue biopsy, in view of tumor heterogeneity. In addition, even if the patient has primary lung cancer, surgery can be expected to contribute to the prognosis, even if it is sublobar resection . Therefore, we believe that a curative surgical approach should be justified in cases that meet the prognostic predictors shown in this study. This study has several limitations. First, it was a retrospective study using a registry database whose information was prospectively collected. Therefore, measurement bias was inevitable to a certain extent. We should consider the possibility that potential confounding factors have not been taken into account because of the insufficient information in the database, such as whether nonoperative treatment methods were used as preoperative or postoperative adjuvant therapy and whether the surgical method was open, thoracoscopic, or robotic. Second, the significance of surgery is not fully evaluated because this study was conducted on patients who underwent surgical treatment and did not compare the results with those of patients who did not undergo surgical treatment. However, lung resection is superior to other treatment methods in that it allows pathological diagnosis and treatment of the lesion at the same time. As mentioned above, it is difficult to distinguish esophageal cancer pulmonary metastases from primary lung cancer pathologically, so sufficient pathology specimens would be always required. From this point of view, we believe that lung resection should be recommended in suitable cases. Furthermore, this is a multi-institutional study, and each institution had autonomy over who should be enrolled in this study; therefore, selection bias was inevitable to a certain extent. Moreover, because the study period covered 20 years, not only the preoperative diagnostic procedures but also the treatment may not be uniform due to advances made in the clinic during this time, such as PET-CT and chemotherapy including immunotherapy. It is assumed that not all cases included in this study were diagnosed and treated equally in this regard, and the possibility that the results of this study strongly reflect the influence of some treatments cannot be ruled out. However, even with these limitations, it would be useful to analyze the impact of pulmonary metastasectomy in a large population of patients and to identify prognostic predictors for future treatment selection. 5. Conclusions The surgical indication of pulmonary metastasectomy derived from esophageal cancer should be determined based on prognostic predictors such as tumor size, tumor number, initial metastasis site, duration between primary tumor treatment and metastasectomy, and administration of preoperative chemotherapy for pulmonary metastasis. Highly selected patients with pulmonary metastasis from esophageal cancer would be good candidates for pulmonary metastasectomy, although some primary lung cancer cases can be included in the population. Acknowledgments We are grateful to the members of Teikyo Academic Research Center for their support of METAL-J database management. We also thank H. Nikki March, from Edanz ) (accessed on 14 February 2023) for editing a draft of this manuscript. Supplementary Materials The following supporting information can be downloaded at: File S1: Membership of Metastatic Lung Tumor Study Group of Japan. Table S1. Result of univariate analysis of primary tumor factors for disease free survival and overall survival after lung metastasectomy. Click here for additional data file. Author Contributions Conceptualization: Y.Y.; Methodology: Y.Y. and M.K.; Software: Y.Y.; Validation: J.N., H.K., T.I., M.E., Y.S. (Yukinori Sakao), H.M., K.F., H.H. and M.K.; Formal analysis: Y.Y.; Investigation: Y.Y.; Resources: Y.Y., J.N. and M.K.; Data curation: J.N., M.M., Y.S. (Yasushi Shintani), H.K., T.I., M.E., Y.A., M.C., Y.S. (Yukinori Sakao), I.Y., N.I., H.M., K.F. and H.H.; Writing--original draft preparation: Y.Y.; Writing--review and editing: J.N., M.M., Y.S. (Yasushi Shintani), H.K., T.I., M.E., Y.A., M.C., Y.S. (Yukinori Sakao), I.Y., N.I., H.M., K.F., H.H. and M.K.; Visualization: Y.Y., J.N., H.K., T.I., M.E., Y.S. (Yukinori Sakao), H.M., K.F., H.H. and M.K.; Supervision: J.N., H.K., T.I., M.E., Y.S. (Yukinori Sakao), H.M., K.F., H.H. and M.K.; Project administration: Y.Y., J.N., Y.S. (Yukinori Sakao) and M.K.; Funding acquisition: Y.Y. and M.K. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Teikyo University School of Medicine (approval number: 21-142, approved on 4 November 2021). Informed Consent Statement Patient consent was waived due to the difficulty of acquisition of informed consent in database analysis. Data Availability Statement Data available on request due to restrictions due to privacy and ethical reasons. Conflicts of Interest The authors declare no conflict of interest. Figure 1 The flowchart of patient selection. Figure 2 (a) Overall survival and (b) disease-free survival after pulmonary metastasectomy. The survival curves are depicted as solid lines and 95% confidence intervals are drawn in halftone. The numbers of patients at risk at lung surgery at 20, 40, and 60 months after lung surgery are reported at the bottom of the curves. Three-year overall survival was 48.3% and five-year overall survival was 34.4%. Three-year disease-free survival was 40.3% and five-year disease-free survival was 22.1%. Figure 3 Comparison of overall survival after pulmonary metastasectomy regarding patients' characteristics. (a) Maximum tumor size of lung metastasis was more than 18 mm and OS was significantly worse than that of patients with lung metastasis of not less than 18 mm (p = 0.027). (b) When multiple lung metastases were found at the time of lung metastasis detection, OS was significantly worse than that with solitary lung metastasis at the lung metastasis detection (p = 0.012). (c) When the surgery for lung metastasis was performed less than 800 days after the initial treatment of the primary tumor, OS was significantly worse than that when the surgery was performed not less than 800 days after the initial treatment of the primary tumor (p = 0.002). (d) When the lymph node metastases found at surgery were accessible from the ipsilateral thoracic cavity, OS was significantly worse than that without lymph node metastasis (p = 0.003). Figure 4 Comparison of disease survival after pulmonary metastasectomy regarding patients' characteristics. (a) When maximum tumor size of lung metastasis was more than 18 mm, DFS was significantly worse than that with lung metastasis of not less than 18 mm (p = 0.047). (b) When multiple lung metastases were found at the time of lung metastasis detection, DFS was significantly worse than that with solitary lung metastasis at lung metastasis detection (p = 0.003). (c) When the surgery for lung metastasis was performed less than 720 days after the initial treatment of primary tumor, DFS was significantly worse than that when the surgery was performed not less than 720 days after the initial treatment of the primary tumor (p = 0.013). (d) When the lymph node metastases found at surgery were accessible from the ipsilateral thoracic cavity, DFS was significantly worse than that without lymph node metastasis (p = 0.02). cancers-15-01472-t001_Table 1 Table 1 Patients' characteristics. Variables Number (%)/Average Sex Male 97 (89.0) Female 12 (11.0) Histology of primary tumor SqCC 103 (94.5) ADC 3 (2.8) Others 3 (2.8) Initial treatment for primary tumor Surgery alone 36 (33.0) Chemotherapy alone 3 (2.8) Radiotherapy alone 1 (0.9) Surgery and Chemotherapy 28 (25.7) Surgery and Radiotherapy 3 (2.8) Chemotherapy and Radiotherapy 21 (19.3) Surgery, Chemotherapy, and Radiotherapy 12 (11.0) Not available 5 (4.6) pathological N stage of primary tumor N0 27 (24.8) N1-3 63 (57.8) pathological M stage of primary tumor M0 73 (67.0) M1 19 (17.4) Initial recurrence site Pulmonary 94 (86.2) Extrapulmonary 15 (13.8) Number of tumors at detection of lung metastasis 1 81 (74.3) 2-4 24 (22.0) perioperative chemotherapy for lung metastasis Before lung surgery 14 (12.8) After Lung surgery 16 (14.7) The type of surgery for lung metastasis wedge resection 86 (78.9) segmentectomy 9 (8.3) lobectomy 14 (12.8) The side of surgery for lung metastasis right 59 (54.1) left 38 (34.9) both side 12 (11.0) Lymph node metastasis found at lung surgery None 106 (97.2) Hilar lymph node metastasis 1 (0.9) Mediastinal lymph node metastasis 2 (1.8) Patients' age at lung surgery 67 +- 9 Maximum tumor size of resected lung metastasis (mm) 16.9 +- 7.7 Disease free interval from the initial treatment (days) 664 +- 527 Duration from primary tumor treatment to lung surgery (days) 887 +- 684 cancers-15-01472-t002_Table 2 Table 2 Results of multivariate analysis for disease-free survival and overall survival after lung metastasectomy. Factors Overall Survival Disease Free Survival HR (95% CI) p-Value HR (95% CI) p-Value Number of lung metastases at the detection 1.69 (0.95-3.00) 0.072 1.66 (1.03-2.66) 0.037 * Lymph node metastasis found at lung metastasectomy negative Reference 0.24 Reference 0.503 positive 2.33 (0.58-9.42) 1.57 (0.42-5.92) Initial recurrence site pulmonary Reference 0.043 * Reference 0.008 * extrapulmonary 2.65 (1.03-6.80) 2.89 (1.32-6.36) Maximum tumor size of resected lung metastasis 1.52 (1.00-2.29) 0.048 * 1.30 (0.92-1.84) 0.14 Duration from primary tumor treatment to lung surgery 0.99 (0.99-1.00) 0.037 * 0.99 (0.99-1.00) 0.010 * Preoperative chemotherapy for lung metastasis Undone Reference 0.082 Reference 0.02 * Done 0.38 (0.13-1.13) 0.33 (0.13-0.84) HR: Hazard Ratio, CI: Confidence Interval. * p < 0.05 Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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